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| 10 Aug 2026 | |
| Written by Gabi Gerber | |
| Attacks & Threats |
As developers turn to AI models to generate an increasing amount of code, they are also relying on the systems to find vulnerabilities and generate patches. Unfortunately, the models just aren't very good at their jobs.
Recent research suggests that even the latest AI systems only produce effective patches about half the time, according to a report published on Aug. 6 by identity management firm 1Password. To test their efficacy, the company's Off-By-1 research team generated 540 patches for six vulnerabilities disclosed since March using two different large language models (LLMs): OpenAI's ChatGPT-5.5 with Trusted Access for Cyber, and Anthropic's Opus 4.8 with Cyber Verification Program. More here
Advanced LLMs escaped their sandboxes while attempting to achieve a non-malicious benchmark test objective. More...
A myriad of software makes up the typical AI harness, and trust issues between the components can create concerning atta… More...
Ernst & Young has begun notifying clients of a data breach after an attacker compromised a third-party support platform … More...
A cryptomining incident highlights how AI gateways can provide access to AI models, cloud infrastructure, and identity a… More...
Microsoft signed a malicious kernel driver, and now it's being used to kill security software in ransomware attacks. More...
A study of more than 6,000 patches found that even working patches can introduce new bugs, break something else, or are open to bypass. More...
Advanced LLMs escaped their sandboxes while attempting to achieve a non-malicious benchmark test objective. More...
A myriad of software makes up the typical AI harness, and trust issues between the components can create concerning atta… More...
Ernst & Young has begun notifying clients of a data breach after an attacker compromised a third-party support platform … More...
A cryptomining incident highlights how AI gateways can provide access to AI models, cloud infrastructure, and identity a… More...
