Secure AI Weekly

220 Results / Page 1 of 25

todayDecember 4, 2024

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Towards Secure AI Week 48 – Biggest AI Security Bug Bounty

Artificial Intelligence Vulnerability Scoring System (AIVSS) GitHub The AI Vulnerability Scoring System (AIVSS) has been proposed as a framework designed to evaluate vulnerabilities in AI systems comprehensively. Unlike static models, AIVSS incorporates dynamic metrics tailored to AI, including model robustness, data sensitivity, ethical impact, and adaptability, alongside traditional security considerations. ...

todayNovember 18, 2024

  • 46
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Towards Secure AI Week 46 – Hacking LLM Robots

It’s Surprisingly Easy to Jailbreak LLM-Driven Robots Researchers induced bots to ignore their safeguards without exception IEEE Spectrum, November 11, 2024 The rapid integration of large language models (LLMs) like ChatGPT into robotics has revolutionized how robots interact with humans, offering capabilities such as voice-activated commands and task execution based ...

todayNovember 12, 2024

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Towards Secure AI Week 45 – AI Safety Through Testing, Legislation, and Talent Building

Microsoft’s Yonatan Zunger on Red Teaming Generative AI The Cyber Wire, November 6, 2024 In a recent Microsoft Threat Intelligence Podcast episode, host Sherrod DeGrippo speaks with Yonatan Zunger, Corporate Vice President of AI Safety and Security at Microsoft, to explore the critical importance of securing AI systems. The conversation ...

todayNovember 6, 2024

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Towards Secure AI Week 44 – From Open-Source AI Risks to National Policies

Researchers Uncover Vulnerabilities in Open-Source AI and ML Models The Hacker News, October 29, 2024 Recent disclosures have highlighted over thirty security vulnerabilities within various open-source artificial intelligence (AI) and machine learning (ML) models, some of which could allow for remote code execution and unauthorized data access. Key flaws have ...

todayOctober 23, 2024

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Towards Secure AI Week 42 – New Jailbreaks and Incidents

LLMs are easier to jailbreak using keywords from marginalized groups, study finds The Decoder, October 20, 2024 A recent study highlights unintended vulnerabilities in the safety protocols of large language models (LLMs), revealing that well-meaning ethical measures can introduce security gaps. Researchers found that the ease with which these models ...