LIVE WEBINAR | OCTOBER 13 | 10 AM ET
There’s no benchmark for measuring how good AI is at the actual work of offensive security. There’s no single AI model that’s best at every task, and too many AI-driven OffSec systems that treat safety as an afterthought. These are the gaps that Novee sought to close. In this technical fireside chat with Head of AI Dan Padnos and AI Research Team Lead Or Dancig, you’ll find out how we did it.
Tune in to learn about the techniques we use to train our offensive AI, and how we turned those techniques into a public benchmark for agentic greybox testing. You’ll also hear why offensive work needs many models — including small language models, not one frontier LLM — and why these systems have to be built safety-first.
LIVE WEBINAR | OCTOBER 13 | 10 AM ET
There’s no benchmark for measuring how good AI is at the actual work of offensive security. There’s no single AI model that’s best at every task, and too many AI-driven OffSec systems that treat safety as an afterthought. These are the gaps that Novee sought to close. In this technical fireside chat with Head of AI Dan Padnos and AI Research Team Lead Or Dancig, you’ll find out how we did it.
Tune in to learn about the techniques we use to train our offensive AI, and how we turned those techniques into a public benchmark for agentic greybox testing. You’ll also hear why offensive work needs many models — including small language models, not one frontier LLM — and why these systems have to be built safety-first.
AI Research Team Lead at Novee Security, where he leads model training and post-training to build proprietary AI penetration testing models. Former Operations Research Head of Data Science in the IDF; now builds state-of-the-art synthetic environments and benchmarks to sharpen Novee’s autonomous offensive AI stack.
Always on and self-service – test on demand, no scheduling required.
Finds complex exploit chains and business logic vulnerabilities that scanners and shallow tools miss.
Validates findings with a working exploit and reproducible steps – no false positives, no noise.
Delivers precise remediation based on your architecture and retests automatically.
Continuously map your live environment the way an attacker would – by interacting with real flows, endpoints, and behavior to understand what’s actually exposed.
Test on demand or let Novee fire automatically when code ships.
Understands how your application behaves and tests it for chained attack paths, business logic flaws, authorization gaps, and workflow manipulation that other tools miss.
Context compounds with every cycle, so testing gets deeper, faster, and more targeted over time.
Every finding is independently validated for exploitability, reproducibility, confidence, and real-world impact – complete with working exploits, reproduction steps, and PoC scripts.
Only proven vulnerabilities reach your team.
Get remediation guidance tailored to your specific WAF, backend, frameworks, and infrastructure – or route fixes directly to the AI coding agents your engineering team already uses.
Automatically retests as code changes and environments evolve – learning from each cycle, so testing gets more targeted and effective over time.