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Adversarial Ml Python Packages

Python packages with the GitHub topic adversarial-ml. Sorted by monthly downloads, with stars and forks.
issdandavis
scbe-aethermoore

Geometric AI governance and evaluation framework with a 14-layer security pipeline, semantic projection, and reproducible benchmark lanes.

624 8 3
rudrasatani13
cot-redteam-agent

Red-team visible LLM reasoning — refusal quotes aren't success. Adaptive TUI, CI scan, OWASP tags, mock provider, proof-of-action agent lane.

181 2 2
deconvolute-labs
yara-gen

Generate YARA rules automatically from positive and negative examples. For PII detection, secret scanning, and prompt injection.

122 1 0
sparckix
ztare

Autonomous research engine for generating, testing, and governing auditable claims across science, proofs, and high-stakes projects.

102 20 3
OndiekiFrank
corpusguard

Production-ready RAG security testing and defense framework. Adversarial corpus poisoning attacks + Memory Hygiene Layer defense. Based on SSRN 6734225.

98 0 0
issdandavis
scbe-agent-bus

Geometric AI governance and evaluation framework with a 14-layer security pipeline, semantic projection, and reproducible benchmark lanes.

92 8 3
issdandavis
scbe-bookforge

Geometric AI governance and evaluation framework with a 14-layer security pipeline, semantic projection, and reproducible benchmark lanes.

73 8 3
deconvolute-labs
yaramint

Generate YARA rules automatically from positive and negative examples. For PII detection, secret scanning, and prompt injection.

67 1 0
issdandavis
scbe-polly-pad

Geometric AI governance and evaluation framework with a 14-layer security pipeline, semantic projection, and reproducible benchmark lanes.

63 8 3
issdandavis
scbe-govern

Geometric AI governance and evaluation framework with a 14-layer security pipeline, semantic projection, and reproducible benchmark lanes.

52 8 3
scthornton
mlsec

Collection of Python security analysis tools for ML models and infrastructure. Includes FGSM harness, model inspection, poison monitoring, and deployment security validation.

50 2 0
    • Original data from PyPI, GitHub, and OSV; downloads served through ClickHouse
    • Sources & methodology