Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Autonomous AI agents execute tasks at machine speed, but they cannot take legal or operational accountability when code introduces security risks. Asaf Saar (EVP and Chief Product Officer, Mend.io) and Christian Jensen (VP Engineering, Tricentis) explain why human governance remains vital.

If your AI security strategy is focused on stopping copy-pastes into chatbots, you're fighting yesterday's war. AI agent security is now the real endpoint challenge — autonomous agents operating with your users' credentials. Traditional firewalls, CASBs, and DLP weren't built for agentic AI. They can't see delegated credentials, multi-step tool calls, or live runtime execution across IDEs, browsers, and local apps.

Your backlog of low and medium severity vulnerabilities just became a real threat. AI can now chain them into critical exploits, and the window between exploit discovery and active use is around eight hours. Curtis Koenig, Head of Application Security at Gen, joins the show to explain why treating AI agents like human users is the single most important step security teams can take this year. CHAPTERS.

The window between an exploit being discovered and actively used is around eight hours. Curtis Koenig, Head of Application Security at Gen, explains why zero trust and a prepared incident response process remain the foundation for security teams navigating this new threat landscape. "The good news is that if the tool can find a vulnerability and create an exploit, it can find a vulnerability and write a patch as well.".

Attackers targeting open source dependencies already have all the code they need. Curtis Koenig, Head of Application Security at Gen, explains the fundamental asymmetry and why building quality fixes at speed is the real challenge for defenders. "An attacker can produce very fast, very ugly code that propagates through as an attack. When we're trying to fix something, the challenge we have is we're always trying to build for quality.".

AI agents are about to act as humans inside your organization. Curtis Koenig, Head of Application Security at Gen, explains why treating them with the same identity and data controls is the single most important step to get ahead of AI risk. "We're going to give these agents the capability to do things as though they were humans. If we are not treating them like we treat our other human users in our organizations, that's where we're creating risk.".

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Point an AI model at a security stack it doesn't fully understand and you get confident, wrong answers faster. Reach gives your AI a source of truth for security controls. The MCP Server connects MCP-compatible AI tools directly to Reach. The Public API brings Reach findings and evidence into SIEM, ticketing, and GRC workflows. The MCP Server is intentionally read-only, so your team decides when recommendations become actions.