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Last analyzed Sep 9, 2026

Language Model Security Database

985 research findings · 1119 evaluated models

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1 entry

Matches every word across titles, descriptions, sources, affected systems, and models.

Sleeper Memory Poisoning in LLM Agents

Published Analyzed Source: arXiv

The paper presents a specific black-box indirect prompt-injection evaluation: attacker-controlled external content can cause a memory-enabled assistant or external memory manager to persist a fabricated user memory, which may later be retrieved in a separate session and steer responses or agent actions. The authors evaluate injection, retrieval, and conditional adversarial usage separately across synthetic document and future-session datasets. The released repository provides defensive…

Hidden in Memory: Sleeper Memory Poisoning in LLM Agents
Evaluated models: GPT-5.4, GPT-5.5, Claude Sonnet 4.6+3 more
  • GPT-5.4
  • GPT-5.5
  • Claude Sonnet 4.6
  • Gemini 3.1 Pro
  • Kimi-K2.6
  • DeepSeek V4-Pro
Application layer
Injection
Poisoning
AI agents

Research methodology

Entries summarize publicly available primary-source security research. Model names reflect only systems explicitly evaluated by the cited paper, and measurements are research-reported unless independent verification is stated.

Discovery and publication are separate: new papers enter a candidate queue, then require human review and explicit approval before publication. Updates follow that review process, not a guaranteed daily publishing schedule. “Last analyzed” is the newest analysis date among published entries; it does not mean that all recent research has been covered.