MIT AI Risk Repository · Risk Sub-Category · 17.04.03
Assisting code generation for cyber attacks, weapons, or malicious use
Category: Malicious Uses
Description
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From Ethical and social risks of harm from language models (Weidinger2021), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Domain
- 4. Malicious actors
- Causal entity
- Human
- Intent
- Intentional
- Timing
- Post-deployment
Subdomain definition: Using AI systems to develop cyber weapons (e.g., coding cheaper, more effective malware), develop new or enhance existing weapons (e.g., Lethal Autonomous Weapons or CBRNE), or use weapons to cause mass harm.
Real-world incidents in this subdomain
- Anthropic's Claude Was Reportedly Jailbroken To Allegedly Help Steal Sensitive Mexican Government Data
- OpenAI ChatGPT Models Reportedly Jailbroken to Provide Chemical, Biological, and Nuclear Weapons Instructions
- Anthropic Reportedly Identifies AI Misuse in Extortion Campaigns, North Korean IT Schemes, and Ransomware Sales
- LAMEHUG Malware Reportedly Integrates Large Language Model for Real-Time Command Generation in a Purported APT28-Linked Cyberattack
- Reported AI-Aided Development of Explosive Devices by Long Island Resident Michael Gann
- AI Chatbot Allegedly Used to Research Explosive Materials in Palm Springs Fertility Clinic Bombing
How other frameworks describe this risk
Other entries from Weidinger2021
- Discrimination, Exclusion and Toxicity
- Social stereotypes and unfair discrmination
- Social stereotypes and unfair discrmination
- Exclusionary norms
- Exclusionary norms
- Exclusionary norms
- Exclusionary norms
- Toxic language
- Lower performance for some languages and social groups
- Lower performance for some languages and social groups
- Information Hazards
- Compromising privacy by leaking private infiormation