Safety & Security

Artificial intelligence safety and security encompasses the technical and policy measures used to mitigate model risks, vulnerabilities, abuse and failures. Truncated covers research developments, threat analyses, defense mechanisms and policy discussions related to reliable deployment.

Tuesday 3 November

Vibe Coded AO3 Clone Site Down After Fanfic Authors Buried It With 2,000 Takedown Notices in a Single Day

AI-generated summary According to reports, a fanfiction clone site scraped Archive of Our Own and charged for audiobook versions before shutting down after receiving over 2,000 takedown requests. The archive repository Archive of Our Own remains offline following a security incident while authors express concern over unauthorized scraping and monetization of their works.

What is memory poisoning and who is at risk?

Cyber attacks concept image showing a red-colored warning symbol hovering above a laptop used by man in dark room.

AI-generated summary Security researchers have released details about a technique known as memory poisoning, which allows attackers to inject malicious or misleading memory items into an artificial intelligence assistant's persistent memory layer. Forcepoint states that the aim of these attacks is to trick artificial intelligence agents into producing false information, creating a persistent risk that can repeatedly output flawed data across future sessions.

Monday 2 November

Preparing our next security sprint to harden OpenAI

AI-generated summary OpenAI announced plans for its next internal security sprint, partnering with Cathedral Systems to test defenses and quadrupling rewards for critical findings in its Security Bug Bounty program. OpenAI says the initiative builds on previous efforts where engineers used Codex to investigate findings and prepare patches as part of an ongoing effort to strengthen systems.

Also covered by Cyber Security News Interesting Engineering The Decoder

Accent bias: AI models penalize certain speakers in interviews and tests, UW study finds

AI-generated summary University of Washington researchers released a new study showing that AI models from Google, OpenAI and Alibaba penalize speakers with Nigerian and Chinese accents during interviews and tests. The study indicates that the models generally ranked American and British speakers highest while giving lower scores to Chinese and Nigerian speakers based on their delivery and perceived clarity.

Also covered by Tech Xplore