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AML.T0080.000

AI Agent Context Poisoning: Memory

How AML.T0080.000 AI Agent Context Poisoning: Memory shows up in practice: the mapped risk classes in this atlas, the documented incidents that prove it's real, and the scenarios and controls to learn and defend against it.

Controls & guardrails that address this

4

Guardrails across the risks mapped to AML.T0080.000, grouped by control function. Filter by control category below.

Control category
Preventive · 1
Memory write validation, provenance & reviewinteractive

Being careful about what gets saved to long-term memory, labelling where it came from, and letting users see and delete their memories.

Detective · 3
Memory anomaly detection & quarantineinteractive

Watching for strange new memories — like instructions that suddenly appear — and holding them aside until checked.

Full-trace audit logginginteractive

Recording everything — questions, documents fetched, actions taken — so you can investigate when something goes wrong.

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AI RiskAtlas is an educational model of how GenAI & agentic systems work and fail. Architectures and payloads are illustrative and simplified for learning — not operational guidance. Real-world cases are summarised from public reporting.

Sources & further reading →·Built by Shi Yuan ↗