17 papers
Running the Gauntlet: Re-evaluating the Capabilities of Agents Beyond Familiar Environments
Mykola Vysotskyi, Runqi Lin, Grzegorz Biziel +22
As agentic systems continue to evolve and are widely deployed in real-world scenarios, there is a growing demand to faithfully evaluate their capabilities. However, current benchma…
Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community
Lin Li, Qi Zhang, Xander Davies +2
AI is increasingly used to support scientific peer review, from manuscript screening, reviewer assistance to editorial triage. Although such systems promise to reduce reviewer burd…
Evaluating whether AI models would sabotage AI safety research
Robert Kirk, Alexandra Souly, Kai Fronsdal +2
We evaluate the propensity of frontier models to sabotage or refuse to assist with safety research when deployed as AI research agents within a frontier AI company. We apply two co…
UK AISI Alignment Evaluation Case-Study
Alexandra Souly, Robert Kirk, Jacob Merizian +2
This technical report presents methods developed by the UK AI Security Institute for assessing whether advanced AI systems reliably follow intended goals. Specifically, we evaluate…
How Vulnerable Are AI Agents to Indirect Prompt Injections? Insights from a Large-Scale Public Competition
Mateusz Dziemian, Maxwell Lin, Xiaohan Fu +28
LLM based agents are increasingly deployed in high stakes settings where they process external data sources such as emails, documents, and code repositories. This creates exposure…
Breaking Agent Backbones: Evaluating the Security of Backbone LLMs in AI Agents
Julia Bazinska, Max Mathys, Francesco Casucci +4
AI agents powered by large language models (LLMs) are being deployed at scale, yet we lack a systematic understanding of how the choice of backbone LLM affects agent security. The…