At @ManGroup's Technology Offsite this week, our CEO @dan_lahav gave the keynote on frontier AI security risk as a category of its own, alongside classical cybersecurity.
The tools we defend networks with were built for systems that follow rules. AI systems reason toward a goal,
Most 'world-changing' AI ideas are about what these systems can do. Ours is about whether you can trust them to do it. We’re proud to be a winner on @FastCompany’s 2026 World Changing Ideas list, alongside the labs and teams betting on getting this right.
We’re happy to share that CyScenarioBench, our benchmark for offensive cyber operations, was used by @AnthropicAI to test Claude Mythos 5 and Claude Fable 5.
Most current cybersecurity evaluations check isolated skills, such as vulnerability research or exploitation.
The New York Times covered new research from the University of Toronto on AI-powered worms.
Speaking to @nytimes, our CEO @dan_lahav highlighted the gap between lab demonstrations and real-world cyber impact: reliability, complexity, and defenses.
At Irregular, we work on
Honored to be the main sponsor of CyberML 2026, a leading technical conference dedicated to the intersection of cybersecurity and machine learning. Our co-founder and CTO, Omer Nevo, opens with the keynote "Artificial Attackers: Risks, Capabilities and Mitigations.”
Swing by our
Thrilled to be recognized in @Redpoint's 2026 InfraRed 100, highlighting 100 of the most promising private companies in AI infrastructure.
This recognition is a powerful validation of our mission: to protect the world as AI systems become increasingly capable and sophisticated.
Last week, Irregular brought together CISOs and CIOs from more than 20 Fortune 500 enterprises in New York for a closed-door workshop on AI security. The sessions mapped directly to what these executives are facing as agents move into production, informed by weeks of private
Our CEO, @dan_lahav, spoke at @jpmorgan's Global Cyber Innovation Summit in NYC about cybersecurity in the era of frontier AI, exploring how AI systems fail and how to build trust where traditional security tools fall short.
A timely conversation for a fast-moving field.
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
We evaluated GPT-5.5 before release, testing cyber capabilities across our private benchmark suites. We found clear gains over GPT-5.4: stronger performance at lower costs.
As models become more capable, understanding and reducing their security risks becomes increasingly
Introducing GPT-5.5
A new class of intelligence for real work and powering agents, built to understand complex goals, use tools, check its work, and carry more tasks through to completion. It marks a new way of getting computer work done.
Now available in ChatGPT and Codex.
We evaluated GPT-5.5 using Irregular’s offensive security methodology across two frameworks: Atomic Tasks, which tests discrete technical skills, and CyScenarioBench, which tests end-to-end, multi-stage operations. On Atomic Tasks, the model performed strongly, particularly in
“We’re aiming to build the next Palo Alto Networks or CrowdStrike.”
Working with companies like Anthropic and OpenAI, @Irregular was named as Israel’s most promising startup in Calcalist and CTech’s annual Top 50 list.