Facilitation of weapons, CBRN and serious physical harm (capability uplift)
The system lowers barriers to chemical, biological, radiological, nuclear, explosive or other weapons and dangerous activities by providing actionable how-to information or uplift.
- Risk family
- Model & system behaviour
- MIT domain
- 4. Malicious Actors & Misuse
- MIT subdomain
- 4.2 > Cyberattacks, weapon development or use, and mass harm
- AI type
- GPAI, Agentic
- Scope
- System
- Source standard
- MIT AI Risk Repository v4
Provenance
41 entries across 23 papers
- Abercrombie2024A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms58.07.15
- Anwar2024Foundational Challenges in Assuring Alignment and Safety of Large Language Models73.03.05
- Bengio2025International AI Safety Report 202560.01.04
- Chin2025Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks68.01.00
- Clarke2023A Survey of the Potential Long-term Impacts of AI: How AI Could Lead to Long-term Changes in Science, Cooperation, Power, Epistemics and Values55.02.01
- DSIT2023Capabilities and Risks from Frontier AI67.03.00 67.03.01
- G'sell2024Regulating under Uncertainty: Governance Options for Generative AI47.02.03
- Gabriel2024The Ethics of Advanced AI Assistants24.03.06
- Ghosh2024AILUMINATE: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons57.01.04
- Gipiškis2024Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems62.05.00 62.08.06 62.29.02 62.33.01 62.33.02
- Hendrycks2022X-Risk Analysis for AI Research35.01.00
- Hendrycks2023An Overview of Catastrophic AI Risks22.01.01
- InfoComm2023Cataloguing LLM Evaluations43.02.02 43.02.06
- Maas2023Advancing AI Governance: A Literature Review of Problems, Options, and Proposals53.03.06
- Maham2023Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks52.02.00 52.02.02
- NIST2024Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile48.01.00
- Shevlane2023Model Evaluation for Extreme Risks25.05.00
- Tang2025Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy71.01.01 71.01.02 71.01.03
- TC2602024AI Safety Governance Framework45.02.08
- Tse2025Frontier AI Risk Management Framework (v1.0)72.01.02 72.05.11
- Uuk2025A Taxonomy of Systemic Risks from General-Purpose AI61.01.13 61.02.02
- Vidgen2024Introducing v0.5 of the AI Safety Benchmark from MLCommons23.02.06 23.05.00 23.05.01 23.05.02 23.05.03 23.05.04 23.05.05 23.05.06
- Weidinger2023Sociotechnical Safety Evaluation of Generative AI Systems18.04.04
Ev IDs of the entries consolidated into this risk in the MIT AI Risk Repository (V4); the source sheet row appears on hover.
Framework crosswalk
Every framework item mapped to this risk. Items marked partial overlap only in part; definitions appear on hover where the source licence permits.
1- A.10 ISO/IEC 23894 Annex A A.10
2- A.5.5 ISO/IEC 42001 Annex A A.5.5
- A.9.4 ISO/IEC 42001 Annex A A.9.4
1- AISubtech-15.1.18 Safety Harms and Toxicity: Weapons / CBRN Risks
1- GENAI.1 CBRN Information or Capabilities
More in Model & system behaviour
Part of the Deployer AI Risk Register, an open-source resource powered by MindXO. Version 1.0, 3 July 2026. Derived from the MIT AI Risk Repository (V4, December 2025) under CC BY 4.0; an independent derivative work, not endorsed by or affiliated with MIT. Sub-risk decomposition references MITRE ATLAS™ v5.6.0 (© 2021-2026 The MITRE Corporation, reproduced and distributed with permission). ISO/IEC and EU AI Act references are by number only. License: CC BY 4.0. Full attribution and licensing.