diff --git a/security_scanning/examples/apps/poetry.lock b/security_scanning/examples/apps/poetry.lock
index f296ae759b..caa82c99ac 100644
--- a/security_scanning/examples/apps/poetry.lock
+++ b/security_scanning/examples/apps/poetry.lock
@@ -13,13 +13,13 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/auto_deploy/poetry.lock b/security_scanning/examples/auto_deploy/poetry.lock
index 201eb0b971..e4e3db4c5d 100644
--- a/security_scanning/examples/auto_deploy/poetry.lock
+++ b/security_scanning/examples/auto_deploy/poetry.lock
@@ -261,13 +261,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/draft_target_model/poetry.lock b/security_scanning/examples/draft_target_model/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/draft_target_model/poetry.lock
+++ b/security_scanning/examples/draft_target_model/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/eagle/poetry.lock b/security_scanning/examples/eagle/poetry.lock
index 1f19cc5d1f..1a7b36af59 100644
--- a/security_scanning/examples/eagle/poetry.lock
+++ b/security_scanning/examples/eagle/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1767,13 +1767,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/llm-eval/lm-eval-harness/poetry.lock b/security_scanning/examples/llm-eval/lm-eval-harness/poetry.lock
index dcc80adc49..a147921560 100644
--- a/security_scanning/examples/llm-eval/lm-eval-harness/poetry.lock
+++ b/security_scanning/examples/llm-eval/lm-eval-harness/poetry.lock
@@ -213,13 +213,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/lookahead/poetry.lock b/security_scanning/examples/lookahead/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/lookahead/poetry.lock
+++ b/security_scanning/examples/lookahead/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/medusa/poetry.lock b/security_scanning/examples/medusa/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/medusa/poetry.lock
+++ b/security_scanning/examples/medusa/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/baichuan/poetry.lock b/security_scanning/examples/models/contrib/baichuan/poetry.lock
index 23ccdc0e92..2977c6aab1 100644
--- a/security_scanning/examples/models/contrib/baichuan/poetry.lock
+++ b/security_scanning/examples/models/contrib/baichuan/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -781,13 +781,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -800,13 +800,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1967,13 +1967,13 @@ transformers = ">=4.26.1"
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/bloom/poetry.lock b/security_scanning/examples/models/contrib/bloom/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/models/contrib/bloom/poetry.lock
+++ b/security_scanning/examples/models/contrib/bloom/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/chatglm-6b/poetry.lock b/security_scanning/examples/models/contrib/chatglm-6b/poetry.lock
index c53e5cbbc1..4bcc69beb5 100644
--- a/security_scanning/examples/models/contrib/chatglm-6b/poetry.lock
+++ b/security_scanning/examples/models/contrib/chatglm-6b/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1883,13 +1883,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/chatglm2-6b/poetry.lock b/security_scanning/examples/models/contrib/chatglm2-6b/poetry.lock
index c53e5cbbc1..4bcc69beb5 100644
--- a/security_scanning/examples/models/contrib/chatglm2-6b/poetry.lock
+++ b/security_scanning/examples/models/contrib/chatglm2-6b/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1883,13 +1883,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/chatglm3-6b-32k/poetry.lock b/security_scanning/examples/models/contrib/chatglm3-6b-32k/poetry.lock
index c53e5cbbc1..4bcc69beb5 100644
--- a/security_scanning/examples/models/contrib/chatglm3-6b-32k/poetry.lock
+++ b/security_scanning/examples/models/contrib/chatglm3-6b-32k/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1883,13 +1883,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/dbrx/poetry.lock b/security_scanning/examples/models/contrib/dbrx/poetry.lock
index bea6ace5af..ad71da46bb 100644
--- a/security_scanning/examples/models/contrib/dbrx/poetry.lock
+++ b/security_scanning/examples/models/contrib/dbrx/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1765,13 +1765,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/deepseek_v1/poetry.lock b/security_scanning/examples/models/contrib/deepseek_v1/poetry.lock
index 0b138d080f..a9fec7edd0 100644
--- a/security_scanning/examples/models/contrib/deepseek_v1/poetry.lock
+++ b/security_scanning/examples/models/contrib/deepseek_v1/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1713,13 +1713,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/deepseek_v2/poetry.lock b/security_scanning/examples/models/contrib/deepseek_v2/poetry.lock
index 0f448fc0a3..00f49a484b 100644
--- a/security_scanning/examples/models/contrib/deepseek_v2/poetry.lock
+++ b/security_scanning/examples/models/contrib/deepseek_v2/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1713,13 +1713,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/gptj/poetry.lock b/security_scanning/examples/models/contrib/gptj/poetry.lock
index 0b138d080f..a9fec7edd0 100644
--- a/security_scanning/examples/models/contrib/gptj/poetry.lock
+++ b/security_scanning/examples/models/contrib/gptj/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1713,13 +1713,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/gptneox/poetry.lock b/security_scanning/examples/models/contrib/gptneox/poetry.lock
index 0b138d080f..a9fec7edd0 100644
--- a/security_scanning/examples/models/contrib/gptneox/poetry.lock
+++ b/security_scanning/examples/models/contrib/gptneox/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1713,13 +1713,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/grok/poetry.lock b/security_scanning/examples/models/contrib/grok/poetry.lock
index a1f069b476..9c2dd8c4ee 100644
--- a/security_scanning/examples/models/contrib/grok/poetry.lock
+++ b/security_scanning/examples/models/contrib/grok/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -881,13 +881,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -900,13 +900,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1630,13 +1630,13 @@ nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
 name = "nvidia-nccl-cu12"
-version = "2.28.9"
+version = "2.29.2"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nccl_cu12-2.28.9-py3-none-manylinux_2_18_aarch64.whl", hash = "sha256:50a36e01c4a090b9f9c47d92cec54964de6b9fcb3362d0e19b8ffc6323c21b60"},
-    {file = "nvidia_nccl_cu12-2.28.9-py3-none-manylinux_2_18_x86_64.whl", hash = "sha256:485776daa8447da5da39681af455aa3b2c2586ddcf4af8772495e7c532c7e5ab"},
+    {file = "nvidia_nccl_cu12-2.29.2-py3-none-manylinux_2_18_aarch64.whl", hash = "sha256:0712e55c067965c6093cc793a9bbcc5f37b5b47248e9ebf8ae3af06867757587"},
+    {file = "nvidia_nccl_cu12-2.29.2-py3-none-manylinux_2_18_x86_64.whl", hash = "sha256:3a9a0bf4142126e0d0ed99ec202579bef8d007601f9fab75af60b10324666b12"},
 ]
 
 [[package]]
@@ -2678,13 +2678,13 @@ test = ["absl-py (>=1.4.0)", "jax (>=0.4.23)", "omegaconf (>=2.0.0)", "pydantic
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/hyperclovax/poetry.lock b/security_scanning/examples/models/contrib/hyperclovax/poetry.lock
index 24b481f58c..5af934d652 100644
--- a/security_scanning/examples/models/contrib/hyperclovax/poetry.lock
+++ b/security_scanning/examples/models/contrib/hyperclovax/poetry.lock
@@ -2,13 +2,13 @@
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -290,13 +290,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -309,13 +309,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1040,13 +1040,13 @@ dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
 
 [[package]]
 name = "timm"
-version = "1.0.23"
+version = "1.0.24"
 description = "PyTorch Image Models"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "timm-1.0.23-py3-none-any.whl", hash = "sha256:8b351810c714ede9a3c2f0fd9845c5d312548cc4397967ffd49334e9cbc8e165"},
-    {file = "timm-1.0.23.tar.gz", hash = "sha256:32e8e678212746d493a57438071c34f10b433f0c8167285bfd9d7607238d9d35"},
+    {file = "timm-1.0.24-py3-none-any.whl", hash = "sha256:8301ac783410c6ad72c73c49326af6d71a9e4d1558238552796e825c2464913f"},
+    {file = "timm-1.0.24.tar.gz", hash = "sha256:c7b909f43fe2ef8fe62c505e270cd4f1af230dfbc37f2ee93e3608492b9d9a40"},
 ]
 
 [package.dependencies]
@@ -1220,13 +1220,13 @@ tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
@@ -1250,4 +1250,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "bd26d980de5c246fd11414019d9af4702f9a970537f160246c394ce9852a9c33"
+content-hash = "c192429330d74a80d01bb76235d36a9d5ae31fff1b4ad57a0a22f7439a6843e0"
diff --git a/security_scanning/examples/models/contrib/hyperclovax/pyproject.toml b/security_scanning/examples/models/contrib/hyperclovax/pyproject.toml
index a9b6235891..82f8cbf9ef 100644
--- a/security_scanning/examples/models/contrib/hyperclovax/pyproject.toml
+++ b/security_scanning/examples/models/contrib/hyperclovax/pyproject.toml
@@ -8,7 +8,7 @@ readme = "README.md"
 [tool.poetry.dependencies]
 python = ">=3.10,<3.13"
 decord = "^0.6.0"
-timm = "^1.0.23"
+timm = "^1.0.24"
 av = "^16.0.1"
 
 
diff --git a/security_scanning/examples/models/contrib/internlm/poetry.lock b/security_scanning/examples/models/contrib/internlm/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/models/contrib/internlm/poetry.lock
+++ b/security_scanning/examples/models/contrib/internlm/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/jais/poetry.lock b/security_scanning/examples/models/contrib/jais/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/models/contrib/jais/poetry.lock
+++ b/security_scanning/examples/models/contrib/jais/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/mmdit/poetry.lock b/security_scanning/examples/models/contrib/mmdit/poetry.lock
index 67e00bf1a9..9f2df3b29d 100644
--- a/security_scanning/examples/models/contrib/mmdit/poetry.lock
+++ b/security_scanning/examples/models/contrib/mmdit/poetry.lock
@@ -2,13 +2,13 @@
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/mpt/poetry.lock b/security_scanning/examples/models/contrib/mpt/poetry.lock
index 0b138d080f..a9fec7edd0 100644
--- a/security_scanning/examples/models/contrib/mpt/poetry.lock
+++ b/security_scanning/examples/models/contrib/mpt/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1713,13 +1713,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/opt/poetry.lock b/security_scanning/examples/models/contrib/opt/poetry.lock
index 0b138d080f..a9fec7edd0 100644
--- a/security_scanning/examples/models/contrib/opt/poetry.lock
+++ b/security_scanning/examples/models/contrib/opt/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1713,13 +1713,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/skywork/poetry.lock b/security_scanning/examples/models/contrib/skywork/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/models/contrib/skywork/poetry.lock
+++ b/security_scanning/examples/models/contrib/skywork/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/contrib/smaug/poetry.lock b/security_scanning/examples/models/contrib/smaug/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/models/contrib/smaug/poetry.lock
+++ b/security_scanning/examples/models/contrib/smaug/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/core/commandr/poetry.lock b/security_scanning/examples/models/core/commandr/poetry.lock
index 0b138d080f..a9fec7edd0 100644
--- a/security_scanning/examples/models/core/commandr/poetry.lock
+++ b/security_scanning/examples/models/core/commandr/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1713,13 +1713,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/core/gemma/poetry.lock b/security_scanning/examples/models/core/gemma/poetry.lock
index d5cbcb3020..1df2fa84af 100644
--- a/security_scanning/examples/models/core/gemma/poetry.lock
+++ b/security_scanning/examples/models/core/gemma/poetry.lock
@@ -192,13 +192,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -872,13 +872,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -891,13 +891,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -2708,13 +2708,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/core/glm-4-9b/poetry.lock b/security_scanning/examples/models/core/glm-4-9b/poetry.lock
index c53e5cbbc1..4bcc69beb5 100644
--- a/security_scanning/examples/models/core/glm-4-9b/poetry.lock
+++ b/security_scanning/examples/models/core/glm-4-9b/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1883,13 +1883,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/core/gpt/poetry.lock b/security_scanning/examples/models/core/gpt/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/models/core/gpt/poetry.lock
+++ b/security_scanning/examples/models/core/gpt/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/core/nemotron/poetry.lock b/security_scanning/examples/models/core/nemotron/poetry.lock
index 0b138d080f..a9fec7edd0 100644
--- a/security_scanning/examples/models/core/nemotron/poetry.lock
+++ b/security_scanning/examples/models/core/nemotron/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1713,13 +1713,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/core/phi/poetry.lock b/security_scanning/examples/models/core/phi/poetry.lock
index 5b9482ae01..db07266c65 100644
--- a/security_scanning/examples/models/core/phi/poetry.lock
+++ b/security_scanning/examples/models/core/phi/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -782,13 +782,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -801,13 +801,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1776,13 +1776,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/core/qwen/poetry.lock b/security_scanning/examples/models/core/qwen/poetry.lock
index fb3d235bdf..95f4cf1e21 100644
--- a/security_scanning/examples/models/core/qwen/poetry.lock
+++ b/security_scanning/examples/models/core/qwen/poetry.lock
@@ -231,13 +231,13 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -3399,13 +3399,13 @@ transformers = ">=4.26.1"
 
 [[package]]
 name = "typer"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer-0.21.0-py3-none-any.whl", hash = "sha256:c79c01ca6b30af9fd48284058a7056ba0d3bf5cf10d0ff3d0c5b11b68c258ac6"},
-    {file = "typer-0.21.0.tar.gz", hash = "sha256:c87c0d2b6eee3b49c5c64649ec92425492c14488096dfbc8a0c2799b2f6f9c53"},
+    {file = "typer-0.21.1-py3-none-any.whl", hash = "sha256:7985e89081c636b88d172c2ee0cfe33c253160994d47bdfdc302defd7d1f1d01"},
+    {file = "typer-0.21.1.tar.gz", hash = "sha256:ea835607cd752343b6b2b7ce676893e5a0324082268b48f27aa058bdb7d2145d"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/models/core/qwenvl/poetry.lock b/security_scanning/examples/models/core/qwenvl/poetry.lock
index 494d8b0fe3..a19aa6b0d0 100644
--- a/security_scanning/examples/models/core/qwenvl/poetry.lock
+++ b/security_scanning/examples/models/core/qwenvl/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -945,13 +945,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -964,13 +964,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -3034,13 +3034,13 @@ tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/ngram/poetry.lock b/security_scanning/examples/ngram/poetry.lock
index c062c6677b..60b7e78b1e 100644
--- a/security_scanning/examples/ngram/poetry.lock
+++ b/security_scanning/examples/ngram/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1781,13 +1781,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/quantization/poetry.lock b/security_scanning/examples/quantization/poetry.lock
index f96fe49c3e..fa3dfba0e4 100644
--- a/security_scanning/examples/quantization/poetry.lock
+++ b/security_scanning/examples/quantization/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -736,13 +736,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -755,13 +755,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1934,13 +1934,13 @@ transformers = ">=4.26.1"
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/ray_orchestrator/poetry.lock b/security_scanning/examples/ray_orchestrator/poetry.lock
index 1bedee5fcc..b6c048c435 100644
--- a/security_scanning/examples/ray_orchestrator/poetry.lock
+++ b/security_scanning/examples/ray_orchestrator/poetry.lock
@@ -215,17 +215,6 @@ files = [
     {file = "attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11"},
 ]
 
