We recently helped close a handful of zero-days in CUPS, the default printing system on most Linux distros. Our AI security eval system keeps surfacing real vulnerabilities, with similar findings in Soft Serve and QuickJS a few months ago. Responsibly disclosed (CVE-2026-41079/39314/39316) and patched in v2.4.17.
If you're running CUPS, update it now.
โWeโre aiming to build the next Palo Alto Networks or CrowdStrike.โ
Working with companies like Anthropic and OpenAI, @Irregular was named as Israelโs most promising startup in Calcalist and CTechโs annual Top 50 list.
https://t.co/ZUDnEGX6kH
An AI agent was told only to retrieve a document. When it encountered access restrictions, it reverse-engineered the authentication system, identified a hardcoded secret key, and forged admin credentials to bypass it.
This is one of three scenarios we documented in a new Irregular research report on what we call emergent cyber behavior.
Agents performing routine enterprise tasks autonomously hacked the systems they were operating in. One escalated its own privileges and disabled Windows Defender to complete a file download. Another developed a steganographic encoding scheme to smuggle credentials past a DLP system.
None of this was the product of unsafe system design. It emerged from standard tools, common prompt patterns, and the broad cybersecurity knowledge embedded in frontier models.
Companies that deploy AI agents and do not consider this risk as part of their threat model may end up exposed, and implement insufficient security controls.
Full blog post in the first comment.
New paper: Three frontier models refused a request to leak AWS credentials when malicious intent was stated upfront, but complied with the identical request without it. Same request, different outcome. We propose a 5-dimension framework that grounds refusal in technical content rather than stated intent.
Our AI security evaluation system quietly crossed a line: it began discovering real zero-day vulnerabilities.
We build production-grade ecosystems to study how AI behaves, coordinating agents that attack, defend, and interpret results. As we expanded coverage, our pipeline found real bugs, including two in Soft Serve (CVE-2025-64494, CVE-2025-64522) and a use-after-free in QuickJS (CVE-2025-63998). All disclosed and patched.
Tools built to evaluate AI security are becoming part of the security stack itself. As models grow more autonomous, how we design, operate, and share these pipelines will shape whether they reduce overall risk or amplify it.
@Sequoia's Training Data podcast featuring Irregularโs co-founder/CEO @dan_lahav and @DeanMeyer & @sonyatweetybird from @sequoia just dropped.
This episode dives into the rise of frontier AI security as a critical new discipline, and Irregularโs role in shaping it.
Huge thanks to our partners at @sequoia. Give it a listen๐
My team and I have been working with Irregular for years. Dan and Omer are exceptional. Irregular's talent density is unparalleled.
I am very glad this company is working on some of the biggest/hardest issues in AI security.
Congrats!
Today, we @sequoia are excited to announce back to back rounds led by us and @Redpoint in Irregular
Irregular (what a cool name!) is a frontier AI security lab
They are already working closely with Anthropic, OpenAI and Google Deepmind to secure frontier models