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Open-source implementation of an agent-centric red-teaming scanner inspired by Cloud Security Alliance guidance. Automated security testing for AI agents and LLM applications.
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43
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feat: replace Terragon scaffolding with real adversarial LLM scanner
2540d15View on GitHubfeat(validation): add comprehensive production validation and test suites (#28)
b16130bView on GitHubchore(deployment-report): update timestamps and performance metrics in deployment reports (#27)
440f5b3View on GitHubfeat(deployment): add comprehensive production deployment final preparation (#26)
24e6a4eView on GitHubfeat(scaling): add scaling metrics and policy dataclasses for auto-scaler (#25)
df2019cView on GitHubfeat(monitoring): add performance monitoring wrapper and global instance (#24)
bed0d14View on GitHubfix(reliability): avoid error when creating existing circuit breaker (#23)
9bb010bView on GitHubfeat(production): add production deployment guide, examples, and demos (#22)
f581c29View on GitHubfeat(quality-gates): add comprehensive quality gates with 85%+ coverage requirement (#21)
e2655f9View on GitHubfeat(quality_gates): add comprehensive multi-generation quality gates and tests (#20)
995d1ffView on GitHubfeat(autonomous-sdlc): complete autonomous SDLC execution with quality gates and deployment (#19)
ff0f8afView on GitHubfeat: Complete Autonomous SDLC Execution - Global-Ready Production Framework (#18)
25d729bView on GitHubfeat: Complete Autonomous SDLC Execution - Production-Ready Implementation (#17)
ffc9230View on GitHubfeat: Complete Autonomous SDLC Execution - Production-Ready AI Security Framework (#16)
b3dddcfView on GitHubfeat(agentic_redteam): add advanced reliability and scaling modules (#15)
278c096View on GitHub