-[[package]]
-name = "cachetools"
-version = "6.2.4"
-description = "Extensible memoizing collections and decorators"
-optional = false
-python-versions = ">=3.9"
-files = [
-    {file = "cachetools-6.2.4-py3-none-any.whl", hash = "sha256:69a7a52634fed8b8bf6e24a050fb60bff1c9bd8f6d24572b99c32d4e71e62a51"},
-    {file = "cachetools-6.2.4.tar.gz", hash = "sha256:82c5c05585e70b6ba2d3ae09ea60b79548872185d2f24ae1f2709d37299fd607"},
-]
-
 [[package]]
 name = "certifi"
 version = "2026.1.4"
@@ -585,29 +574,28 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.46.0"
+version = "2.47.0"
 description = "Google Authentication Library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "google_auth-2.46.0-py3-none-any.whl", hash = "sha256:fa51659c3745cb7024dd073f4ab766222767ea5f7dee2472110eaa03c9dbd2cb"},
-    {file = "google_auth-2.46.0.tar.gz", hash = "sha256:cb04c071a73394a6e3b9e48c1a7f48506001175b33e9679587a0f5320a21a34d"},
+    {file = "google_auth-2.47.0-py3-none-any.whl", hash = "sha256:c516d68336bfde7cf0da26aab674a36fedcf04b37ac4edd59c597178760c3498"},
+    {file = "google_auth-2.47.0.tar.gz", hash = "sha256:833229070a9dfee1a353ae9877dcd2dec069a8281a4e72e72f77d4a70ff945da"},
 ]
 
 [package.dependencies]
-cachetools = ">=2.0.0,<7.0"
 pyasn1-modules = ">=0.2.1"
 rsa = ">=3.1.4,<5"
 
 [package.extras]
 aiohttp = ["aiohttp (>=3.6.2,<4.0.0)", "requests (>=2.20.0,<3.0.0)"]
-cryptography = ["cryptography (<39.0.0)", "cryptography (>=38.0.3)"]
+cryptography = ["cryptography (>=38.0.3)"]
 enterprise-cert = ["cryptography", "pyopenssl"]
-pyjwt = ["cryptography (<39.0.0)", "cryptography (>=38.0.3)", "pyjwt (>=2.0)"]
-pyopenssl = ["cryptography (<39.0.0)", "cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
+pyjwt = ["cryptography (>=38.0.3)", "pyjwt (>=2.0)"]
+pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0)"]
-testing = ["aiohttp (<3.10.0)", "aiohttp (>=3.6.2,<4.0.0)", "aioresponses", "cryptography (<39.0.0)", "cryptography (<39.0.0)", "cryptography (>=38.0.3)", "cryptography (>=38.0.3)", "flask", "freezegun", "grpcio", "oauth2client", "packaging", "pyjwt (>=2.0)", "pyopenssl (<24.3.0)", "pyopenssl (>=20.0.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-localserver", "pyu2f (>=0.1.5)", "requests (>=2.20.0,<3.0.0)", "responses", "urllib3"]
+testing = ["aiohttp (<3.10.0)", "aiohttp (>=3.6.2,<4.0.0)", "aioresponses", "cryptography (>=38.0.3)", "cryptography (>=38.0.3)", "flask", "freezegun", "grpcio", "oauth2client", "packaging", "pyjwt (>=2.0)", "pyopenssl (<24.3.0)", "pyopenssl (>=20.0.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-localserver", "pyu2f (>=0.1.5)", "requests (>=2.20.0,<3.0.0)", "responses", "urllib3"]
 urllib3 = ["packaging", "urllib3"]
 
 [[package]]
diff --git a/security_scanning/examples/redrafter/poetry.lock b/security_scanning/examples/redrafter/poetry.lock
index e286cbc156..fa46e1e5db 100644
--- a/security_scanning/examples/redrafter/poetry.lock
+++ b/security_scanning/examples/redrafter/poetry.lock
@@ -181,13 +181,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -771,13 +771,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "1.2.3"
+version = "1.2.4"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 files = [
-    {file = "huggingface_hub-1.2.3-py3-none-any.whl", hash = "sha256:c9b7a91a9eedaa2149cdc12bdd8f5a11780e10de1f1024718becf9e41e5a4642"},
-    {file = "huggingface_hub-1.2.3.tar.gz", hash = "sha256:4ba57f17004fd27bb176a6b7107df579865d4cde015112db59184c51f5602ba7"},
+    {file = "huggingface_hub-1.2.4-py3-none-any.whl", hash = "sha256:2db69b91877d9d34825f5cd2a63b94f259011a77dcf761b437bf510fbe9522e9"},
+    {file = "huggingface_hub-1.2.4.tar.gz", hash = "sha256:7a1d9ec4802e64372d1d152d69fb8e26d943f15a2289096fbc8e09e7b90c21a5"},
 ]
 
 [package.dependencies]
@@ -790,13 +790,13 @@ pyyaml = ">=5.1"
 shellingham = "*"
 tqdm = ">=4.42.1"
 typer-slim = "*"
-typing-extensions = ">=3.7.4.3"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
 all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
-hf-xet = ["hf-xet (>=1.1.3,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
 mcp = ["mcp (>=1.8.0)"]
 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
@@ -1791,13 +1791,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "typer-slim"
-version = "0.21.0"
+version = "0.21.1"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typer_slim-0.21.0-py3-none-any.whl", hash = "sha256:92aee2188ac6fc2b2924bd75bb61a340b78bd8cd51fd9735533ce5a856812c8e"},
-    {file = "typer_slim-0.21.0.tar.gz", hash = "sha256:f2dbd150cfa0fead2242e21fa9f654dfc64773763ddf07c6be9a49ad34f79557"},
+    {file = "typer_slim-0.21.1-py3-none-any.whl", hash = "sha256:6e6c31047f171ac93cc5a973c9e617dbc5ab2bddc4d0a3135dc161b4e2020e0d"},
+    {file = "typer_slim-0.21.1.tar.gz", hash = "sha256:73495dd08c2d0940d611c5a8c04e91c2a0a98600cbd4ee19192255a233b6dbfd"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/examples/trtllm-eval/poetry.lock b/security_scanning/examples/trtllm-eval/poetry.lock
index 960415b1f9..f13e70ad4a 100644
--- a/security_scanning/examples/trtllm-eval/poetry.lock
+++ b/security_scanning/examples/trtllm-eval/poetry.lock
@@ -213,13 +213,13 @@ typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
diff --git a/security_scanning/metadata.json b/security_scanning/metadata.json
index 2665c7ff38..567d8ffa7a 100644
--- a/security_scanning/metadata.json
+++ b/security_scanning/metadata.json
@@ -1,4 +1,4 @@
 {
-  "commit_hash": "9cae7277ea9cc41242ede456ea1955902962f971",
-  "timestamp": "2026-01-06T02:39:48Z"
+  "commit_hash": "6095c80e560c612b8a8f4ff70e8930edf7798d21",
+  "timestamp": "2026-01-07T02:39:54Z"
 }
diff --git a/security_scanning/poetry.lock b/security_scanning/poetry.lock
index bcc90cf0ea..6d04c2d679 100644
--- a/security_scanning/poetry.lock
+++ b/security_scanning/poetry.lock
@@ -245,13 +245,13 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.12.0"
+version = "4.12.1"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.12.0-py3-none-any.whl", hash = "sha256:dad2376a628f98eeca4881fc56cd06affd18f659b17a747d3ff0307ced94b1bb"},
-    {file = "anyio-4.12.0.tar.gz", hash = "sha256:73c693b567b0c55130c104d0b43a9baf3aa6a31fc6110116509f27bf75e21ec0"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
@@ -2834,13 +2834,13 @@ dill = ">=0.3.8"
 
 [[package]]
 name = "narwhals"
-version = "2.14.0"
+version = "2.15.0"
 description = "Extremely lightweight compatibility layer between dataframe libraries"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "narwhals-2.14.0-py3-none-any.whl", hash = "sha256:b56796c9a00179bd757d15282c540024e1d5c910b19b8c9944d836566c030acf"},
-    {file = "narwhals-2.14.0.tar.gz", hash = "sha256:98be155c3599db4d5c211e565c3190c398c87e7bf5b3cdb157dece67641946e0"},
+    {file = "narwhals-2.15.0-py3-none-any.whl", hash = "sha256:cbfe21ca19d260d9fd67f995ec75c44592d1f106933b03ddd375df7ac841f9d6"},
+    {file = "narwhals-2.15.0.tar.gz", hash = "sha256:a9585975b99d95084268445a1fdd881311fa26ef1caa18020d959d5b2ff9a965"},
 ]
 
 [package.extras]
diff --git a/setup.py b/setup.py
index 3b0bae13a0..d189da40dd 100644
--- a/setup.py
+++ b/setup.py
@@ -173,7 +173,6 @@ def extract_from_precompiled(precompiled_location: str, package_data: List[str],
     - Remote URL: Downloads and extracts from URL (wheel or tar.gz)
     """
     import fnmatch
-    import glob
     import shutil
     import tarfile
     import zipfile
@@ -183,6 +182,7 @@ def extract_from_precompiled(precompiled_location: str, package_data: List[str],
 
     # Handle local directory (assuming repo structure)
     if os.path.isdir(precompiled_location):
+        precompiled_location = os.path.abspath(precompiled_location)
         print(
             f"Using local directory as precompiled source: {precompiled_location}"
         )
@@ -192,14 +192,13 @@ def extract_from_precompiled(precompiled_location: str, package_data: List[str],
                 f"Directory {precompiled_location} does not contain a tensorrt_llm folder."
             )
 
-        for pattern in package_data:
-            full_pattern = os.path.join(source_tensorrt_llm, pattern)
-            for src_file in glob.glob(full_pattern, recursive=True):
-                if not os.path.isfile(src_file):
-                    continue
-
+        # Walk through all files and match using fnmatch (consistent with wheel extraction)
+        for root, dirs, files in os.walk(source_tensorrt_llm):
+            for filename in files:
+                src_file = os.path.join(root, filename)
+                # Get path relative to precompiled_location (e.g., "tensorrt_llm/libs/libtensorrt_llm.so")
                 rel_path = os.path.relpath(src_file, precompiled_location)
-                dst_file = rel_path  # e.g., "tensorrt_llm/libs/libtensorrt_llm.so"
+                dst_file = rel_path
 
                 # Skip yaml files
                 if dst_file.endswith(".yaml"):
@@ -214,6 +213,14 @@ def extract_from_precompiled(precompiled_location: str, package_data: List[str],
                     if not any(dst_file.startswith(d) for d in allowed_dirs):
                         continue
 
+                # Check if file matches any pattern using fnmatch (same as wheel extraction)
+                for filename_pattern in package_data:
+                    if fnmatch.fnmatchcase(rel_path,
+                                           f"tensorrt_llm/{filename_pattern}"):
+                        break
+                else:
+                    continue
+
                 dst_dir = os.path.dirname(dst_file)
                 if dst_dir:
                     os.makedirs(dst_dir, exist_ok=True)
diff --git a/tensorrt_llm/_torch/attention_backend/sparse/dsa.py b/tensorrt_llm/_torch/attention_backend/sparse/dsa.py
index aa32d6317e..79ea9a9dec 100644
--- a/tensorrt_llm/_torch/attention_backend/sparse/dsa.py
+++ b/tensorrt_llm/_torch/attention_backend/sparse/dsa.py
@@ -114,7 +114,6 @@ def transform_local_topk_and_prepare_pool_view(
     num_blocks, num_layers, _, _ = all_layer_kv_pool.shape
     tokens_per_block = kv_cache_manager.tokens_per_block
     head_dim = kv_cache_manager.head_dim
-    assert num_layers == kv_cache_manager.num_local_layers, "PP is not enabled yet for DeepSeek V3.2"
     assert all_layer_kv_pool.is_contiguous(
     ), "all_layer_kv_pool should be contiguous"
     all_layer_kv_pool = all_layer_kv_pool.squeeze(2).view(-1, 1, head_dim)
@@ -1647,7 +1646,8 @@ class DSATrtllmAttention(TrtllmAttention):
     ) -> Tuple[Optional[torch.Tensor], Optional[torch.Tensor]]:
         # Transform the local topk indices to global topk indices in paged kv cache
         topk_indices_global, _ = transform_local_topk_and_prepare_pool_view(
-            topk_indices, metadata, self.layer_idx, is_generation)
+            topk_indices, metadata, self.get_local_layer_idx(metadata),
+            is_generation)
 
         # TODO: Use sparse_attn_indexer to predict the indices for DSA attention
         # return self.indexer(q, k, metadata, hidden_states, qr, position_ids)
diff --git a/tensorrt_llm/_torch/auto_deploy/export/library/meta_nonzero.py b/tensorrt_llm/_torch/auto_deploy/export/library/meta_nonzero.py
new file mode 100644
index 0000000000..0a1f79f7a4
--- /dev/null
+++ b/tensorrt_llm/_torch/auto_deploy/export/library/meta_nonzero.py
@@ -0,0 +1,37 @@
+"""Patch to enable torch.nonzero() on meta tensors during export.
+
+This patch addresses an issue where torch.nonzero() raises NotImplementedError
+when tracing models that use nonzero on meta device. The fix sets the config
+flag to assume all elements are non-zero, which enables export to proceed.
+"""
+
+import torch.fx.experimental._config as fx_config
+
+from ..interface import BaseExportPatch, ExportPatchRegistry
+
+
+@ExportPatchRegistry.register("meta_nonzero")
+class MetaNonzeroPatch(BaseExportPatch):
+    """Patch to enable torch.nonzero() meta registration during export.
+
+    This patch sets torch.fx.experimental._config.meta_nonzero_assume_all_nonzero
+    to True, allowing torch.nonzero() to work on meta tensors during tracing.
+    The implementation assumes all elements are non-zero, which is acceptable
+    for tracing purposes where only shapes matter.
+    """
+
+    def _apply_patch(self):
+        """Apply the meta nonzero patch."""
+        # Store original config value
+        self.original_values["meta_nonzero_assume_all_nonzero"] = getattr(
+            fx_config, "meta_nonzero_assume_all_nonzero", False
+        )
+
+        # Enable nonzero on meta tensors
+        fx_config.meta_nonzero_assume_all_nonzero = True
+
+    def _revert_patch(self):
+        """Revert the meta nonzero patch."""
+        fx_config.meta_nonzero_assume_all_nonzero = self.original_values[
+            "meta_nonzero_assume_all_nonzero"
+        ]
diff --git a/tensorrt_llm/_torch/auto_deploy/models/patches/llama4.py b/tensorrt_llm/_torch/auto_deploy/models/patches/llama4.py
index f6cfb5a636..d91d7062d5 100644
--- a/tensorrt_llm/_torch/auto_deploy/models/patches/llama4.py
+++ b/tensorrt_llm/_torch/auto_deploy/models/patches/llama4.py
@@ -72,11 +72,11 @@ def _forward_with_cond(
         inputs_embeds = self.get_input_embeddings()(input_ids)
 
     def _vision_branch(inputs_embeds, pixel_values, input_ids):
+        # Updated to match transformers 4.57.1+ signature
+        # get_image_features now takes: (self, pixel_values, vision_feature_select_strategy, **kwargs)
         image_features = self.get_image_features(
             pixel_values=pixel_values,
-            vision_feature_layer=vision_feature_layer,
             vision_feature_select_strategy=vision_feature_select_strategy,
-            image_sizes=None,
         )
 
         vision_flat = image_features.view(-1, image_features.size(-1))
diff --git a/tensorrt_llm/_torch/auto_deploy/models/patches/mixtral.py b/tensorrt_llm/_torch/auto_deploy/models/patches/mixtral.py
index b759fe6495..c370de2285 100644
--- a/tensorrt_llm/_torch/auto_deploy/models/patches/mixtral.py
+++ b/tensorrt_llm/_torch/auto_deploy/models/patches/mixtral.py
@@ -7,19 +7,38 @@ from transformers.models.mixtral.modeling_mixtral import MixtralSparseMoeBlock
 
 from ...export.interface import BaseExportPatch, ExportPatchRegistry
 
+# Import SiLUActivation for compatibility check
+try:
+    from transformers.activations import SiLUActivation
+
+    _SILU_TYPES = (nn.SiLU, SiLUActivation)
+except ImportError:
+    _SILU_TYPES = (nn.SiLU,)
+
+
+def _is_silu_activation(act_fn) -> bool:
+    """Check if activation function is SiLU or equivalent."""
+    return isinstance(act_fn, _SILU_TYPES)
+
 
 def _forward_moe(self: MixtralSparseMoeBlock, hidden_states: torch.Tensor):
     # check if we can apply the patch
-    use_original_forward = False
-    if not all(isinstance(expert.act_fn, nn.SiLU) for expert in self.experts):
-        use_original_forward = True
+    unsupported_reasons = []
+    if not all(_is_silu_activation(expert.act_fn) for expert in self.experts):
+        unsupported_reasons.append("expert activation is not SiLU")
 
     if any(getattr(mod, "bias", None) is not None for mod in self.experts.modules()):
-        use_original_forward = True
+        unsupported_reasons.append("expert modules have bias")
 
