memory-management
Pass
Audited by Gen Agent Trust Hub on Sep 19, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The Python implementation pattern provided in SKILL.md for a memory-augmented agent lacks input sanitization or boundary markers when interpolating untrusted data into LLM prompts.
- Ingestion points: The user_input and context variables in the memory_augmented_agent function in SKILL.md.
- Boundary markers: No delimiters or 'ignore embedded instructions' markers are present in the provided prompt template examples.
- Capability inventory: The example pattern includes LLM generation and persistent database storage (memory.add).
- Sanitization: No logic for filtering, validating, or escaping external content is included in the implementation snippets.
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