Python: [Feature Request] Memory Poisoning Protection for Semantic Kernel via OWASP Agent Memory Guard

Problem

Semantic Kernel agents with persistent memory (ChatHistory, VolatileMemoryStore, or custom stores) are vulnerable to memory poisoning attacks. Adversarial inputs stored in memory can cause agents to leak secrets, ignore instructions, or produce corrupted outputs. OWASP identifies this as a top risk for LLM applications.

Proposed Solution

OWASP Agent Memory Guard (AMG) is an open-source Python library that wraps any memory store as a transparent security layer:

• pip install agent-memory-guard
• Scans every memory write for prompt injection, PII leakage, and tampering
• 92.5% detection rate on AgentThreatBench
• <5ms latency per scan

Links

• GitHub: https://github.com/OWASP/www-project-agent-memory-guard
• PyPI: https://pypi.org/project/agent-memory-guard/
• Benchmark: https://pypi.org/project/agent-threat-bench/

Would the Semantic Kernel team consider integrating AMG as a security layer for agent memory? Happy to contribute a PR.

The issue names no Semantic Kernel files or tests. Start by reviewing the ChatHistory, VolatileMemoryStore, and custom memory-store integration points, then examine the linked agent-memory-guard package. Done means an agreed integration scope with validation criteria, or a clearly scoped implementation path.