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Last analyzed Sep 9, 2026

Language Model Security Database

985 research findings · 1119 evaluated models

Filtered research findings

1 entry

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

Agent Data Injection via Trusted-Metadata Spoofing

Published Analyzed Source: arXiv

Agent data injection (ADI) is a reproducible indirect injection class in which attacker-controlled external content is formatted to resemble trusted metadata or agent-context structure. The paper reports that probabilistic delimiter injection can cause agents to misinterpret untrusted content as trusted element IDs, author identities, or tool responses, leading to unintended clicks, command execution, or PR merges. Safe defensive reproduction should use the authors’ synthetic LLM/AgentDojo…

Agent Data Injection Attacks are Realistic Threats to AI Agents
Evaluated models: GPT-5.2, GPT-5 Mini, Claude Opus 4.5+3 more
  • GPT-5.2
  • GPT-5 Mini
  • Claude Opus 4.5
  • Claude Sonnet 4.5
  • Gemini 3 Pro
  • Gemini 3 Flash
Application layer
Injection
AI agents
Coding 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.