OWASP Agent Memory Guard: runtime screening for agent memory reads and writes
OWASP Agent Memory Guard is an incubator project and reference implementation for screening AI-agent memory reads and writes against prompt injection, protected-key tampering, secret leakage, size anomalies, and rapid-change patterns.
Date
Feb 16, 2026
First Seen
Feb 16, 2026
Last Reviewed
Jun 1, 2026
Publisher
OWASP
Source Type
repo
Source Summary
What It Contains
OWASP Agent Memory Guard is an incubator project and reference implementation for screening AI-agent memory reads and writes against prompt injection, protected-key tampering, secret leakage, size anomalies, and rapid-change patterns.
Extracted Claims
- Persistent agent memory, including RAG indexes, chat history, scratchpads, and vector stores, can become a privileged input if untrusted content is written into it.
- Memory poisoning differs from front-door prompt injection because the malicious content can survive across sessions and steer later tool use or data disclosure.
- The project wraps agent memory stores and applies policy actions such as allow, redact, quarantine, or block.
- It reports benchmark coverage across prompt injection, protected-key tampering, sensitive-data leakage, and size-anomaly categories, with local operation and no external API dependency.
- Integrations and recipes are documented for LangChain, OpenAI Agents SDK, AutoGen, mem0, and other memory-store-compatible frameworks.
Evidence Quality
Primary source — public OWASP GitHub repository. The repository was updated on 2026-05-31 and surfaced in a 2026-06-01 Hacker News Show HN item, but the control should be treated as defensive guidance and implementation evidence rather than proof of a specific exploited incident.
Follow-Up
- Track whether OWASP publishes additional guidance for ASI06 memory poisoning in agentic applications.
- Consider whether Armorer health checks should flag persistent-memory-enabled profiles that lack explicit memory scope, policy logging, or review gates.
- Monitor package releases and integration support before recommending production deployment of this specific library.