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owasp-llm

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The open-source diagnostic for AI misalignment. 32 tests across fabrication, manipulation, deception, unpredictability, and opacity. Provider-agnostic. Runs against OpenAI, Anthropic, Bedrock, Azure, Gemini, and more. Letter grade in under 5 minutes, content-addressed manifest for bit-identical replay. Built by iMe.

  • Updated Jun 5, 2026
  • Python
claude-security-skills

25 production-tested defensive security skills for Claude Code - WordPress, VPS, Cloudflare, Next.js hardening, AI agent guardrails, MCP security, prompt injection defense, OWASP LLM Top 10, LLM coding failure modes (slopsquatting, hallucinated APIs, sycophancy), incident response, GDPR/DACH compliance. MIT, battle-tested.

  • Updated Jun 3, 2026
  • Python

Exposure intelligence for the AI-infrastructure layer — finds and weighs leaked credentials, MCP/agent configs, git-metadata secrets, and supply-chain risk, and tells you which exposures to trust. Active verification, orphan-signal triage, SARIF dedup. OWASP LLM + MITRE ATLAS tagged.

  • Updated Jun 6, 2026
  • Python
ZTIF

Zero Trust Intent Framework redefines where security decisions happen — from the boundary to the behavior. Intent analysis, contextual verification, and continuous trust evaluation layered on top of OWASP input validation. Static checkpoint → dynamic security posture. NIST SP 800-228 · OWASP LLM Top 10.

  • Updated May 27, 2026
  • Jupyter Notebook

Blackwall LLM Shield is an open-source AI security toolkit for JavaScript and Python that protects LLM apps from prompt injection, sensitive data leaks, unsafe tool calls, and hostile RAG content with prompt sanitisation, PII masking, output inspection, policy enforcement, and audit trails.

  • Updated Mar 27, 2026
  • JavaScript

Blackwall LLM Shield is an open-source AI security toolkit for JavaScript and Python that protects LLM apps from prompt injection, sensitive data leaks, unsafe tool calls, and hostile RAG content with prompt sanitization, PII masking, output inspection, policy enforcement, and audit trails.

  • Updated Mar 27, 2026
  • Python

Hands-on demos for the Pluralsight course: Generative AI Data Privacy and Safe Use for Developers. Covers PII masking, prompt injection attacks and defenses, five guardrail rail types (input, retrieval, dialog, execution, output), evaluation release gates, and dashboards mapped to EU AI Act, NIST AI RMF, and ISO/IEC 42001.

  • Updated May 3, 2026
  • Python

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