-    # rely on original forward instead
-    if use_original_forward:
-        return self._original_forward(hidden_states)
+    # Raise informative error for unsupported configurations
+    # (fallback to original forward is not export-compatible with transformers >= 4.57.1)
+    if unsupported_reasons:
+        raise NotImplementedError(
+            f"MixtralSparseMoeBlock forward patch does not support this model configuration: "
+            f"{', '.join(unsupported_reasons)}. "
+            f"The original transformers forward uses torch.nonzero() and tensor indexing "
+            f"which are not compatible with torch.export on meta tensors."
+        )
 
     batch_size, sequence_length, hidden_dim = hidden_states.shape
     if self.training and self.jitter_noise > 0:
diff --git a/tensorrt_llm/_torch/auto_deploy/models/patches/qwen3.py b/tensorrt_llm/_torch/auto_deploy/models/patches/qwen3.py
index 3870bc5bfd..e5ed0c6af2 100644
--- a/tensorrt_llm/_torch/auto_deploy/models/patches/qwen3.py
+++ b/tensorrt_llm/_torch/auto_deploy/models/patches/qwen3.py
@@ -7,19 +7,38 @@ from transformers.models.qwen3_moe.modeling_qwen3_moe import Qwen3MoeSparseMoeBl
 
 from ...export.interface import BaseExportPatch, ExportPatchRegistry
 
+# Import SiLUActivation for compatibility check
+try:
+    from transformers.activations import SiLUActivation
+
+    _SILU_TYPES = (nn.SiLU, SiLUActivation)
+except ImportError:
+    _SILU_TYPES = (nn.SiLU,)
+
+
+def _is_silu_activation(act_fn) -> bool:
+    """Check if activation function is SiLU or equivalent."""
+    return isinstance(act_fn, _SILU_TYPES)
+
 
 def _forward_moe(self: Qwen3MoeSparseMoeBlock, hidden_states: torch.Tensor):
     # check if we can apply the patch
-    use_original_forward = False
-    if not all(isinstance(expert.act_fn, nn.SiLU) for expert in self.experts):
-        use_original_forward = True
+    unsupported_reasons = []
+    if not all(_is_silu_activation(expert.act_fn) for expert in self.experts):
+        unsupported_reasons.append("expert activation is not SiLU")
 
     if any(getattr(mod, "bias", None) is not None for mod in self.experts.modules()):
-        use_original_forward = True
+        unsupported_reasons.append("expert modules have bias")
 
-    # rely on original forward instead
-    if use_original_forward:
-        return self._original_forward(hidden_states)
+    # Raise informative error for unsupported configurations
+    # (fallback to original forward is not export-compatible with transformers >= 4.57.1)
+    if unsupported_reasons:
+        raise NotImplementedError(
+            f"Qwen3MoeSparseMoeBlock forward patch does not support this model configuration: "
+            f"{', '.join(unsupported_reasons)}. "
+            f"The original transformers forward uses torch.nonzero() and tensor indexing "
+            f"which are not compatible with torch.export on meta tensors."
+        )
 
     batch_size, sequence_length, hidden_dim = hidden_states.shape
     hidden_states = hidden_states.view(-1, hidden_dim)
diff --git a/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py b/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py
index 6519ce2017..ae61e2b64c 100644
--- a/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py
+++ b/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py
@@ -1864,10 +1864,13 @@ if IS_CUTLASS_DSL_AVAILABLE:
             mma_tiler_mn_candidates = [(self.tile_size, 128),
                                        (self.tile_size, 256)]
             cluster_shape_mn_candidates = [(self.tile_size // 128, 1)]
+            # TODO: Add raster_along_m=True if we find it more performant in some cases.
+            raster_along_m_candidates = [False]
 
             valid_tactics = []
-            for mma_tiler_mn, cluster_shape_mn in itertools.product(
-                    mma_tiler_mn_candidates, cluster_shape_mn_candidates):
+            for mma_tiler_mn, cluster_shape_mn, raster_along_m in itertools.product(
+                    mma_tiler_mn_candidates, cluster_shape_mn_candidates,
+                    raster_along_m_candidates):
                 if self.__class__.kernel_class.can_implement(
                         ab_dtype=cutlass.Float4E2M1FN,
                         sf_dtype=cutlass.Float8E4M3FN,
@@ -1883,7 +1886,8 @@ if IS_CUTLASS_DSL_AVAILABLE:
                         b_major="k",
                         c_major="n",
                 ):
-                    valid_tactics.append((mma_tiler_mn, cluster_shape_mn))
+                    valid_tactics.append(
+                        (mma_tiler_mn, cluster_shape_mn, raster_along_m))
 
             return valid_tactics
 
@@ -2013,15 +2017,16 @@ if IS_CUTLASS_DSL_AVAILABLE:
             stream = cuda.CUstream(torch_stream.cuda_stream)
 
             if isinstance(tactic, tuple):
-                mma_tiler_mn, cluster_shape_mn = tactic
+                mma_tiler_mn, cluster_shape_mn, raster_along_m = tactic
             else:
                 mma_tiler_mn = (self.tile_size, 128)
                 cluster_shape_mn = (self.tile_size // 128, 1)
+                raster_along_m = False
             assert mma_tiler_mn[
                 0] == self.tile_size, f"Tactic ({tactic}) is incompatible with tile size ({self.tile_size})"
 
             cache_key = (self.scaling_vector_size, self.tile_size, self.top_k,
-                         mma_tiler_mn, cluster_shape_mn)
+                         mma_tiler_mn, cluster_shape_mn, raster_along_m)
             if cache_key not in self.__class__.kernel_cache:
                 gemm = self.__class__.kernel_class(
                     sf_vec_size=self.scaling_vector_size,
@@ -2029,6 +2034,7 @@ if IS_CUTLASS_DSL_AVAILABLE:
                     cluster_shape_mn=cluster_shape_mn,
                     vectorized_f32=True,
                     topk=self.top_k,
+                    raster_along_m=raster_along_m,
                 )
                 # Compute max active clusters on current device
                 hardware_info = cutlass.utils.HardwareInfo()
diff --git a/tensorrt_llm/_torch/cute_dsl_kernels/blackwell/blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py b/tensorrt_llm/_torch/cute_dsl_kernels/blackwell/blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py
index 0df0d1832a..5a4c5d0a00 100644
--- a/tensorrt_llm/_torch/cute_dsl_kernels/blackwell/blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py
+++ b/tensorrt_llm/_torch/cute_dsl_kernels/blackwell/blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py
@@ -37,6 +37,7 @@ import cutlass.utils.blackwell_helpers as sm100_utils
 import cutlass.utils.blockscaled_layout as blockscaled_utils
 from cutlass._mlir.dialects import math
 from cutlass.cute.nvgpu import cpasync, tcgen05
+from cutlass.cutlass_dsl import Int32
 
 from .custom_pipeline import PipelineCpAsyncUmma
 from .utils import (
@@ -154,6 +155,144 @@ CUDA Graph Support:
 """
 
 
+# TODO: Remove this hook helper function after nvidia-cutlass-dsl 4.4 is released.
+def hooked_PersistentTileSchedulerParams_init(
+    self,
+    problem_shape_ntile_mnl: cute.Shape,
+    cluster_shape_mnk: cute.Shape,
+    swizzle_size: int = 1,
+    raster_along_m: bool = True,
+    *,
+    loc=None,
+    ip=None,
+):
+    if cluster_shape_mnk[2] != 1:
+        raise ValueError(f"unsupported cluster_shape_k {cluster_shape_mnk[2]}")
+    if swizzle_size < 1:
+        raise ValueError(f"expect swizzle_size >= 1, but get {swizzle_size}")
+
+    self.problem_shape_ntile_mnl = problem_shape_ntile_mnl
+    # cluster_shape_mnk is kept for reconstruction
+    self._cluster_shape_mnk = cluster_shape_mnk
+    self.cluster_shape_mn = cluster_shape_mnk[:2]
+    self.swizzle_size = swizzle_size
+    self._raster_along_m = raster_along_m
+    self._loc = loc
+
+    # Apply swizzle if swizzle_size > 1
+    if swizzle_size > 1:
+        problem_shape_ncluster_mnl = cute.round_up(
+            self.problem_layout_ncluster_mnl.shape,
+            (1, swizzle_size, 1) if raster_along_m else (swizzle_size, 1, 1),
+        )
+
+        if raster_along_m:
+            self.problem_layout_ncluster_mnl = cute.make_layout(
+                (
+                    problem_shape_ncluster_mnl[0],
+                    (swizzle_size, problem_shape_ncluster_mnl[1] // swizzle_size),
+                    problem_shape_ncluster_mnl[2],
+                ),
+                stride=(
+                    swizzle_size,
+                    (1, swizzle_size * problem_shape_ncluster_mnl[0]),
+                    problem_shape_ncluster_mnl[0] * problem_shape_ncluster_mnl[1],
+                ),
+                loc=loc,
+                ip=ip,
+            )
+        else:
+            self.problem_layout_ncluster_mnl = cute.make_layout(
+                (
+                    (swizzle_size, problem_shape_ncluster_mnl[0] // swizzle_size),
+                    problem_shape_ncluster_mnl[1],
+                    problem_shape_ncluster_mnl[2],
+                ),
+                stride=(
+                    (1, swizzle_size * problem_shape_ncluster_mnl[1]),
+                    swizzle_size,
+                    problem_shape_ncluster_mnl[0] * problem_shape_ncluster_mnl[1],
+                ),
+                loc=loc,
+                ip=ip,
+            )
+
+    # Create FastDivmod divisors (only when swizzle_size == 1 for correctness)
+    # FastDivmod assumes simple col-major/row-major layout, incompatible with swizzled layouts
+    if swizzle_size == 1:
+        problem_shape_ncluster_mnl = cute.ceil_div(
+            self.problem_shape_ntile_mnl, cluster_shape_mnk[:2], loc=loc, ip=ip
+        )
+        if raster_along_m:
+            self.problem_layout_ncluster_mnl = cute.make_layout(
+                problem_shape_ncluster_mnl,
+                stride=(
+                    1,
+                    problem_shape_ncluster_mnl[0],
+                    problem_shape_ncluster_mnl[0] * problem_shape_ncluster_mnl[1],
+                ),
+                loc=loc,
+                ip=ip,
+            )
+        else:
+            self.problem_layout_ncluster_mnl = cute.make_layout(
+                problem_shape_ncluster_mnl,
+                stride=(
+                    problem_shape_ncluster_mnl[1],
+                    1,
+                    problem_shape_ncluster_mnl[0] * problem_shape_ncluster_mnl[1],
+                ),
+                loc=loc,
+                ip=ip,
+            )
+        problem_layout_size = cute.size(self.problem_layout_ncluster_mnl, loc=loc, ip=ip)
+        cluster_count_m = self.problem_layout_ncluster_mnl.shape[0]
+        cluster_count_n = self.problem_layout_ncluster_mnl.shape[1]
+
+        # batch_fdd: Used to map linear_idx to work_unit_id (handles persistent scheduling)
+        self.batch_fdd = cute.fast_divmod_create_divisor(problem_layout_size, loc=loc, ip=ip)
+
+        # cluster_shape_m_fdd: Used to decode work_unit_id to cluster coordinates
+        self.cluster_shape_m_fdd = cute.fast_divmod_create_divisor(cluster_count_m, loc=loc, ip=ip)
+
+        # cluster_shape_n_fdd: Used for the second level decomposition
+        self.cluster_shape_n_fdd = cute.fast_divmod_create_divisor(cluster_count_n, loc=loc, ip=ip)
+    else:
+        # FastDivmod not applicable with swizzling, set to None
+        self.batch_fdd = None
+        self.cluster_shape_m_fdd = None
+        self.cluster_shape_n_fdd = None
+
+
+def hooked_get_cluster_work_idx_with_fastdivmod(
+    self, current_work_linear_idx: Int32, *, loc=None, ip=None
+) -> Tuple[Int32, Int32, Int32]:
+    work_iteration, work_unit_id = divmod(current_work_linear_idx, self.params.batch_fdd)
+
+    if self.params._raster_along_m:
+        # raster_along_m=True means column major (m is fastest)
+        # First, get cluster_m using cluster_shape_m_fdd
+        cluster_n_batch, cluster_m = divmod(work_unit_id, self.params.cluster_shape_m_fdd)
+
+        # Then decode cluster_n_batch to get cluster_n and batch_l using FastDivmod
+        batch_l, cluster_n = divmod(cluster_n_batch, self.params.cluster_shape_n_fdd)
+    else:
+        # raster_along_m=False means row major (n is fastest)
+        # First, get cluster_n using cluster_shape_n_fdd
+        cluster_m_batch, cluster_n = divmod(work_unit_id, self.params.cluster_shape_n_fdd)
+
+        # Then decode cluster_m_batch to get cluster_m and batch_l using FastDivmod
+        batch_l, cluster_m = divmod(cluster_m_batch, self.params.cluster_shape_m_fdd)
+
+    return (cluster_m, cluster_n, batch_l)
+
+
+cutlass.utils.PersistentTileSchedulerParams.__init__ = hooked_PersistentTileSchedulerParams_init
+cutlass.utils.StaticPersistentTileScheduler._get_cluster_work_idx_with_fastdivmod = (
+    hooked_get_cluster_work_idx_with_fastdivmod
+)
+
+
 class BlockScaledContiguousGatherGroupedGemmKernel:
     """This class implements contiguous grouped matrix multiplication with gather operation and SwiGLU fusion
     for FC1 layer computation (C = up * silu(gate), where up/gate come from interleaved GEMM result).
@@ -245,6 +384,7 @@ class BlockScaledContiguousGatherGroupedGemmKernel:
         cluster_shape_mn: Tuple[int, int],
         vectorized_f32: bool,
         topk: cutlass.Int64,
+        raster_along_m: bool = False,
     ):
         """Initializes the configuration for a Blackwell blockscaled dense GEMM kernel with
         gather operation and SwiGLU fusion.
@@ -289,6 +429,7 @@ class BlockScaledContiguousGatherGroupedGemmKernel:
         self.cluster_shape_mn = cluster_shape_mn
         # K dimension is deferred in _setup_attributes
         self.mma_tiler = (*mma_tiler_mn, 1)
+        self.raster_along_m = raster_along_m
 
         self.cta_group = tcgen05.CtaGroup.TWO if self.use_2cta_instrs else tcgen05.CtaGroup.ONE
 
