arXiv (All)
open access
From Attack Success to Attack Severity: Counterfactual Memory Attacks on LLM Agents
As LLM agents increasingly rely on persistent memory for long-horizon and personalized behavior, they can retain and reuse information across interactions, but this also creates a lasting channel through which malicious memory writes can influence future behavior. Persistent-memory attacks are typic
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Agent Memory: Characterization and System Implications of Stateful Long-Horizon Workloads#1062655
- Just-in-Time Memory: Learning to Curate Task-Adaptive Memory for LLM Agents#1063545
- Utility Under Attack: Agent Memory Poisoning and the Limits of Content Screening and Provenance Ranking#479983
- Distributed traces and the causal theory of constructive memory#74107
- MemRiskBench: Trace-Aware Risk-Preserving Evaluation for Long-Horizon LLM Agents#1084878
Record · ID 1119205
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive