mlsanityData to 14 Oct 2026

The Agent Incident Registry: Toward Preventing Repeated AI Agent Failures

arXiv 2609.11030 ↗First posted 10 Sep 2026cs.AIcited by 2

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Abstract (arXiv)

AI agents increasingly act through tools and delegated authority, but general incident repositories rarely capture the mechanisms needed to compare public failures with agent-security evaluations. We present the Agent Incident Registry (AIR) (Project page: https://enkryptai.com/air), a source-linked catalog containing 487 records of agent-related events disclosed from 2022 through 2026. Each record includes supporting evidence, a stable identifier, and missingness-aware labels for causal role, disclosure class, mechanism, and outcome. Among the 336 generative-system records in which the agent acted, 81 involved realized harm (24%). Realized outcomes concentrate in in-the-wild and safety-failure records, while responsible disclosures and research demonstrations are overwhelmingly demonstrated; the aggregate share therefore characterizes collection composition rather than deployment risk. After initial curation, a second human reviewer checked all 487 records and their existing labels for completeness and correctness. In a deployment-analogue audit, InjecAgent's 1,054 cases occupy three of AIR's twelve surfaces and are all attacker-triggered, whereas AIR contains 92 no-adversary safety failures. AIR supports source-grounded case retrieval and evaluation-scope auditing, not failure-rate or control-efficacy estimation.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 11 of its 28 references that are in the map. First posted on arXiv 10 Sep 2026.

Builds on

11 of 28 references.

References · 11

  1. 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injectioncited by 1,443
  2. 2018Datasheets for Datasetscited by 1,386
  3. 2024InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agentscited by 538
  4. 2024AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agentscited by 437
  5. 2024Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agentscited by 369
  6. 2020Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Databasecited by 96
  7. 2025EchoLeak: The First Real-World Zero-Click Prompt Injection Exploit in a Production LLM Systemcited by 29
  8. 2024The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligencecited by 16
  9. 2024SAGE-RT: Synthetic Alignment data Generation for Safety Evaluation and Red Teamingcited by 10
  10. 2022A taxonomic system for failure cause analysis of open source AI incidentscited by 9
  11. 2026Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discoverycited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.