@@ -743,7 +884,11 @@ class BlockScaledContiguousGatherGroupedGemmKernel:
 
         # Compute grid size
         self.tile_sched_params, grid = self._compute_grid(
-            c, self.cta_tile_shape_mnk_c, self.cluster_shape_mn, max_active_clusters
+            c,
+            self.cta_tile_shape_mnk_c,
+            self.cluster_shape_mn,
+            max_active_clusters,
+            self.raster_along_m,
         )
 
         self.buffer_align_bytes = 1024
@@ -1254,34 +1399,69 @@ class BlockScaledContiguousGatherGroupedGemmKernel:
                 pipeline.PipelineUserType.Producer, self.num_tile_stage
             )
 
-            while work_tile.is_valid_tile:
-                cur_tile_coord = work_tile.tile_idx
-                mma_tile_coord_m = cur_tile_coord[0] // cute.size(tiled_mma.thr_id.shape)
-                if mma_tile_coord_m < num_non_exiting_tiles[0]:
-                    tile_info_pipeline.producer_acquire(tile_info_producer_state)
+            num_non_exiting_tiles_value = num_non_exiting_tiles[0]
+
+            if cutlass.const_expr(self.raster_along_m):
+                while work_tile.is_valid_tile:
                     cur_tile_coord = work_tile.tile_idx
-                    expert_idx = tile_idx_to_expert_idx[mma_tile_coord_m]
-                    mn_limit = tile_idx_to_mn_limit[mma_tile_coord_m]
-                    with cute.arch.elect_one():
-                        sInfo[(0, tile_info_producer_state.index)] = cur_tile_coord[0]
-                        sInfo[(1, tile_info_producer_state.index)] = cur_tile_coord[1]
-                        sInfo[(2, tile_info_producer_state.index)] = expert_idx
-                        sInfo[(3, tile_info_producer_state.index)] = cutlass.Int32(
-                            work_tile.is_valid_tile
+                    mma_tile_coord_m = cur_tile_coord[0] // cute.size(tiled_mma.thr_id.shape)
+                    if mma_tile_coord_m < num_non_exiting_tiles_value:
+                        tile_info_pipeline.producer_acquire(tile_info_producer_state)
+                        cur_tile_coord = work_tile.tile_idx
+                        expert_idx = tile_idx_to_expert_idx[mma_tile_coord_m]
+                        mn_limit = tile_idx_to_mn_limit[mma_tile_coord_m]
+                        with cute.arch.elect_one():
+                            sInfo[(0, tile_info_producer_state.index)] = cur_tile_coord[0]
+                            sInfo[(1, tile_info_producer_state.index)] = cur_tile_coord[1]
+                            sInfo[(2, tile_info_producer_state.index)] = expert_idx
+                            sInfo[(3, tile_info_producer_state.index)] = cutlass.Int32(
+                                work_tile.is_valid_tile
+                            )
+                            sInfo[(4, tile_info_producer_state.index)] = mn_limit
+                            # fence view async shared
+                        cute.arch.fence_proxy(
+                            cute.arch.ProxyKind.async_shared,
+                            space=cute.arch.SharedSpace.shared_cta,
                         )
-                        sInfo[(4, tile_info_producer_state.index)] = mn_limit
-                        # fence view async shared
-                    cute.arch.fence_proxy(
-                        cute.arch.ProxyKind.async_shared,
-                        space=cute.arch.SharedSpace.shared_cta,
-                    )
 
-                    self.sched_sync_barrier.arrive_and_wait()
-                    tile_info_pipeline.producer_commit(tile_info_producer_state)
-                    tile_info_producer_state.advance()
+                        self.sched_sync_barrier.arrive_and_wait()
+                        tile_info_pipeline.producer_commit(tile_info_producer_state)
+                        tile_info_producer_state.advance()
 
-                tile_sched.advance_to_next_work()
-                work_tile = tile_sched.get_current_work()
+                    tile_sched.advance_to_next_work()
+                    work_tile = tile_sched.get_current_work()
+            else:
+                is_continue = cutlass.Boolean(1)
+                while work_tile.is_valid_tile and is_continue:
+                    cur_tile_coord = work_tile.tile_idx
+                    mma_tile_coord_m = cur_tile_coord[0] // cute.size(tiled_mma.thr_id.shape)
+                    if mma_tile_coord_m < num_non_exiting_tiles_value:
+                        tile_info_pipeline.producer_acquire(tile_info_producer_state)
+                        cur_tile_coord = work_tile.tile_idx
+                        expert_idx = tile_idx_to_expert_idx[mma_tile_coord_m]
+                        mn_limit = tile_idx_to_mn_limit[mma_tile_coord_m]
+                        with cute.arch.elect_one():
+                            sInfo[(0, tile_info_producer_state.index)] = cur_tile_coord[0]
+                            sInfo[(1, tile_info_producer_state.index)] = cur_tile_coord[1]
+                            sInfo[(2, tile_info_producer_state.index)] = expert_idx
+                            sInfo[(3, tile_info_producer_state.index)] = cutlass.Int32(
+                                work_tile.is_valid_tile
+                            )
+                            sInfo[(4, tile_info_producer_state.index)] = mn_limit
+                            # fence view async shared
+                        cute.arch.fence_proxy(
+                            cute.arch.ProxyKind.async_shared,
+                            space=cute.arch.SharedSpace.shared_cta,
+                        )
+
+                        self.sched_sync_barrier.arrive_and_wait()
+                        tile_info_pipeline.producer_commit(tile_info_producer_state)
+                        tile_info_producer_state.advance()
+                    else:
+                        is_continue = cutlass.Boolean(0)
+
+                    tile_sched.advance_to_next_work()
+                    work_tile = tile_sched.get_current_work()
 
             tile_info_pipeline.producer_acquire(tile_info_producer_state)
             with cute.arch.elect_one():
@@ -2781,6 +2961,7 @@ class BlockScaledContiguousGatherGroupedGemmKernel:
         cta_tile_shape_mnk: Tuple[int, int, int],
         cluster_shape_mn: Tuple[int, int],
         max_active_clusters: cutlass.Constexpr,
+        raster_along_m: bool = False,
     ) -> Tuple[utils.PersistentTileSchedulerParams, Tuple[int, int, int]]:
         """Use persistent tile scheduler to compute the grid size for the output tensor C.
 
@@ -2803,7 +2984,9 @@ class BlockScaledContiguousGatherGroupedGemmKernel:
         num_ctas_mnl = gc[(0, (None, None, None))].shape
         cluster_shape_mnl = (*cluster_shape_mn, 1)
 
-        tile_sched_params = utils.PersistentTileSchedulerParams(num_ctas_mnl, cluster_shape_mnl)
+        tile_sched_params = utils.PersistentTileSchedulerParams(
+            num_ctas_mnl, cluster_shape_mnl, raster_along_m=raster_along_m
+        )
         grid = utils.StaticPersistentTileScheduler.get_grid_shape(
             tile_sched_params, max_active_clusters
         )
@@ -3209,3 +3392,33 @@ class BlockScaledContiguousGatherGroupedGemmKernel:
             stream=stream,
             epilogue_op=epilogue_op,
         )
+
+
+@cute.jit
+def cvt_sf_MKL_to_M32x4xrm_K4xrk_L(
+    sf_ref_tensor: cute.Tensor,
+    sf_mma_tensor: cute.Tensor,
+):
+    """Convert scale factor tensor from MKL layout to mma specification M(32x4xrest_m)xK(4xrest_k)xL layout"""
+    # sf_mma_tensor has flatten shape (32, 4, rest_m, 4, rest_k, l)
+    # group to ((32, 4, rest_m), (4, rest_k), l)
+    sf_mma_tensor = cute.group_modes(sf_mma_tensor, 0, 3)
+    sf_mma_tensor = cute.group_modes(sf_mma_tensor, 1, 3)
+    for i in cutlass.range(cute.size(sf_ref_tensor)):
+        mkl_coord = sf_ref_tensor.layout.get_hier_coord(i)
+        sf_mma_tensor[mkl_coord] = sf_ref_tensor[mkl_coord]
+
+
+@cute.jit
+def cvt_sf_M32x4xrm_K4xrk_L_to_MKL(
+    sf_swizzled_tensor: cute.Tensor,
+    sf_unswizzled_tensor: cute.Tensor,
+):
+    """Convert scale factor tensor from mma specification M(32x4xrest_m)xK(4xrest_k)xL layout to MKL layout"""
+    # sf_swizzled_tensor has flatten shape (32, 4, rest_m, 4, rest_k, l)
+    # group to ((32, 4, rest_m), (4, rest_k), l)
+    sf_swizzled_tensor = cute.group_modes(sf_swizzled_tensor, 0, 3)
+    sf_swizzled_tensor = cute.group_modes(sf_swizzled_tensor, 1, 3)
+    for i in cutlass.range(cute.size(sf_unswizzled_tensor)):
+        mkl_coord = sf_unswizzled_tensor.layout.get_hier_coord(i)
+        sf_unswizzled_tensor[mkl_coord] = sf_swizzled_tensor[mkl_coord]
diff --git a/tests/integration/defs/accuracy/references/gsm8k.yaml b/tests/integration/defs/accuracy/references/gsm8k.yaml
index d281411d12..76cf65bcb3 100644
--- a/tests/integration/defs/accuracy/references/gsm8k.yaml
+++ b/tests/integration/defs/accuracy/references/gsm8k.yaml
@@ -106,6 +106,9 @@ deepseek-ai/DeepSeek-V3.2-Exp:
   - quant_algo: NVFP4
     spec_dec_algo: MTP
     accuracy: 95.6
+Qwen3/Qwen3-4B:
+  - spec_dec_algo: Eagle
+    accuracy: 85.823
 Qwen3/Qwen3-8B:
   - accuracy: 87.1114
   - spec_dec_algo: Eagle
diff --git a/tests/integration/defs/accuracy/test_llm_api_pytorch.py b/tests/integration/defs/accuracy/test_llm_api_pytorch.py
index ee416eb247..1a32e333b5 100644
--- a/tests/integration/defs/accuracy/test_llm_api_pytorch.py
+++ b/tests/integration/defs/accuracy/test_llm_api_pytorch.py
@@ -2727,10 +2727,11 @@ class TestDeepSeekV32(LlmapiAccuracyTestHarness):
             (8, 1, 8, 0, True, True, True, True, 24, "CUTLASS", False),
             (8, 1, 8, 3, False, False, True, True, 1, "TRTLLM", False),
             (8, 1, 8, 1, False, True, True, True, 24, "CUTLASS", True),
+            (1, 4, 1, 1, False, False, True, True, 24, "TRTLLM", False),
         ],
         ids=[
             "baseline", "baseline_mtp1", "baseline_fp8kv", "latency",
-            "disable_skip_indexer"
+            "disable_skip_indexer", "baseline_pp4_mtp1"
         ])
     def test_nvfp4_multi_gpus(self, tp_size, pp_size, ep_size, mtp_nextn, fp8kv,
                               attention_dp, cuda_graph, overlap_scheduler,
@@ -3327,6 +3328,35 @@ class TestQwen2_7BInstruct(LlmapiAccuracyTestHarness):
                           extra_evaluator_kwargs=self.EXTRA_EVALUATOR_KWARGS)
 
 
+class TestQwen3_4B(LlmapiAccuracyTestHarness):
+    MODEL_NAME = "Qwen3/Qwen3-4B"
+
+    def test_eagle3(self):
+        "RCCA: https://nvbugspro.nvidia.com/bug/5698434"
+        pytorch_config = dict(
+            disable_overlap_scheduler=True,
+            cuda_graph_config=CudaGraphConfig(),
+        )
+        kv_cache_config = KvCacheConfig(
+            enable_block_reuse=False,
+            free_gpu_memory_fraction=0.6,
+        )
+
+        eagle_model_dir = f"{llm_models_root()}/Qwen3/Qwen3-4B_eagle3/"
+        target_model_dir = f"{llm_models_root()}/Qwen3/Qwen3-4B"
+
+        draft_len = 3
+        spec_config = EagleDecodingConfig(max_draft_len=draft_len,
+                                          speculative_model_dir=eagle_model_dir)
+
+        with LLM(model=target_model_dir,
+                 **pytorch_config,
+                 kv_cache_config=kv_cache_config,
+                 speculative_config=spec_config) as llm:
+            task = GSM8K(self.MODEL_NAME)
+            task.evaluate(llm)
+
+
 class TestQwen3_8B(LlmapiAccuracyTestHarness):
     MODEL_NAME = "Qwen3/Qwen3-8B"
 
diff --git a/tests/integration/test_lists/qa/llm_function_core.txt b/tests/integration/test_lists/qa/llm_function_core.txt
index 541783d36b..d7aedd6be4 100644
--- a/tests/integration/test_lists/qa/llm_function_core.txt
+++ b/tests/integration/test_lists/qa/llm_function_core.txt
@@ -519,12 +519,14 @@ accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[baselin
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[baseline_fp8kv]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[latency]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[disable_skip_indexer]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[baseline_pp4_mtp1]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus_chunked_prefill[baseline_fp8kv]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus_chunked_prefill[latency]
 accuracy/test_llm_api_pytorch.py::TestGLM4_6::test_nvfp4_multi_gpus[throughput]
 accuracy/test_llm_api_pytorch.py::TestGLM4_6::test_nvfp4_multi_gpus[throughput_trtllm]
 accuracy/test_llm_api_pytorch.py::TestGLM4_6::test_nvfp4_2_model_mtp[2model]
 accuracy/test_llm_api_pytorch.py::TestGLM4_6::test_nvfp4_2_model_mtp[2model_trtllm]
+accuracy/test_llm_api_pytorch.py::TestQwen3_4B::test_eagle3
 accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_fp8_block_scales[latency]
 accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_bf16[multi_gpus_no_cache]
 accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_fp8_block_scales[latency-torch_compile=False]
diff --git a/tests/integration/test_lists/qa/llm_function_core_sanity.txt b/tests/integration/test_lists/qa/llm_function_core_sanity.txt
index 3087be3506..58a4436a70 100644
--- a/tests/integration/test_lists/qa/llm_function_core_sanity.txt
+++ b/tests/integration/test_lists/qa/llm_function_core_sanity.txt
@@ -58,6 +58,7 @@ accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[baselin
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[baseline_fp8kv]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[latency]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[disable_skip_indexer]
+accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[baseline_pp4_mtp1]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus_chunked_prefill[baseline_fp8kv]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus_chunked_prefill[latency]
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16_4gpus_online_eplb[mtp_nextn=0-moe_backend=WIDEEP]
@@ -229,6 +230,7 @@ accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_w4a8_mxfp4[mxfp8-laten
 accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_fp8_block_scales[latency]
 accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_w4a8_mxfp4[fp8-latency]
 accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_w4a8_mxfp4[mxfp8-latency]
+accuracy/test_llm_api_pytorch.py::TestQwen3_4B::test_eagle3
 accuracy/test_llm_api_pytorch.py::TestSeedOss_36B::test_auto_dtype
 
