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AI security threats move fast and get buried under hype and noise. Built by an Information Systems Security researcher to help security teams and developers stay ahead of vulnerabilities, privacy incidents, safety research, and policy developments.
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Comprehensive Survey Maps AI Auditing Landscape: A new academic survey consolidates existing frameworks, principles, and methodologies used to audit AI systems for safety, fairness, and reliability, providing practitioners with a structured overview of current evaluation approaches.
AIUC, a new company founded in 2024, raised $40 million to expand its AI certification standard called AIUC-1, which evaluates enterprise AI agents (AI systems that can perform tasks independently) for security risks like jailbreaks (breaking an AI's safety rules), hallucinations (when an AI confidently generates false information), prompt injections (tricking an AI by hiding instructions in its input), and data leaks. The standard tests AI models against about 5,000 adversarial risk scenarios (simulated attacks designed to find weaknesses) and conducts quarterly audits to catch new threats.