Add regulated-ai-governance and enterprise-rag-patterns to Security section

[ashutoshrana]

What this adds

Two open-source Python compliance libraries added to the Frameworks for LLM security table under the Security section.

regulated-ai-governance

Policy enforcement, PII detection, consent management, and data lineage for AI agents under six regulations:

• Regulations: FERPA, HIPAA, GDPR, CCPA, GLBA, SOC 2
• Framework integrations: LangChain, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, Haystack
• Core: GovernedActionGuard wraps any AI action with pre-flight policy check + structured audit record
• MIT licensed, pip-installable: pip install regulated-ai-governance

enterprise-rag-patterns

FERPA/HIPAA/GDPR-compliant RAG retrieval with:

• Identity-scoped vector-store filter (prevents cross-user document leakage)
• Structured disclosure audit logging
• GDPR Art. 17 erasure handling for vector indexes
• MIT licensed: pip install enterprise-rag-patterns

Why this fits the Security section

The existing security section covers adversarial attacks (Plexiglass) and observability tools. These two libraries cover the regulatory compliance layer — the gap between "is my LLM secure?" and "is my AI system legally compliant with HIPAA/FERPA/GDPR?" Both are directly relevant to LLMOps practitioners deploying in healthcare, higher-education, and financial-services environments.

[ashutoshrana]

Hi! Friendly ping — happy to update the description or add any additional context if that would help move this forward. Both packages are actively maintained with weekly PyPI releases and are the only open-source libraries covering 65+ regulatory frameworks for AI agents. Let me know if there's anything I should change. Thanks!

[ashutoshrana]

Closing for now — will resubmit with DCO sign-off and updated description. Thanks for the consideration.