arXiv:2607. 14570v1 Announce Type: new Abstract: AI software development agents are increasingly capable of modifying infrastructure and security critical systems, creating risks where an agent completes its assigned task while covertly weakening safeguards through actions such as broadening permissions, degrading logging, or introducing persistence mechanisms.
By Preeti Ravindra, Rahul Tiwari, Vincent Wolowski
arXiv:2609.39050v1 Announce Type: cross
Abstract: As multi-agent systems enter high-stakes domains, the possibility that agents may circumvent safety boundaries is a growing concern. Prior work has e...
By Deema Alnuhait, Gengyu Wang, Muhammad Khalifa, Hao Peng
arXiv:2607. 20759v1 Announce Type: cross Abstract: AI coding agents powered by LLMs are increasingly integrated into real-world software development, where they generate, edit, and execute code with autonomous access to local files and tools.
By Ankur Singh, Jinqiu Yang, Tse-Hsun Chen
arXiv:2607. 19321v1 Announce Type: new Abstract: As AI agents begin to automate AI R&D, we need ways to assess whether their outputs are safe to deploy, even when the agents themselves may be untrusted.
By Lena Libon, Ben Rank, Jehyeok Yeon, David Schmotz, Jeremy Qin, Daniel Donnelly, Derck Prinzhorn, Maksym Andriushchenko
arXiv:2609.14796v1 Announce Type: new
Abstract: The threat that AI persuasion poses to human control has been acknowledged in the literature, but not yet systematically studied. Now that persuasion a...
By Joshua Levy, Mick Yang, Kellin Pelrine
arXiv:2607. 03215v1 Announce Type: cross Abstract: Artificial intelligence has spread across the whole of the security lifecycle.
By Mohamed Chahine Ghanem
arXiv:2606. 13994v1 Announce Type: cross Abstract: LLM-based Agents are becoming increasingly capable and widely deployed, creating growing incentives for adversarial misuse in the real-world.
By Vikhyath Kothamasu, Virginia Smith, Chhavi Yadav
arXiv:2607. 05743v1 Announce Type: cross Abstract: AI coding agents now read repositories, call tools, and execute shell commands with limited human oversight, and a fast-growing body of work studies whether the execution layer around them is actually safe.
By Mohammadreza Rashidi
arXiv:2606.00341v2 Announce Type: replace-cross
Abstract: As AI agents are increasingly deployed in real personal and corporate settings (email accounts, development workflows, company databases, etc...
By Jeremy Tien, Abishek Anand, Yu-Rou Tuan, Yuchen Shen, J. Zico Kolter, Aran Nayebi
arXiv:2602.20628v2 Announce Type: replace
Abstract: AIs are increasingly being deployed with greater autonomy and capabilities, which increases the risk that a misaligned AI may be able to cause cata...
By Nelson Gardner-Challis, Jonathan Bostock, Georgiy Kozhevnikov, Morgan Sinclaire, Joan Velja, Alessandro Abate, Charlie Griffin
arXiv:2606. 08892v1 Announce Type: new Abstract: AI models deployed in critical domains, such as AI safety research, may subtly sabotage our efforts due to misalignment.
By Mikhail Terekhov, Caglar Gulcehre, Vivek Hebbar, Joe Benton
arXiv:2607. 02389v1 Announce Type: new Abstract: Coding agents are capable; human oversight is the bottleneck.
By Thomas Winninger