 accuracy/test_llm_api_pytorch_multimodal.py::TestQwen2_VL_7B::test_auto_dtype
diff --git a/tests/integration/test_lists/test-db/l0_dgx_b200.yml b/tests/integration/test_lists/test-db/l0_dgx_b200.yml
index cc32c9f9c3..eb7ab1bfc6 100644
--- a/tests/integration/test_lists/test-db/l0_dgx_b200.yml
+++ b/tests/integration/test_lists/test-db/l0_dgx_b200.yml
@@ -111,6 +111,7 @@ l0_dgx_b200:
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[baseline_fp8kv] TIMEOUT (60)
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[latency] TIMEOUT (60)
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[disable_skip_indexer] TIMEOUT (60)
+  - accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus[baseline_pp4_mtp1] TIMEOUT (60)
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV32::test_nvfp4_multi_gpus_chunked_prefill[baseline_fp8kv] TIMEOUT (60)
   - accuracy/test_llm_api_pytorch.py::TestMistralLarge3_675B::test_fp8[latency_moe_deepgemm] TIMEOUT (60)
 - condition:
diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt
index a76d26e688..4461ff1e1b 100644
--- a/tests/integration/test_lists/waives.txt
+++ b/tests/integration/test_lists/waives.txt
@@ -377,7 +377,6 @@ accuracy/test_llm_api_pytorch.py::TestNemotronUltra::test_fp8_prequantized[tp8ep
 accuracy/test_llm_api_pytorch.py::TestNemotronUltra::test_fp8_prequantized[tp8-cuda_graph=True] SKIP (https://nvbugs/5707145)
 accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_w4_chunked_prefill[cutlass-auto] SKIP (https://nvbugs/5596343)
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4_4gpus[moe_backend=TRTLLM-mtp_nextn=0-ep4-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5721661)
-unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_flashinfer_attention_op.py::test_flashinfer_attention_op_context_input_pos[cuda-dtype0-4-8-seq6] SKIP (https://nvbugs/5721907)
 accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[moe_backend=CUTLASS-mtp_nextn=0-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True-torch_compile=False] SKIP (https://nvbugs/5722629)
 accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_eagle3_2gpus[cutlass-two_model-overlap_scheduler] SKIP (https://nvbugs/5702826)
 accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_eagle3_4gpus[cutlass-two_model-overlap_scheduler] SKIP (https://nvbugs/5702826)
@@ -514,3 +513,5 @@ accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_eagle3_vswa_reuse_4gpus[one_m
 accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_eagle3_vswa_reuse_4gpus[two_model] SKIP (https://nvbugs/5756028)
 accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_fp8[latency-torch_compile=False] SKIP (https://nvbugs/5785206)
 examples/test_gpt.py::test_llm_gpt2_parallel_embedding_2gpu[float16-0] SKIP (https://nvbugs/5784518)
+accuracy/test_llm_api_pytorch.py::TestLlama3_2_1B::test_fp8_prequantized SKIP (https://nvbugs/5785465)
+accuracy/test_llm_api_pytorch.py::TestMinistral8BInstruct::test_fp8 SKIP (https://nvbugs/5785485)
diff --git a/tests/scripts/cute_dsl_kernels/run_blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py b/tests/scripts/cute_dsl_kernels/run_blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py
new file mode 100644
index 0000000000..3fb0015c98
--- /dev/null
+++ b/tests/scripts/cute_dsl_kernels/run_blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py
@@ -0,0 +1,1305 @@
+# Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: BSD-3-Clause
+
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+
+# 1. Redistributions of source code must retain the above copyright notice, this
+# list of conditions and the following disclaimer.
+
+# 2. Redistributions in binary form must reproduce the above copyright notice,
+# this list of conditions and the following disclaimer in the documentation
+# and/or other materials provided with the distribution.
+
+# 3. Neither the name of the copyright holder nor the names of its
+# contributors may be used to endorse or promote products derived from
+# this software without specific prior written permission.
+
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+"""Example usage of the kernel.
+
+Functional testing:
+python run_blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py \
+        --ab_dtype Float4E2M1FN --c_dtype Float4E2M1FN \
+        --sf_dtype Float8E4M3FN --sf_vec_size 16 \
+        --mma_tiler_mn 128,128 --cluster_shape_mn 1,1 \
+        --nkl 4096,7168,8 --fixed_m 128
+or use a benchmark file:
+python run_blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py \
+        --ab_dtype Float4E2M1FN --c_dtype Float4E2M1FN \
+        --sf_dtype Float8E4M3FN --sf_vec_size 16 \
+        --mma_tiler_mn 128,128 --cluster_shape_mn 1,1 \
+        --benchmark benchmark.txt
+Perf testing:
+python run_blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion.py \
+        --ab_dtype Float4E2M1FN --c_dtype Float4E2M1FN \
+        --sf_dtype Float8E4M3FN --sf_vec_size 16 \
+        --mma_tiler_mn 128,128 --cluster_shape_mn 1,1 \
+        --benchmark benchmark.txt \
+        --skip_ref_check --use_cold_l2 --use_cupti --warmup_iterations 10 --iterations 50
+A sample benchmark.txt file is shown below:
+0 89x4096x7168
+1 200x4096x7168
+2 145x4096x7168
+3 178x4096x7168
+4 241x4096x7168
+5 78x4096x7168
+6 198x4096x7168
+7 60x4096x7168
+"""
+
+import argparse
+import sys
+from pathlib import Path
+from typing import Tuple, Type
+
+import cuda.bindings.driver as cuda
+import cutlass
+import cutlass.cute as cute
+import cutlass.torch as cutlass_torch
+import torch
+from cutlass.cute.runtime import from_dlpack
+
+try:
+    from tensorrt_llm._torch.cute_dsl_kernels.blackwell import (
+        blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion as kernel_module,
+    )
+except (ModuleNotFoundError, ImportError):
+    sys.path.insert(0, str(Path(__file__).parents[3] / "tensorrt_llm/_torch/cute_dsl_kernels"))
+    from blackwell import blockscaled_contiguous_gather_grouped_gemm_swiglu_fusion as kernel_module
+
+BlockScaledContiguousGatherGroupedGemmKernel = (
+    kernel_module.BlockScaledContiguousGatherGroupedGemmKernel
+)
+
+try:
+    from .testing import benchmark
+except ImportError:
+    from testing import benchmark
+
+
+cvt_sf_MKL_to_M32x4xrm_K4xrk_L = kernel_module.cvt_sf_MKL_to_M32x4xrm_K4xrk_L
+cvt_sf_M32x4xrm_K4xrk_L_to_MKL = kernel_module.cvt_sf_M32x4xrm_K4xrk_L_to_MKL
+
+
+def create_mask(group_m_list, mma_tiler_m, permuted_m=None):
+    """Create mask and group mapping for contiguous grouped GEMM.
+
+    :param group_m_list: List of M values for each group (will be aligned to mma_tiler_m)
+    :param mma_tiler_m: MMA tile size in M dimension (from mma_tiler_mn[0]), also used for alignment
+    :param permuted_m: Optional padded M dimension for cuda_graph support. If provided,
+                     tile_idx_to_expert_idx will be padded to this size.
+                     When tile_idx >= num_non_exiting_tiles, the kernel exits.
+
+    Note: For cuda_graph support, set permuted_m to the pre-calculated padded size:
+          permuted_m = m * topK + num_local_experts * (256 - 1)
+          Example: 4096*8 + (256/32)*255 = 34808
+          Only the actual valid rows (aligned_groupm[0]+aligned_groupm[1]+...) contain
+          valid data. The kernel will exit when tile_idx >= num_non_exiting_tiles.
+
+    :return: Tuple of (valid_m, aligned_group_m_list, tile_idx_to_expert_idx, num_non_exiting_tiles)
+             - tile_idx_to_expert_idx: shape (permuted_m/mma_tiler_m,) if permuted_m provided,
+               else (valid_m/mma_tiler_m,)
+             - num_non_exiting_tiles: scalar value = valid_m/mma_tiler_m
+    """
+    valid_m = 0
+    aligned_group_m_list = []
+    tile_idx_to_expert_idx = []
+    tile_idx_to_mn_limit = []
+
+    for i, group_m in enumerate(group_m_list):
+        aligned_group_m = ((group_m + mma_tiler_m - 1) // mma_tiler_m) * mma_tiler_m
+        aligned_group_m_list.append(aligned_group_m)
+
+        # Calculate number of tiles for this group based on MMA tile M size
+        # Each tile covers mma_tiler_m rows in M dimension
+        num_tiles_in_group = aligned_group_m // mma_tiler_m
+        # Add expert_idx for each tile in this group
+        tile_idx_to_expert_idx.extend([i] * num_tiles_in_group)
+        for tile_idx_in_group in range(num_tiles_in_group):
+            tile_idx_to_mn_limit.append(
+                valid_m + min(tile_idx_in_group * mma_tiler_m + mma_tiler_m, group_m)
+            )
+        valid_m += aligned_group_m
+
+    # Compute num_non_exiting_tiles (number of valid tiles in M dimension)
+    num_non_exiting_tiles = len(tile_idx_to_expert_idx)
+
+    # Apply padding if requested (for cuda_graph support)
+    if permuted_m is not None:
+        if permuted_m < valid_m:
+            raise ValueError(
+                f"permuted_m ({permuted_m}) must be >= valid_m ({valid_m}). "
+                f"Cannot pad to a smaller size."
+            )
+        if permuted_m > valid_m:
+            # Calculate how many padding tiles are needed based on MMA tile M size
+            num_padding_tiles = (permuted_m - valid_m) // mma_tiler_m
+            # Pad with 0 (these tiles won't be accessed due to num_non_exiting_tiles check)
+            tile_idx_to_expert_idx.extend([int(-2e9)] * num_padding_tiles)
+            tile_idx_to_mn_limit.extend([int(-2e9)] * num_padding_tiles)
+
+    # Final shape of tile_idx_to_expert_idx: (permuted_m/mma_tiler_m,) if permuted_m provided,
+    # else (valid_m/mma_tiler_m,)
+    tile_idx_to_expert_idx = torch.tensor(tile_idx_to_expert_idx, device="cuda", dtype=torch.int32)
+    num_non_exiting_tiles_tensor = torch.tensor(
+        [num_non_exiting_tiles], device="cuda", dtype=torch.int32
+    )
+    tile_idx_to_mn_limit_tensor = torch.tensor(
+        tile_idx_to_mn_limit, device="cuda", dtype=torch.int32
+    )
+
+    return (
+        valid_m,
+        aligned_group_m_list,
+        tile_idx_to_expert_idx,
+        num_non_exiting_tiles_tensor,
+        tile_idx_to_mn_limit_tensor,
+    )
+
+
+def create_scale_factor_tensor(num_groups, mn, k, sf_vec_size, dtype):
+    def ceil_div(a, b):
+        return (a + b - 1) // b
+
+    sf_k = ceil_div(k, sf_vec_size)
+    ref_shape = (num_groups, mn, sf_k)
+
+    atom_m = (32, 4)
+    atom_k = 4
+    mma_shape = (
+        num_groups,
+        ceil_div(mn, atom_m[0] * atom_m[1]),
+        ceil_div(sf_k, atom_k),
+        atom_m[0],
+        atom_m[1],
+        atom_k,
+    )
+
+    ref_permute_order = (1, 2, 0)
+    mma_permute_order = (3, 4, 1, 5, 2, 0)
+
+    # Create f32 ref torch tensor (cpu)
+    ref_f32_torch_tensor_cpu = cutlass_torch.create_and_permute_torch_tensor(
+        ref_shape,
+        torch.float32,
+        permute_order=ref_permute_order,
+        init_type=cutlass_torch.TensorInitType.RANDOM,
+        init_config=cutlass_torch.RandomInitConfig(
+            min_val=1,
+            max_val=3,
+        ),
+    )
+
+    # Create f32 cute torch tensor (cpu)
+    cute_f32_torch_tensor_cpu = cutlass_torch.create_and_permute_torch_tensor(
+        mma_shape,
+        torch.float32,
+        permute_order=mma_permute_order,
+        init_type=cutlass_torch.TensorInitType.RANDOM,
+        init_config=cutlass_torch.RandomInitConfig(
+            min_val=0,
+            max_val=1,
+        ),
+    )
+    # convert ref f32 tensor to cute f32 tensor
+    cvt_sf_MKL_to_M32x4xrm_K4xrk_L(
+        from_dlpack(ref_f32_torch_tensor_cpu),
+        from_dlpack(cute_f32_torch_tensor_cpu),
+    )
+
+    cute_f32_torch_tensor = cute_f32_torch_tensor_cpu.cuda()
+
+    # reshape makes memory contiguous
+    ref_f32_torch_tensor_cpu = (
+        ref_f32_torch_tensor_cpu.permute(2, 0, 1)
+        .unsqueeze(-1)
+        .expand(num_groups, mn, sf_k, sf_vec_size)
+        .reshape(num_groups, mn, sf_k * sf_vec_size)
+        .permute(*ref_permute_order)
+    )
+    # prune to mkl for reference check.
+    ref_f32_torch_tensor_cpu = ref_f32_torch_tensor_cpu[:, :k, :]
+
+    # Create dtype cute torch tensor (cpu)
+    cute_tensor, cute_torch_tensor = cutlass_torch.cute_tensor_like(
+        cute_f32_torch_tensor_cpu,
+        dtype,
+        is_dynamic_layout=True,
+        assumed_align=16,
+    )
+
+    # Convert f32 cute tensor to dtype cute tensor
+    cute_tensor = cutlass_torch.convert_cute_tensor(
+        cute_f32_torch_tensor,
+        cute_tensor,
+        dtype,
+        is_dynamic_layout=True,
+    )
+    return ref_f32_torch_tensor_cpu, cute_tensor, cute_torch_tensor
+
+
+def create_scale_factor_tensor_unswizzled(num_groups, mn, k, sf_vec_size, dtype):
+    def ceil_div(a, b):
+        return (a + b - 1) // b
+
+    sf_k = ceil_div(k, sf_vec_size)
+    sf_ref = cutlass_torch.matrix(
+        num_groups,
+        mn,
+        sf_k,
+        False,
+        cutlass.Float32,
+        init_type=cutlass_torch.TensorInitType.RANDOM,
+        init_config=cutlass_torch.RandomInitConfig(
+            min_val=1,
+            max_val=3,
+        ),
+    )
+
+    sf_tensor, sf_torch = cutlass_torch.cute_tensor_like(
+        sf_ref, dtype, is_dynamic_layout=True, assumed_align=16
+    )
+
+    # reshape makes memory contiguous
+    sf_ref = (
+        sf_ref.permute(2, 0, 1)
+        .unsqueeze(-1)
+        .expand(num_groups, mn, sf_k, sf_vec_size)
+        .reshape(num_groups, mn, sf_k * sf_vec_size)
+        .permute(1, 2, 0)
+    )
+
+    # print(sf_ref[0])
+    sf_ref = sf_ref[:, :k, :]
+    return sf_ref, sf_tensor, sf_torch
+
+
+def create_sf_layout_tensor(num_groups, mn, nk, sf_vec_size):
+    def ceil_div(a, b):
+        return (a + b - 1) // b
+
+    sf_k = ceil_div(nk, sf_vec_size)
+
+    atom_m = (32, 4)
+    atom_k = 4
+    mma_shape = (
+        num_groups,
+        ceil_div(mn, atom_m[0] * atom_m[1]),
+        ceil_div(sf_k, atom_k),
+        atom_m[0],
+        atom_m[1],
+        atom_k,
+    )
+
+    mma_permute_order = (3, 4, 1, 5, 2, 0)
+
+    # Create f32 cute torch tensor (cpu)
+    cute_f32_torch_tensor = cutlass_torch.create_and_permute_torch_tensor(
+        mma_shape,
+        torch.float32,
+        permute_order=mma_permute_order,
+        init_type=cutlass_torch.TensorInitType.RANDOM,
+        init_config=cutlass_torch.RandomInitConfig(
+            min_val=0,
+            max_val=1,
+        ),
+    )
+    return cute_f32_torch_tensor, sf_k
+
+
+# Create token_id_mapping tensor for gather operation
+# This tensor maps each output row position to the corresponding input row position in A matrix
+# Shape: (valid_m,) or (permuted_m,) if padding is requested
+# Each element contains the token ID (input row index) for that output position
+# Invalid positions (padding) are marked with -1
+def create_token_id_mapping_tensor(group_m_list, mma_tiler_m, max_token_id, permuted_m=None):
+    """Create token_id_mapping tensor for gather operation with random distribution.
+
+    :param group_m_list: List of M values for each group (will be aligned to mma_tiler_m)
+    :param mma_tiler_m: MMA tile size in M dimension (from mma_tiler_mn[0]), also used for alignment
+    :param max_token_id: Maximum token ID (typically the number of input tokens)
+    :param permuted_m: Optional padded M dimension for cuda_graph support
+
+    Note: In real MoE scenarios, tokens are randomly routed to different experts,
+          so we use random sampling (with replacement) to simulate this distribution.
+    """
+    valid_m = 0
+    for group_m in group_m_list:
+        valid_m += ((group_m + mma_tiler_m - 1) // mma_tiler_m) * mma_tiler_m
+
+    tensor_m = permuted_m if permuted_m is not None else valid_m
+
+    # Initialize all values to -1 (invalid token)
+    base_data = torch.full((tensor_m,), -1, dtype=torch.int32)
+
+    accumulated_m = 0
+    for group_m in group_m_list:
+        start_idx = accumulated_m
+        rounded_group_m = ((group_m + mma_tiler_m - 1) // mma_tiler_m) * mma_tiler_m
+        # Generate random token IDs instead of contiguous ones
+        # Random sampling with replacement to simulate real MoE routing
+        random_token_ids = torch.randint(0, max_token_id, (group_m,), dtype=torch.int32)
+        # perfect_token_ids = torch.arange(0, group_m, dtype=torch.int32)
+        base_data[start_idx : start_idx + group_m] = random_token_ids
+        accumulated_m += rounded_group_m
+
+    token_id_mapping_ref = base_data.clone()
+    token_id_mapping_tensor, token_id_mapping_torch = cutlass_torch.cute_tensor_like(
+        token_id_mapping_ref, cutlass.Int32, is_dynamic_layout=True, assumed_align=4
+    )
+    return token_id_mapping_ref, token_id_mapping_tensor, token_id_mapping_torch
+
+
+def create_tensors(
+    num_groups,
+    group_m_list,
+    n,
+    k,
+    a_major,
+    b_major,
+    cd_major,
+    ab_dtype,
+    c_dtype,
+    sf_dtype,
+    sf_vec_size,
+    mma_tiler_m,
+    permuted_m=None,
+):
+    """Create tensors for contiguous grouped GEMM with gather operation and SwiGLU fusion.
+
+    Note: Output C has N/2 columns since SwiGLU combines pairs of (up, gate) from interleaved B weights.
+    B weights are expected to be interleaved: [up_0:64, gate_64:128, up_128:192, gate_192:256, ...]
+
+    Returns tensors including:
+    - A: Input matrix (MxKx1)
+    - B: Weight matrix with interleaved up/gate weights (NxKxL)
+    - C: Output matrix (Mx(N/2)x1), N is halved due to SwiGLU fusion
+    - SFA, SFB: Scale factor matrices for A and B
+    - SFC: Scale factor matrix for C (only when c_dtype is Float4E2M1FN)
+    - tile_idx_to_expert_idx: Maps tile index to expert/group ID
+    - token_id_mapping: Maps output row position to input row position (for gather)
+    - num_non_exiting_tiles: Number of valid tiles to process
+
+    :param mma_tiler_m: MMA tile size in M dimension (from mma_tiler_mn[0]), also used for alignment
+    :param permuted_m: Optional padded M dimension for cuda_graph support. If provided,
+                     A matrix, C matrix, token_id_mapping, and scale factor A will be padded to this size.
+                     The kernel exits when tile_idx >= num_non_exiting_tiles.
+
+    Example with CUDA graph padding:
+        # For MoE: m=4096, topK=8, num_local_experts=256, experts_per_rank=8
+        permuted_m = 4096 * 8 + 8 * 255  # = 34808
+        tensors = create_tensors(
+            num_groups=8,  # num_local_experts
+            group_m_list=[512, 1024, ...],  # actual group sizes
+            n=4096, k=7168,
+            a_major="k", b_major="k", cd_major="n",
+            ab_dtype=cutlass.Float4E2M1FN,
+            c_dtype=cutlass.BFloat16,
+            sf_dtype=cutlass.Float8E4M3FN,
+            sf_vec_size=16,
+            mma_tiler_m=128,  # MMA tile size in M dimension, also used for alignment
+            permuted_m=34808  # Enable padding for cuda_graph
+        )
+        # Returns tensors with A, C, SFA, and token_id_mapping padded to permuted_m size,
+        # kernel exits early when tile_idx >= num_non_exiting_tiles
+    """
+    torch.manual_seed(1111)
+
+    alpha_torch_cpu = torch.randn((num_groups,), dtype=torch.float32)
+
+    (
+        valid_m,
+        aligned_group_m_list,
+        _tile_idx_to_expert_idx,
+        _num_non_exiting_tiles,
+        _tile_idx_to_mn_limit,
+    ) = create_mask(group_m_list, mma_tiler_m, permuted_m)
+
+    max_m = max(group_m_list)
+
+    # Use permuted_m for A/C tensors if provided (for cuda_graph support)
+    tensor_m = permuted_m if permuted_m is not None else valid_m
+
+    a_torch_cpu = cutlass_torch.matrix(1, max_m, k, a_major == "m", cutlass.Float32)
+    b_torch_cpu = cutlass_torch.matrix(num_groups, n, k, b_major == "n", cutlass.Float32)
+    # C tensor also uses tensor_m (permuted_m) for cuda_graph support
+    c_torch_cpu = cutlass_torch.matrix(1, tensor_m, n // 2, cd_major == "m", cutlass.Float32)
+
+    a_tensor, a_torch_gpu = cutlass_torch.cute_tensor_like(
+        a_torch_cpu, ab_dtype, is_dynamic_layout=True, assumed_align=16
+    )
+    b_tensor, b_torch_gpu = cutlass_torch.cute_tensor_like(
+        b_torch_cpu, ab_dtype, is_dynamic_layout=True, assumed_align=16
+    )
+    c_tensor, c_torch_gpu = cutlass_torch.cute_tensor_like(
+        c_torch_cpu, c_dtype, is_dynamic_layout=True, assumed_align=16
+    )
+
+    # Mark tensor with element divisibility for 16B alignment
+    a_tensor.mark_compact_shape_dynamic(
+        mode=1 if a_major == "k" else 0,
+        stride_order=(2, 0, 1) if a_major == "k" else (2, 1, 0),
+        divisibility=32 if ab_dtype == cutlass.Float4E2M1FN else 16,
+    )
+    b_tensor.mark_compact_shape_dynamic(
+        mode=1 if b_major == "k" else 0,
+        stride_order=(2, 0, 1) if b_major == "k" else (2, 1, 0),
+        divisibility=32 if ab_dtype == cutlass.Float4E2M1FN else 16,
+    )
+    c_tensor.mark_compact_shape_dynamic(
+        mode=1 if cd_major == "n" else 0,
+        stride_order=(2, 0, 1) if cd_major == "n" else (2, 1, 0),
+        divisibility=32 if ab_dtype == cutlass.Float4E2M1FN else 16,
+    )
+
+    # Use tensor_m (permuted_m if provided) for scale factor A
+    sfa_torch_cpu, sfa_tensor, sfa_torch_gpu = create_scale_factor_tensor_unswizzled(
+        1, max_m, k, sf_vec_size, sf_dtype
+    )
+
+    sfb_torch_cpu, sfb_tensor, sfb_torch_gpu = create_scale_factor_tensor(
+        num_groups, n, k, sf_vec_size, sf_dtype
+    )
+
+    token_id_mapping_cpu, token_id_mapping, token_id_mapping_torch = create_token_id_mapping_tensor(
+        group_m_list, mma_tiler_m, max_token_id=max_m, permuted_m=permuted_m
+    )
+
+    tile_idx_to_expert_idx = from_dlpack(_tile_idx_to_expert_idx).mark_layout_dynamic()
+    tile_idx_to_mn_limit = from_dlpack(_tile_idx_to_mn_limit).mark_layout_dynamic()
+    num_non_exiting_tiles = from_dlpack(_num_non_exiting_tiles).mark_layout_dynamic()
+
+    alpha = from_dlpack(alpha_torch_cpu.cuda()).mark_layout_dynamic()
+
+    # Create sfc_tensor and norm_const_tensor when c_dtype is Float4E2M1FN
+    sfc_torch_cpu = None
+    sfc_tensor = None
+    sfc_torch_gpu = None
+    norm_const_torch_cpu = None
+    norm_const_tensor = None
+    norm_const_torch_gpu = None
+    n_out = n // 2  # Output N dimension after SwiGLU fusion
+    if c_dtype == cutlass.Float4E2M1FN:
+        # Create scale factor C tensor for quantized output
+        sfc_torch_cpu, sfc_tensor, sfc_torch_gpu = create_scale_factor_tensor(
+            1, tensor_m, n_out, sf_vec_size, sf_dtype
+        )
+        # Create norm_const_tensor with value 1.0
+        norm_const_torch = torch.tensor([1.0], dtype=torch.float32, device="cuda")
+        norm_const_tensor = from_dlpack(norm_const_torch).mark_layout_dynamic()
+        norm_const_torch_cpu = norm_const_torch.cpu()
+
+    return (
+        a_tensor,
+        b_tensor,
+        c_tensor,
+        sfa_tensor,
+        sfb_tensor,
+        sfc_tensor,
+        norm_const_tensor,
+        tile_idx_to_expert_idx,
+        tile_idx_to_mn_limit,
+        token_id_mapping,
+        num_non_exiting_tiles,
+        alpha,
+        a_torch_cpu,
+        b_torch_cpu,
+        c_torch_cpu,
+        sfa_torch_cpu,
+        sfb_torch_cpu,
+        sfc_torch_cpu,
+        norm_const_torch_cpu,
+        alpha_torch_cpu,
+        a_torch_gpu,
+        b_torch_gpu,
+        c_torch_gpu,
+        sfa_torch_gpu,
+        sfb_torch_gpu,
+        sfc_torch_gpu,
+        norm_const_torch_gpu,
+        aligned_group_m_list,
+        valid_m,
+        token_id_mapping_cpu,
+    )
+
+
+def run(
+    nkl: Tuple[int, int, int],
+    group_m_list: Tuple[int, ...],
+    ab_dtype: Type[cutlass.Numeric],
+    c_dtype: Type[cutlass.Numeric],
+    acc_dtype: Type[cutlass.Numeric],
+    sf_dtype: Type[cutlass.Numeric],
+    sf_vec_size: int,
+    a_major: str,
+    b_major: str,
+    c_major: str,
+    mma_tiler_mn: Tuple[int, int],
+    cluster_shape_mn: Tuple[int, int],
+    tolerance: float,
+    warmup_iterations: int = 0,
+    iterations: int = 1,
+    skip_ref_check: bool = False,
+    use_cold_l2: bool = False,
+    permuted_m: int = None,
+    use_cupti: bool = False,
+    raster_along_m: bool = False,
+    **kwargs,
+):
+    """Run contiguous grouped GEMM with gather operation and SwiGLU fusion for FC1 layer.
+
+    Computation flow:
+    1. GEMM: acc = alpha * (SFA * A[token_ids]) * (SFB * B)
+    2. SwiGLU: C = up * silu(gate), where up/gate are extracted from interleaved acc (granularity=64)
+    3. Optional Quant: When c_dtype is Float4E2M1FN, generates SFC and quantizes output
+
+    Note: Output C has N/2 columns since SwiGLU combines pairs of (up, gate) from interleaved B weights.
+
+    This function:
+    - Creates tensors including token_id_mapping for gather operation
+    - Uses LDGSTS for loading A and SFA matrices with gather capability
+    - Uses TMA for loading B and SFB matrices with multicast
+    - Performs SwiGLU activation fusion in epilogue
+    - Optionally performs quantization fusion for Float4E2M1FN output
+    - Performs reference checking (if not skipped)
+    - Benchmarks kernel performance
+
+    :param nkl: (N, K, L) dimensions where L is the number of experts/groups
+    :param group_m_list: List of M values for each group
+    :param mma_tiler_mn: MMA tile shape (M, N), where mma_tiler_mn[0] is used for group M alignment
+    :param permuted_m: Optional padded M dimension for CUDA graph support. If provided,
+                     A/C matrices, token_id_mapping, and scale factor A will be padded to this size.
+    """
+    print("Running Blackwell Persistent Contiguous Grouped GEMM with Gather test:")
+    print(f"nkl: {nkl}")
+    print(f"group_m_list: {group_m_list}")
+    print(
+        f"AB dtype: {ab_dtype}, C dtype: {c_dtype}, Acc dtype: {acc_dtype}, "
+        f"Scale factor dtype: {sf_dtype}, SF Vec size: {sf_vec_size}"
+    )
+    if permuted_m is not None:
+        print(f"Padded M (CUDA graph support): {permuted_m}")
+    print(f"Matrix majors - A: {a_major}, B: {b_major}, C: {c_major}")
+    print(f"Mma Tiler (M, N): {mma_tiler_mn}, Cluster Shape (M, N): {cluster_shape_mn}")
+    print(f"2CTA MMA instructions: {'True' if mma_tiler_mn[0] == 256 else 'False'}")
+    print(f"Use TMA Store: {'True'}")
+    print(f"Tolerance: {tolerance}")
+    print(f"Warmup iterations: {warmup_iterations}")
+    print(f"Iterations: {iterations}")
+    print(f"Skip reference checking: {skip_ref_check}")
+    print(f"Use cold L2: {use_cold_l2}")
+    print(f"Use CUPTI: {use_cupti}")
+    print(f"Raster along M: {raster_along_m}")
+
+    # Unpack parameters
+    n, k, num_groups = nkl
+
+    if not torch.cuda.is_available():
+        raise RuntimeError("GPU is required to run this example!")
+
+    # Skip unsupported testcase
+    # Note: For grouped GEMM, we use mma_tiler_mn[0] as the m parameter for can_implement check
+    # since individual group M values vary
+    if not BlockScaledContiguousGatherGroupedGemmKernel.can_implement(
+        ab_dtype,
+        sf_dtype,
+        sf_vec_size,
+        c_dtype,
+        mma_tiler_mn,
+        cluster_shape_mn,
+        mma_tiler_mn[0],  # m (use mma_tiler_m as placeholder for grouped GEMM)
+        n,
+        k,
+        num_groups,
+        a_major,
+        b_major,
+        c_major,
+    ):
+        raise TypeError(
+            f"Unsupported testcase {ab_dtype}, {sf_dtype}, {sf_vec_size}, {acc_dtype}, "
+            f"{c_dtype}, {mma_tiler_mn}, {cluster_shape_mn}, {n}, {k}, {num_groups}, "
+            f"{a_major}, {b_major}, {c_major}"
+        )
+
+    (
+        a_tensor,
+        b_tensor,
+        c_tensor,
+        sfa_tensor,
+        sfb_tensor,
+        sfc_tensor,
+        norm_const_tensor,
