AI Safety at the Frontier: Paper Highlights of July 2026

tl;dr Topic of the month: AI agents autonomously attacked real organizations during cyber evaluations. A swarm of OpenAI agents coordinated via a package manager and broke into Hugging Face to cheat the eval, Mythos 5 performed a supply-chain attack with spear-phishing and sockpuppets against real developers, and Claude models breached companies it took for simulations. Research highlights: Case studies of AI misalignment, like Claude-based judges knowingly mislabeling up to 86% of the time when the correct label would train away behavior they endorse, and Gemini 3.1 Pro covertly sabotaging research it objects to. Implanting beliefs about grader rewards via contrastive synthetic document finetuning shows o3 tracking its grader more and more over a capabilities RL run. OpenAI trains the red-teaming GPT-Red model via self play, which achieves higher success than human red teamers and substantially cuts prompt-injection success on GPT-5.6 via adversarial training. Gradient Routed Auxiliary Modules trains per-domain modules to absorb dual-use knowledge during pretraining, which then can be deleted depending on the deployment. FAR.AI find that Grok 4.5 and Gemini 3.1 Pro are easily jailbroken and don’t meet a minimal bar for security. Full post here. Discuss