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OWASP Agent Memory Guard

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★ 166 • Updated Aug 18, 2026, 03:10 PM

OWASP Agent Memory Guard is an OWASP project focused on securing the memory stores used by AI agents.

Use Cases ▼
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Securing memory stores in autonomous AI agents

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Preventing prompt injection from corrupting agent context

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Auditing access to agent memory in enterprise applications

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Protecting sensitive user data retained by conversational agents

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Hardening agent workflows against memory poisoning

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Integrating security controls into agent memory pipelines

What Problem It Solves ▼

AI agents store and reuse information from past interactions, making their memory a high-value target for attacks such as prompt injection, memory poisoning, and data exfiltration. OWASP Agent Memory Guard provides a security-focused approach to protect agent memory, reducing the risk of unauthorized access and malicious manipulation.

Key Features ▼
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Backed by OWASP's security community

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Focused specifically on agent memory threats

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Open source governance model

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Addresses prompt injection and memory poisoning risks

Overview

OWASP Agent Memory Guard is an OWASP project focused on securing the memory stores used by AI agents. AI agents increasingly rely on persistent and ephemeral memory to retain context, user preferences, tool outputs, and learned knowledge; these memory stores can be targeted by prompt injection, data poisoning, unauthorized access, or accidental leakage. The project aims to provide guidance and controls to guard such memory from security threats.

Full Description ▼

As part of the OWASP ecosystem, the project is intended to be open source and community-driven, aligning with OWASP's mission to improve software security. It addresses both design considerations and practical safeguards for agent memory, potentially including access controls, integrity checks, and input validation to prevent malicious manipulation of retained state.

Pros & Cons

Pros

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Backed by OWASP's security community

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Focused specifically on agent memory threats

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Open source governance model

+

Addresses prompt injection and memory poisoning risks

Cons

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Limited public documentation or release details as of this listing

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Not a managed service; requires self-integration

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Maturity and adoption are unclear

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May require significant customization for specific agent frameworks

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