recon-operations
claudeProvides authorized network, public-exposure, human, physical, and AI-system reconnaissance with explicit scope, contact, noise, evidence, and automation boundaries.
9 skills
152
claude
ml-system-security
Audits ML artifact lifecycles, decision boundaries, dataset integrity, and model-serving exposure with explicit evidence states.
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Plugin ml-system-security from marketplace zero-lab in zero-lab-ai/skills. Commands read from the repo's manifest — 19 days ago.
What it installs
Skills (4)
dataset-integrity-assessmentAudits dataset sources, labels, transformations, review, versioning, split integrity, retraining triggers, and rollback controls for poisoning and targeted degradation risk. Use when reviewing an ML training or evaluation data supply chain.
ml-decision-boundary-assessmentEvaluates classifiers and scoring models used as security gates for adversarial robustness, preprocessing differences, thresholds, abstention, and fallback behavior. Use when an authorized assessment must measure whether bounded input changes alter a security decision.
model-artifact-lifecycle-auditAudits how model artifacts are accepted, validated, stored, selected, loaded, executed, monitored, and retired. Use when reviewing model registries, loaders, CI/CD pipelines, scanner-to-runtime gaps, or ML supply-chain controls.
model-serving-exposure-auditAudits model-serving APIs, administrative and debug surfaces, vector stores, object storage, caches, workload identity, metadata access, and orchestration credentials. Use when reviewing the deployed infrastructure around model inference.
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