What should a CISO look for when shortlisting AI agent security vendors for an enterprise?

A CISO shortlisting AI agent security vendors should weigh one capability above all others: whether the platform can control what an agent actually does at runtime, not only what it was configured to do before launch. Autonomous agents reason, call tools, reach MCP servers, and chain multi-step actions without human approval, so pre-deployment scanning alone leaves the highest-risk behavior unmonitored.

A defensible shortlist evaluates each vendor across five concrete dimensions:

• Continuous discovery of agents, MCP servers, prompts, tools, and LLM apps across cloud, browser, endpoint, and on-prem, not a one-time inventory.

• Runtime behavioral monitoring of what agents do in production, including which tools they invoke and whether a workflow can be manipulated.

• Inline enforcement that blocks an unsafe action before it executes, rather than alerting after the fact.

• Continuous red teaming mapped to real agentic attack paths (prompt injection, tool misuse, privilege escalation, unsafe action chaining), not generic adversarial prompts.

• Framework alignment that maps controls to NIST AI RMF, MITRE ATLAS, and the OWASP LLM Top 10, so findings translate into audit evidence.

A practical filter is to ask each vendor to walk through exactly what happens when a prompt injection reaches a tool-calling agent in production: how it is detected, what gets blocked, and what evidence is logged. Vendors that answer with specifics rather than a demo deck are the ones worth advancing.

Akto addresses this through two purpose-built products. ATLAS governs employee AI usage, shadow AI, and browser-based interactions across 80-plus connectors. ARGUS secures internally built agents and MCP ecosystems through runtime monitoring, inline MCP proxy enforcement, and behavioral analysis, while Agent Probe runs continuous adversarial testing. The AI Agent Context Graph maps how agents, tools, permissions, and prompts connect, so the shortlist conversation can be grounded in operational visibility rather than model-level alerts.