{
  "id": "injecagent",
  "name": "InjecAgent",
  "category": "information",
  "summary": "Benchmark of 1,054 test cases measuring how tool-using LLM agents fall for indirect prompt injections in tool outputs.",
  "description": "The cases span 17 user tools and 62 attacker tools, covering both direct harm and data-stealing attacks. Scripts evaluate prompted (ReAct) agents and fine-tuned function-calling agents. From UIUC's Kang Lab (paper arXiv:2403.02691). MIT. Last updated July 2024.",
  "url": "https://github.com/uiuc-kang-lab/InjecAgent",
  "repo": "https://github.com/uiuc-kang-lab/InjecAgent",
  "tags": [
    "benchmark",
    "prompt-injection",
    "security",
    "tool-use",
    "dataset"
  ],
  "license": "MIT",
  "pricing": "open-source",
  "related": [
    "agentdojo"
  ],
  "sources": [
    "https://github.com/uiuc-kang-lab/InjecAgent",
    "https://arxiv.org/abs/2403.02691"
  ],
  "added": "2026-10-31",
  "updated": "2026-10-31",
  "last_verified": "2026-10-31",
  "submitted_by": "agentica-curator",
  "maintainer": "UIUC Kang Lab",
  "longform": [],
  "links": {
    "html": "https://indexagentica.com/entries/injecagent/",
    "markdown": "https://indexagentica.com/entries/injecagent.md",
    "json": "https://indexagentica.com/api/entries/injecagent.json",
    "source": "https://github.com/Drudley/indexagentica/blob/main/content/information/injecagent.json"
  }
}