AI-system security
Adversarial inputs and vulnerable integrations can undermine an AI application’s intended behavior.
READING ROOM ↗Risks, incidents and research in context. An independent, curated map of AI’s human consequences.
A small historical collection, maintained editorially. Not exhaustive, not a live feed, and not a ranking of dangerous companies or models. Most recent record review: 2026-10-07.
Adversarial inputs and vulnerable integrations can undermine an AI application’s intended behavior.
An incorrect identity match can become a harmful human decision.
Collecting and using personal data creates questions about purpose, access and retention.
Confirmed occurrence and attributed allegations carry different labels. These historical examples do not measure incident frequency.
The FCC documented a campaign using a cloned presidential voice and misleading caller identification.
A regulator complaint describes harmful false matches in a retail surveillance deployment.
A historical developer account of capabilities and limitations at launch.
Voluntary guidance connecting governance, context, measurement and management of AI risks.
A companion resource for applying AI risk-management guidance to generative systems.
The original adopted text of Regulation (EU) 2024/1689, connected to its risk-related provisions.
A historical model record tied to its original research announcement.