+        tile_idx_to_expert_idx,
+        tile_idx_to_mn_limit,
+        token_id_mapping,
+        num_non_exiting_tiles,
+        alpha,
+        a_torch_cpu,
+        b_torch_cpu,
+        c_torch_cpu,
+        sfa_torch_cpu,
+        sfb_torch_cpu,
+        sfc_torch_cpu,
+        norm_const_torch_cpu,
+        alpha_torch_cpu,
+        a_torch_gpu,
+        b_torch_gpu,
+        c_torch_gpu,
+        sfa_torch_gpu,
+        sfb_torch_gpu,
+        sfc_torch_gpu,
+        norm_const_torch_gpu,
+        aligned_group_m_list,
+        valid_m,
+        token_id_mapping_cpu,
+    ) = create_tensors(
+        num_groups,
+        group_m_list,
+        n,
+        k,
+        a_major,
+        b_major,
+        c_major,
+        ab_dtype,
+        c_dtype,
+        sf_dtype,
+        sf_vec_size,
+        mma_tiler_mn[0],  # mma_tiler_m, also used for alignment
+        permuted_m,
+    )
+    # Configure gemm kernel
+    gemm = BlockScaledContiguousGatherGroupedGemmKernel(
+        sf_vec_size,
+        mma_tiler_mn,
+        cluster_shape_mn,
+        True,
+        topk=1,
+        raster_along_m=raster_along_m,
+    )
+
+    # Compute max active clusters on current device
+    hardware_info = cutlass.utils.HardwareInfo()
+    max_active_clusters = hardware_info.get_max_active_clusters(
+        cluster_shape_mn[0] * cluster_shape_mn[1]
+    )
+
+    # Get current CUDA stream from PyTorch
+    torch_stream = torch.cuda.current_stream()
+    # Get the raw stream pointer as a CUstream
+    current_stream = cuda.CUstream(torch_stream.cuda_stream)
+    # Compile gemm kernel
+    # sfc_tensor is optional and can be set as None (Python's None value) if not needed.
+    compiled_gemm = cute.compile(
+        gemm,
+        a_tensor,
+        b_tensor,
+        c_tensor,
+        sfa_tensor,
+        sfb_tensor,
+        sfc_tensor,
+        norm_const_tensor,
+        tile_idx_to_expert_idx,
+        tile_idx_to_mn_limit,
+        token_id_mapping,
+        num_non_exiting_tiles,
+        alpha,
+        max_active_clusters,
+        current_stream,
+    )
+
+    # Execution
+    compiled_gemm(
+        a_tensor,
+        b_tensor,
+        c_tensor,
+        sfa_tensor,
+        sfb_tensor,
+        sfc_tensor,
+        norm_const_tensor,
+        tile_idx_to_expert_idx,
+        tile_idx_to_mn_limit,
+        token_id_mapping,
+        num_non_exiting_tiles,
+        alpha,
+        current_stream,
+    )
+
+    torch.cuda.synchronize()
+    # Compute reference result
+    if not skip_ref_check:
+        print("Verifying results...")
+        # SwiGLU fusion with interleaved weights at granularity 64
+        # Output has N/2 columns since pairs of (up, gate) are combined
+        interleave_granularity = 64
+        n_out = n // 2
+
+        # Step 1: Compute full GEMM first
+        gemm_result = torch.empty((1, valid_m, n), dtype=torch.float32)
+        start = 0
+        a_torch_cpu_f32 = torch.einsum("mk,mk->mk", a_torch_cpu[:, :, 0], sfa_torch_cpu[:, :, 0])
+        for i, group_m in enumerate(aligned_group_m_list):
+            end = start + group_m
+            res_a = a_torch_cpu_f32[token_id_mapping_cpu[start:end]]
+            res_b = torch.einsum("nk,nk->nk", b_torch_cpu[:, :, i], sfb_torch_cpu[:, :, i])
+            gemm_result[0, start:end, :] = (
+                torch.einsum("mk,nk->mn", res_a, res_b) * alpha_torch_cpu[i]
+            )
+            start = end
+
+        # Step 2: Apply SwiGLU on interleaved GEMM result
+        # Weights are interleaved: [up_0:64, gate_64:128, up_128:192, gate_192:256, ...]
+        assert n % (2 * interleave_granularity) == 0
+        ref = torch.empty((1, valid_m, n_out), dtype=torch.float32)
+        for n_block in range(0, n, 2 * interleave_granularity):
+            # Up projection result: columns n_block to n_block+64
+            up_result = gemm_result[0, :, n_block : n_block + interleave_granularity]
+            # Gate projection result: columns n_block+64 to n_block+128
+            gate_result = gemm_result[
+                0, :, n_block + interleave_granularity : n_block + 2 * interleave_granularity
+            ]
+
+            # SwiGLU: up * silu(gate) where silu(x) = x * sigmoid(x)
+            silu_gate = gate_result * torch.sigmoid(gate_result)
+            output_block = up_result * silu_gate
+
+            # Store to output at n_block/2 position
+            out_start = n_block // 2
+            out_end = out_start + interleave_granularity
+            ref[0, :, out_start:out_end] = output_block
+
+        ref = ref.permute((1, 2, 0))
+
+        # Convert c back to f32 for comparison.
+        res = c_torch_cpu.cuda()
+        cute.testing.convert(
+            c_tensor,
+            from_dlpack(res, assumed_align=16).mark_layout_dynamic(
+                leading_dim=(1 if c_major == "n" else 0)
+            ),
+        )
+
+        # Only compare valid rows (in case of padding for cuda_graph)
+        res = res[:valid_m]
+        mask = token_id_mapping_cpu[:valid_m] >= 0
+        res = res.cpu()[mask]
+        ref = ref[mask]
+
+        print(f"valid_m: {valid_m}, ref.shape: {ref.shape}, res.shape: {res.shape}")
+
+        if c_dtype in (cutlass.Float32, cutlass.Float16, cutlass.BFloat16):
+            torch.testing.assert_close(res.cpu(), ref.cpu(), atol=tolerance, rtol=1e-02)
+        elif c_dtype in (cutlass.Float8E5M2, cutlass.Float8E4M3FN):
+            # Convert ref : f32 -> f8 -> f32
+            ref_f8_ = torch.empty(*(1, valid_m, n_out), dtype=torch.uint8, device="cuda").permute(
+                1, 2, 0
+            )
+            ref_f8 = from_dlpack(ref_f8_, assumed_align=16).mark_layout_dynamic(leading_dim=1)
+            ref_f8.element_type = c_dtype
+            ref_device = ref.cuda()
+            ref_tensor = from_dlpack(ref_device, assumed_align=16).mark_layout_dynamic(
+                leading_dim=1
+            )
+            cute.testing.convert(ref_tensor, ref_f8)
+            cute.testing.convert(ref_f8, ref_tensor)
+            torch.testing.assert_close(res.cpu(), ref_device.cpu(), atol=tolerance, rtol=1e-02)
+        elif c_dtype is cutlass.Float4E2M1FN:
+
+            def ceil_div(a, b):
+                return (a + b - 1) // b
+
+            def simulate_f8_quantization(tensor_f32: torch.Tensor, f8_dtype) -> torch.Tensor:
+                """Simulate f8 quantization: fp32 -> f8 -> fp32.
+
+                This models the precision loss when storing scale factors in f8 format.
+
+                :param tensor_f32: Input fp32 tensor (on CPU), shape (m, n, num_groups)
+                :param f8_dtype: Target f8 dtype (e.g., cutlass.Float8E4M3FN)
+                :return: Tensor after f32 -> f8 -> f32 round-trip (on CPU)
+                """
+                shape = tensor_f32.shape
+                # Create f8 tensor on GPU
+                f8_torch = torch.empty(*shape, dtype=torch.uint8, device="cuda")
+                f8_tensor = from_dlpack(f8_torch, assumed_align=16).mark_layout_dynamic(
+                    leading_dim=1
+                )
+                f8_tensor.element_type = f8_dtype
+                # Create f32 tensor on GPU
+                f32_device = tensor_f32.cuda()
+                f32_tensor = from_dlpack(f32_device, assumed_align=16).mark_layout_dynamic(
+                    leading_dim=1
+                )
+                # f32 -> f8 -> f32
+                cute.testing.convert(f32_tensor, f8_tensor)
+                cute.testing.convert(f8_tensor, f32_tensor)
+                return f32_device.cpu()
+
+            def simulate_nvfp4_quantization(tensor_f32: torch.Tensor) -> torch.Tensor:
+                """Simulate nvfp4 quantization: fp32 -> nvfp4 -> fp32.
+
+                This models the precision loss when storing output in nvfp4 format.
+
+                :param tensor_f32: Input fp32 tensor (on CPU), shape (m, n, ng)
+                :return: Tensor after f32 -> nvfp4 -> f32 round-trip (on CPU)
+                """
+                m, n, ng = tensor_f32.shape
+                # Create properly packed nvfp4 tensor using cutlass_torch utilities
+                ref_f32_torch = cutlass_torch.matrix(ng, m, n, False, cutlass.Float32)
+                f4_tensor, _ = cutlass_torch.cute_tensor_like(
+                    ref_f32_torch, cutlass.Float4E2M1FN, is_dynamic_layout=True, assumed_align=16
+                )
+                # Create f32 tensor on GPU
+                f32_device = tensor_f32.cuda()
+                f32_tensor = from_dlpack(f32_device, assumed_align=16).mark_layout_dynamic(
+                    leading_dim=1
+                )
+                # f32 -> f4 -> f32
+                cute.testing.convert(f32_tensor, f4_tensor)
+                cute.testing.convert(f4_tensor, f32_tensor)
+                return f32_device.cpu()
+
+            def compute_scale_factor(
+                tensor_f32: torch.Tensor,
+                sf_vec_size: int,
+                norm_const: float,
+                rcp_limits: float,
+            ) -> torch.Tensor:
+                """Compute scale factor for nvfp4 quantization.
+
+                Scale factor = abs_max_per_vector * norm_const * rcp_limits
+
+                :param tensor_f32: Input fp32 tensor, shape (m, n, ng)
+                :param sf_vec_size: Vector size for scale factor (e.g., 16)
+                :param norm_const: Normalization constant
+                :param rcp_limits: Reciprocal of dtype max value (e.g., 1/6.0 for nvfp4)
+                :return: Scale factor tensor, shape (m, sfn, ng) where sfn = ceil(n / sf_vec_size)
+                """
+                m, n, ng = tensor_f32.shape
+                sfn = ceil_div(n, sf_vec_size)
+                # Reshape to (m, sfn, sf_vec_size, ng) for abs max computation
+                # Pad n dimension if needed
+                padded_n = sfn * sf_vec_size
+                if padded_n > n:
+                    tensor_padded = torch.zeros(m, padded_n, ng, dtype=tensor_f32.dtype)
+                    tensor_padded[:, :n, :] = tensor_f32
+                else:
+                    tensor_padded = tensor_f32
+                tensor_reshaped = tensor_padded.view(m, sfn, sf_vec_size, ng)
+                # Compute abs max over sf_vec_size dimension
+                abs_max, _ = torch.abs(tensor_reshaped).max(dim=2)  # (m, sfn, l)
+                # Compute scale factor
+                scale_factor = abs_max * norm_const * rcp_limits
+                return scale_factor
+
+            def apply_quantization_scale(
+                tensor_f32: torch.Tensor,
+                scale_factor: torch.Tensor,
+                sf_vec_size: int,
+                norm_const: float,
+            ) -> torch.Tensor:
+                """Apply quantization scale to tensor.
+
+                Output = tensor * (norm_const / scale_factor).
+                This simulates the kernel's quantization scaling.
+
+                :param tensor_f32: Input fp32 tensor, shape (m, n, ng)
+                :param scale_factor: Scale factor tensor, shape (m, sfn, ng)
+                :param sf_vec_size: Vector size for scale factor
+                :param norm_const: Normalization constant
+                :return: Scaled tensor, shape (m, n, ng)
+                """
+                m, n, ng = tensor_f32.shape
+                sfn = scale_factor.shape[1]
+                # Compute reciprocal scale, clamping inf to fp32_max (matching kernel fmin behavior)
+                fp32_max = torch.tensor(3.40282346638528859812e38, dtype=torch.float32)
+                scale_rcp = norm_const * scale_factor.reciprocal()
+                scale_rcp = torch.where(torch.isinf(scale_rcp), fp32_max, scale_rcp)
+                # Expand scale factor to match tensor dimensions
+                # (m, sfn, ng) -> (m, sfn, sf_vec_size, ng) -> (m, sfn * sf_vec_size, ng)
+                scale_rcp_expanded = scale_rcp.unsqueeze(2).expand(m, sfn, sf_vec_size, ng)
+                scale_rcp_expanded = scale_rcp_expanded.reshape(m, sfn * sf_vec_size, ng)
+                # Trim to exact n dimension
+                scale_rcp_expanded = scale_rcp_expanded[:, :n, :]
+                # Apply scale
+                return tensor_f32 * scale_rcp_expanded
+
+            def unswizzle_kernel_sfc(
+                sfc_tensor,
+                permuted_m: int,
+                n_out: int,
+                sf_vec_size: int,
+            ) -> torch.Tensor:
+                """Unswizzle kernel's scale factor tensor from MMA layout to MKL layout.
+
+                :param sfc_tensor: Kernel's scale factor cute tensor (swizzled MMA layout)
+                :param permuted_m: Padded M dimension
+                :param n_out: Output N dimension
+                :param sf_vec_size: Vector size for scale factor
+                :return: Unswizzled scale factor tensor, shape (permuted_m, sfn, 1)
+                """
+                sfn = ceil_div(n_out, sf_vec_size)
+                unswizzled_sfc = torch.empty(permuted_m, sfn, 1, dtype=torch.float32)
+                # Create swizzled layout tensor and convert from kernel sfc
+                swizzled_sfc_cpu, _ = create_sf_layout_tensor(1, permuted_m, n_out, sf_vec_size)
+                swizzled_sfc_tensor, swizzled_sfc_torch = cutlass_torch.cute_tensor_like(
+                    swizzled_sfc_cpu, cutlass.Float32, is_dynamic_layout=True, assumed_align=16
+                )
+                cute.testing.convert(sfc_tensor, swizzled_sfc_tensor)
+                swizzled_sfc_cpu = swizzled_sfc_torch.cpu()
+                # Convert from swizzled to MKL layout
+                cvt_sf_M32x4xrm_K4xrk_L_to_MKL(
+                    from_dlpack(swizzled_sfc_cpu),
+                    from_dlpack(unswizzled_sfc),
+                )
+                return unswizzled_sfc
+
+            # ============================================================
+            # Step 1: Compute reference scale factor (SFC) from SwiGLU output
+            # ============================================================
+            norm_const = norm_const_torch_cpu.item()
+            rcp_limits = gemm.get_dtype_rcp_limits(c_dtype)
+
+            # Compute reference SFC: abs_max * norm_const * rcp_limits
+            ref_sfc_f32 = compute_scale_factor(ref, sf_vec_size, norm_const, rcp_limits)
+            # Simulate f8 quantization for SFC (kernel stores SFC in f8 format)
+            ref_sfc_f32 = simulate_f8_quantization(ref_sfc_f32, sf_dtype)
+
+            # ============================================================
+            # Step 2: Verify kernel SFC matches reference SFC
+            # ============================================================
+            permuted_m = token_id_mapping_cpu.shape[0]
+            kernel_sfc = unswizzle_kernel_sfc(sfc_tensor, permuted_m, n_out, sf_vec_size)
+            torch.testing.assert_close(
+                ref_sfc_f32, kernel_sfc[:valid_m][mask], atol=tolerance, rtol=1e-02
+            )
+            print("SFC Tensor comparison passed!")
+
+            # ============================================================
+            # Step 3: Apply quantization scale and simulate nvfp4 precision loss
+            # ============================================================
+            # Apply scale: ref_scaled = ref * (norm_const / sfc)
+            ref_scaled = apply_quantization_scale(ref, ref_sfc_f32, sf_vec_size, norm_const)
+            # Simulate nvfp4 quantization: f32 -> nvfp4 -> f32
+            ref_quantized = simulate_nvfp4_quantization(ref_scaled)
+
+            # ============================================================
+            # Step 4: Compare kernel output with reference
+            # ============================================================
+            print("Verifying C Tensor...")
+            res_cpu = res.cpu()
+            diff = torch.abs(res_cpu - ref_quantized)
+            within_tolerance = (diff <= tolerance) | (diff <= torch.abs(ref_quantized) * 1e-02)
+            pass_rate = within_tolerance.float().mean().item()
+            print(f"C Tensor pass rate: {pass_rate * 100:.2f}% (threshold: 95%)")
+            assert pass_rate >= 0.95, (
+                f"Only {pass_rate * 100:.2f}% elements within tolerance, expected >= 95%"
+            )
+
+    def generate_tensors():
+        # Reuse existing CPU reference tensors and create new GPU tensors from them
+        (
+            a_tensor,
+            b_tensor,
+            c_tensor,
+            sfa_tensor,
+            sfb_tensor,
+            sfc_tensor,
+            norm_const_tensor,
+            tile_idx_to_expert_idx,
+            tile_idx_to_mn_limit,
+            token_id_mapping,
+            num_non_exiting_tiles,
+            alpha,
+            a_torch_cpu,
+            b_torch_cpu,
+            c_torch_cpu,
+            sfa_torch_cpu,
+            sfb_torch_cpu,
+            sfc_torch_cpu,
+            norm_const_torch_cpu,
+            alpha_torch_cpu,
+            a_torch_gpu,
+            b_torch_gpu,
+            c_torch_gpu,
+            sfa_torch_gpu,
+            sfb_torch_gpu,
+            sfc_torch_gpu,
+            norm_const_torch_gpu,
+            aligned_group_m_list,
+            valid_m,
+            token_id_mapping_cpu,
+        ) = create_tensors(
+            num_groups,
+            group_m_list,
+            n,
+            k,
+            a_major,
+            b_major,
+            c_major,
+            ab_dtype,
+            c_dtype,
+            sf_dtype,
+            sf_vec_size,
+            mma_tiler_mn[0],  # mma_tiler_m, also used for alignment
+            permuted_m,
+        )
+        return cute.testing.JitArguments(
+            a_tensor,
+            b_tensor,
+            c_tensor,
+            sfa_tensor,
+            sfb_tensor,
+            sfc_tensor,
+            norm_const_tensor,
+            tile_idx_to_expert_idx,
+            tile_idx_to_mn_limit,
+            token_id_mapping,
+            num_non_exiting_tiles,
+            alpha,
+            current_stream,
+        )
+
+    workspace_count = 1
+    if use_cold_l2:
+        # Calculate actual tensor_m used (with padding if permuted_m provided)
+        tensor_m = permuted_m if permuted_m is not None else valid_m
+        one_workspace_bytes = (
+            a_torch_gpu.numel() * a_torch_gpu.element_size()
+            + b_torch_gpu.numel() * b_torch_gpu.element_size()
+            + c_torch_gpu.numel() * c_torch_gpu.element_size()
+            + sfa_torch_gpu.numel() * sfa_torch_gpu.element_size()
+            + sfb_torch_gpu.numel() * sfb_torch_gpu.element_size()
+            + (tensor_m // mma_tiler_mn[0])
+            * 4  # tile_idx_to_expert_idx length (tiles) * sizeof(int32)
+            + (tensor_m // mma_tiler_mn[0])
+            * 4  # tile_idx_to_mn_limit length (tiles) * sizeof(int32)
+            + tensor_m * 4  # token_id_mapping_tensor length (elements) * sizeof(int32)
+            + 1 * 4  # num_non_exiting_tiles (1 element) * sizeof(int32)
+            + alpha_torch_cpu.numel() * alpha_torch_cpu.element_size()
+        )
+        workspace_count = cute.testing.get_workspace_count(
+            one_workspace_bytes, warmup_iterations, iterations
+        )
+
+    exec_time = benchmark(
+        compiled_gemm,
+        workspace_generator=generate_tensors,
+        workspace_count=workspace_count,
+        stream=current_stream,
+        warmup_iterations=warmup_iterations,
+        iterations=iterations,
+        use_cupti=use_cupti,
+    )
+    return exec_time
+
+
+if __name__ == "__main__":
+
+    def parse_comma_separated_ints(s: str) -> Tuple[int, ...]:
+        try:
+            return tuple(int(x.strip()) for x in s.split(","))
+        except ValueError:
+            raise argparse.ArgumentTypeError("Invalid format. Expected comma-separated integers.")
+
+    def read_benchmark_file(
+        filepath: str,
+    ) -> Tuple[Tuple[int, int, int], Tuple[int, ...]]:
+        """Read benchmark file and return nkl and group_m_list.
+
+        File format:
+            0 256x512x128
+            1 512x512x512
+            2 1024x256x128
+            ...
+
+        Returns:
+            Tuple of ((n, k, l), (m0, m1, m2, ...)) where:
+            - n, k are from the first problem
+            - l is the total number of problems (groups)
+            - (m0, m1, m2, ...) are the M values for each group
+        """
+        problems = []
+        try:
+            with open(filepath, "r") as f:
+                for line in f:
+                    line = line.strip()
+                    if not line or line.startswith("#"):
+                        continue
+
+                    parts = line.split()
+                    if len(parts) < 2:
+                        continue
+
+                    # Parse index and dimensions (e.g., "256x512x128")
+                    _ = int(parts[0])  # index (unused)
+                    dims = parts[1].split("x")
+                    if len(dims) == 3:
+                        m, n, k = int(dims[0]), int(dims[1]), int(dims[2])
+                        problems.append((m, n, k))
+
+            if not problems:
+                raise ValueError(f"No valid problems found in benchmark file: {filepath}")
+
+            # Use first problem's N, K dimensions
+            m_first, n, k = problems[0]
+            num_groups = len(problems)
+
+            # Extract M values for each group
+            m_values = tuple(m for m, _, _ in problems)
+
+            print(f"Loaded {num_groups} problems from benchmark file")
+            print(f"Using N={n}, K={k}, L={num_groups}")
+            print(f"M values per group: {m_values}")
+
+            return ((n, k, num_groups), m_values)
+
+        except FileNotFoundError:
+            raise argparse.ArgumentTypeError(f"Benchmark file not found: {filepath}")
+        except Exception as e:
+            raise argparse.ArgumentTypeError(f"Error reading benchmark file: {e}")
+
+    parser = argparse.ArgumentParser(description="Example of Dense Persistent GEMM on Blackwell.")
+
+    parser.add_argument(
+        "--nkl",
+        type=parse_comma_separated_ints,
+        default=(256, 512, 1),
+        help="nkl dimensions: N, K, L (number of groups) (comma-separated)",
+    )
+
+    parser.add_argument(
+        "--fixed_m",
+        type=int,
+        default=None,
+        help="Fixed M value for all groups. If specified, all groups will have this M dimension.",
+    )
+
+    parser.add_argument(
+        "--custom_mask",
+        type=parse_comma_separated_ints,
+        default=None,
+        help="Custom M values for each group (comma-separated integers). "
+        "Length must match L dimension. Overrides --fixed_m.",
+    )
+
+    parser.add_argument(
+        "--benchmark",
+        type=str,
+        default=None,
+        help="Path to benchmark file with problem sizes (format: 'index MxNxK' per line). "
+        "If specified, overrides --nkl, --fixed_m, and --custom_mask.",
+    )
+
+    parser.add_argument(
+        "--permuted_m",
+        type=int,
+        default=None,
+        help="Optional padded M dimension for CUDA graph support. If specified, A/C matrices "
+        "and scale factor A will be padded to this size. "
+        "Example: permuted_m = 4096*8 + 8*255 = 34808",
+    )
+
+    parser.add_argument(
+        "--mma_tiler_mn",
+        type=parse_comma_separated_ints,
+        default=(128, 128),
+        help="Mma tile shape (comma-separated)",
+    )
+    parser.add_argument(
+        "--cluster_shape_mn",
+        type=parse_comma_separated_ints,
+        default=(1, 1),
+        help="Cluster shape (comma-separated)",
+    )
+    parser.add_argument("--ab_dtype", type=cutlass.dtype, default=cutlass.Float4E2M1FN)
+    parser.add_argument("--c_dtype", type=cutlass.dtype, default=cutlass.BFloat16)
+    parser.add_argument("--acc_dtype", type=cutlass.dtype, default=cutlass.Float32)
+    parser.add_argument("--sf_dtype", type=cutlass.dtype, default=cutlass.Float8E4M3FN)
+    parser.add_argument("--sf_vec_size", type=int, default=16)
+    parser.add_argument("--a_major", choices=["k"], type=str, default="k")
+    parser.add_argument("--b_major", choices=["k"], type=str, default="k")
+    parser.add_argument("--c_major", choices=["n", "m"], type=str, default="n")
+    parser.add_argument("--tolerance", type=float, default=1e-01, help="Tolerance for validation")
+    parser.add_argument("--warmup_iterations", type=int, default=0, help="Warmup iterations")
+    parser.add_argument(
+        "--iterations",
+        type=int,
+        default=1,
+        help="Number of iterations to run the kernel",
+    )
+    parser.add_argument("--skip_ref_check", action="store_true", help="Skip reference checking")
+    parser.add_argument("--use_cold_l2", action="store_true", default=False, help="Use cold L2")
+    parser.add_argument(
+        "--use_cupti", action="store_true", default=False, help="Use CUPTI for profiling"
+    )
+    parser.add_argument(
+        "--raster_along_m", action="store_true", default=False, help="Raster along M dimension"
+    )
+
+    args = parser.parse_args()
+
+    # Process arguments to generate nkl and group_m_list
+    if args.benchmark:
+        # Read from benchmark file
+        nkl, group_m_list = read_benchmark_file(args.benchmark)
+    else:
+        # Use command line arguments
+        if len(args.nkl) != 3:
+            parser.error("--nkl must contain exactly 3 values")
+
+        n, k, num_groups = args.nkl
+        nkl = (n, k, num_groups)
+
+        # Generate group_m_list based on --custom_mask or --fixed_m
+        if args.custom_mask is not None:
+            group_m_list = args.custom_mask
+            if len(group_m_list) != num_groups:
+                parser.error(
+                    f"--custom_mask must have exactly {num_groups} values (matching L dimension)"
+                )
+        elif args.fixed_m is not None:
+            group_m_list = tuple([args.fixed_m] * num_groups)
+        else:
+            # Default: use 128 for all groups
+            group_m_list = tuple([128] * num_groups)
+
+    if len(args.mma_tiler_mn) != 2:
+        parser.error("--mma_tiler_mn must contain exactly 2 values")
+
+    if len(args.cluster_shape_mn) != 2:
+        parser.error("--cluster_shape_mn must contain exactly 2 values")
+
+    exec_time = run(
+        nkl,
+        group_m_list,
+        args.ab_dtype,
+        args.c_dtype,
+        args.acc_dtype,
+        args.sf_dtype,
+        args.sf_vec_size,
+        args.a_major,
+        args.b_major,
+        args.c_major,
+        args.mma_tiler_mn,
+        args.cluster_shape_mn,
+        args.tolerance,
+        args.warmup_iterations,
+        args.iterations,
+        args.skip_ref_check,
+        args.use_cold_l2,
+        args.permuted_m,
+        args.use_cupti,
+        args.raster_along_m,
+    )
+    print(f"Execution time: {exec_time:.2f} us")
+    print("PASS")
diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_flashinfer_attention_op.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_flashinfer_attention_op.py
index e27477112f..9ce3dcd8ec 100644
--- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_flashinfer_attention_op.py
+++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_flashinfer_attention_op.py
@@ -574,6 +574,17 @@ def test_flashinfer_attention_op_context_input_pos(seq, batch_size, n_heads, dty
         (MAX_BATCH_SIZE, MAX_SEQ_LEN, N_HEADS, D_HEAD), dtype=DTYPE, device=device
     )
 
