SE Radio 733: Max Corbridge on Securing AI Agents
Software Engineering Radio - the podcast for professional software developersShow Notes
Max Corbridge, an ethical hacker and red teamer who is co-founder and CEO of Secure Agentics, speaks with SE Radio host Amey Ambade about how AI agents get attacked and what engineers can actually do to defend them. Drawing on years of offensive security work, Corbridge frames agents as a new and largely undefended attack surface: the industry has handed AI systems autonomy and the ability to act in the real world while carrying forward prompt injection, a flaw the frontier labs themselves describe as effectively unsolvable. He likens the moment to the early, lawless days of the web, when SQL injection was everywhere and adoption ran far ahead of security. The conversation builds from first principles as Corbridge explains what separates an agent from ordinary software and why three properties make them hard to secure: they are non-deterministic, their language-model core can be coerced, and they are increasingly interconnected through MCP servers, other agents, databases, and email. Turning to the attack surface, Corbridge lays out his "lethal trifecta" (a vulnerable core, dense interconnection, and security tooling that has not caught up) and contrasts the decades of layered defenses protecting an ordinary email inbox with the thin protection around agents that take autonomous actions on critical systems. The heart of the episode is defense. Corbridge orders practices by leverage: least-privilege access and privilege separation, sandboxing where feasible, imperfect-but-useful guardrails as one layer of defense in depth, and human-in-the-loop for irreversible actions (which he notes is contentious and does not scale). The discussion closes on detecting a compromised or drifting agent, the value of watching an agent's chain-of-thought reasoning alongside its actions, the open-source tooling landscape (including Corbridge's own project, Adrian), and his central advice: build security in proactively, define what good agent behavior looks like up front, and avoid bolting it on after agents have already spread across the business.
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