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SBOM for pyvisim 1.0.0

A Python library for image similarity analysis using Image Embedders and Neural Networks

CycloneDX PEP 740 attested No known vulnerabilities

Requires Python: >=3.10
PyPI: pyvisim 1.0.0
Download: https://pypi.org/project/pyvisim/#files
Homepage: https://mechacritter.github.io/Python-Visual-Similarity/
Source: https://github.com/MechaCritter/Python-Visual-Similarity

Available SBOMs

Read from .dist-info/sboms/ in each wheel.

pyvisim-1.0.0-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl

Attested

Publisher: GitHub Source: MechaCritter/Python-Visual-Similarity Workflow: publish_pypi.yml Environment: publish

auditwheel.cdx.json

CycloneDX/1.4 application/vnd.cyclonedx+json no known vulnerabilities

pyvisim-1.0.0-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl

Attested

Publisher: GitHub Source: MechaCritter/Python-Visual-Similarity Workflow: publish_pypi.yml Environment: publish

auditwheel.cdx.json

CycloneDX/1.4 application/vnd.cyclonedx+json no known vulnerabilities

pyvisim-1.0.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl

Attested

Publisher: GitHub Source: MechaCritter/Python-Visual-Similarity Workflow: publish_pypi.yml Environment: publish

auditwheel.cdx.json

CycloneDX/1.4 application/vnd.cyclonedx+json no known vulnerabilities

pyvisim-1.0.0-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl

Attested

Publisher: GitHub Source: MechaCritter/Python-Visual-Similarity Workflow: publish_pypi.yml Environment: publish

auditwheel.cdx.json

CycloneDX/1.4 application/vnd.cyclonedx+json no known vulnerabilities

pyvisim-1.0.0-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl

Attested

Publisher: GitHub Source: MechaCritter/Python-Visual-Similarity Workflow: publish_pypi.yml Environment: publish

auditwheel.cdx.json

CycloneDX/1.4 application/vnd.cyclonedx+json no known vulnerabilities

Known vulnerabilities

Components listed in these SBOMs, matched against the OSV database as of 2026-11-10.

OSV has no known vulnerabilities for the components these SBOMs list.

Access via TEA

Use the Transparency Exchange API to fetch this SBOM programmatically:

pip install libtea
python -m libtea https://pypi.sbomify.com pkg:pypi/[email protected]