+    # Initialize the prefilled portion of the cache with random data
+    # This simulates a chunked prefill scenario where previous chunks have already
+    # populated the cache at positions 0:PREFILL_SEQ_LEN
+    if PREFILL_SEQ_LEN > 0:
+        k_cache[0:BATCH_SIZE, 0:PREFILL_SEQ_LEN, :, :] = torch.randn(
+            BATCH_SIZE, PREFILL_SEQ_LEN, N_HEADS, D_HEAD, dtype=DTYPE, device=device
+        )
+        v_cache[0:BATCH_SIZE, 0:PREFILL_SEQ_LEN, :, :] = torch.randn(
+            BATCH_SIZE, PREFILL_SEQ_LEN, N_HEADS, D_HEAD, dtype=DTYPE, device=device
+        )
+
     # make sure planner is initialized
     workspace = torch.empty(128 * 1024 * 1024, dtype=torch.uint8, device=device)
     _GlobalFlashInferPlanner.init_workspace(workspace)
diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_llama4_vlm_patch.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_llama4_vlm_patch.py
index a1879ed30a..af28829e73 100644
--- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_llama4_vlm_patch.py
+++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_llama4_vlm_patch.py
@@ -1,4 +1,3 @@
-import pytest
 import torch
 from _model_test_utils import get_small_model_config
 from build_and_run_ad import ExperimentConfig
@@ -10,10 +9,6 @@ from tensorrt_llm._torch.auto_deploy.utils._graph import move_to_device
 
