Dangerous use

Classification

Domain

4. Malicious actors

Subdomain

4.0

Causal entity

Human

Intent

Intentional

Timing

Post-deployment

How other frameworks describe this risk

• Dual-Use Capabilities Enable Malicious Use and Misuse of LLMs

  Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

• Malicious Use Risks

  International Scientific Report on the Safety of Advanced AI (Bengio2024)

• Risks from malicious use

  International AI Safety Report 2025 (Bengio2025)

• Enabling malicious actors and harmful actions

  Navigating the Landscape of AI Ethics and Responsibility (Cunha2023)

• Malicious Use and Unleashing AI Agents

  Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)

• Misuse risks

  Capabilities and Risks from Frontier AI (DSIT2023)

• Malicious Uses

  The Ethics of Advanced AI Assistants (Gabriel2024)

• Fine-tuning related (Ease of reconfiguring GPAI models)

  Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)

Other entries from IBM2025

• - Risk Category
• Lack of training data transparency Risk Sub-Category · 6.5
• Lack of training data transparency Additional evidence
• Uncertain data provenance Risk Sub-Category · 6.5
• Uncertain data provenance Additional evidence
• - Risk Category
• Data usage restrictions Risk Sub-Category · 7.3
• Data usage restrictions Additional evidence
• Data acquisition restrictions Risk Sub-Category · 7.3
• Data acquisition restrictions Additional evidence
• Data transfer restrictions Risk Sub-Category · 7.3
• Data transfer restrictions Additional evidence