MIT AI Risk Repository
Browse AI risks
3 risk entries extracted from 74 frameworks, coded by domain, subdomain, causal entity, intent and timing. Filter, then export the current selection with its licence and citation attached.
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"AI-enabled cyber offense poses a significant cyber domain security risk by fundamentally transforming the scale, sophistication, and accessibility of cyber-attacks. Unlike traditional cyber threats, AI enables both the automation of existing attack vectors and the creation of entirely new categories of offensive capabilities that can adapt and evolve in real-time. AI can automate and enhance cyber-attacks, including vulnerability discovery and exploitation, password cracking, malicious code generation, sophisticated phishing, network scanning, and social engineering. This could dramatically l
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"The dual-use nature of AI technology presents a critical risk by significantly lowering technical thresholds for malicious non-state actors to design, synthesize, acquire, and deploy CBRNE (Chemical, Biological, Radiological, Nuclear, and Explosive) weapons. This capability poses unprecedented challenges to national security, international non-proliferation regimes, and global security governance."
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"The integration of general-purpose AI models into embodied systems creates direct physical threats through malicious exploitation of autonomous decision-making capabilities in real-world environments. The risk lies in embodied models' capacity for autonomous action and real-world interaction, and when these capabilities are maliciously exploited they may trigger a series of serious consequences.18"
Disclaimer: informational only, not legal advice. Verify every claim against the linked official sources and consult a qualified lawyer before acting.
Frequently asked questions
Where do these risk entries come from?
The MIT AI Risk Repository, which extracts risks from dozens of published frameworks, taxonomies and papers and codes each one by domain and subdomain, and by a causal taxonomy of entity, intent and timing. This is a browseable copy, attributed and openly licensed, not original research.
What do entity, intent and timing mean?
They are the causal coding. Entity is whether a human or the AI system is the cause; intent is whether the harm was intentional or not; timing is whether it arises before or after deployment. Together they let you separate misuse from malfunction.
Can I export the results?
Yes, any filtered set exports as CSV or JSON, and every export carries the upstream source, licence and citation with it, because attribution is a condition of the licence rather than a courtesy.
What is the MIT AI Risk Repository?
A living database of AI risks extracted from published frameworks, taxonomies and papers, classified by a causal taxonomy of entity, intent and timing and by a domain taxonomy of seven domains and 24 subdomains. It is published by the MIT AI Risk Initiative under CC BY 4.0.