Vahe Martirosyan

The gap between theoretical security and operational reality is where breaches occur. Traditional security assessments often test against outdated attack patterns or synthetic scenarios that bear little resemblance to actual threat actor behavior. True adversary emulation requires a fundamentally different approach—one that prioritizes realism while maintaining ethical and legal boundaries.

Autonomous AI agents operating in security contexts present a unique safety challenge. Unlike chatbots where the worst case is inappropriate text output, security agents have the capability to cause real-world impact—both intended (validating defenses) and unintended (service disruption, data exposure). Establishing robust safety boundaries requires engineering discipline that goes beyond typical AI safety practices.

Security monitoring systems that can be tampered with provide only an illusion of visibility. High-assurance logging requires treating the logging infrastructure itself as a critical security control, with integrity guarantees that hold even when attackers have compromised other parts of the environment.