 
 def test_build_run_llama4_vlm():
-    pytest.skip(
-        "Skipping test_build_run_llm4_vlm because Llama4 is giving an error on upgrading transformers version to 4.57.1"
-        "https://nvbugspro.nvidia.com/bug/5732942"
-    )
     atol = 1e-3
     rtol = 1e-3
 
diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py
index 4b2c75f29d..79457fbfca 100644
--- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py
+++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py
@@ -201,19 +201,6 @@ def _check_ad_config(experiment_config: ExperimentConfig, llm_args: LlmArgs):
     ],
 )
 def test_build_ad(model_hub_id: str, llm_extra_args: dict):
-    if (
-        model_hub_id == "mistralai/Mixtral-8x7B-Instruct-v0.1"
-        and llm_extra_args.get("mode") != "transformers"
-    ):
-        pytest.skip(
-            "Mixtral-8x7B-Instruct-v0.1 is giving an error on upgrading transformers version to 4.57.1"
-            "https://nvbugspro.nvidia.com/bug/5732942"
-        )
-    if model_hub_id == "Qwen/Qwen3-30B-A3B" and llm_extra_args.get("mode") != "transformers":
-        pytest.skip(
-            "Qwen3-30B-A3B is giving an error on upgrading transformers version to 4.57.1"
-            "https://nvbugspro.nvidia.com/bug/5732942"
-        )
     experiment_config = get_small_model_config(model_hub_id, **llm_extra_args)
     experiment_config["args"]["runtime"] = "demollm"  # Default runtime set to demollm
     experiment_config["args"]["world_size"] = 0  # Default world_size set to 0