Cequence Security has brought attention to a critical shift in the AI security landscape, focusing on the behavior of AI agents over simple access control.
A consensus is forming among key players in the field, including Anthropic, Dr. Chase Cunningham, and Cequence Security, who all agree that the most significant risk with AI agents lies not in access but in their actions once inside a system.
Convergence on Agent Behavior Security
Anthropic's new frameworks, Dr. Cunningham's research on Agentic Zero Trust, and Cequence Security’s AI Gateway architecture stress the importance of managing agent behavior instead of just relying on authentication.
Traditional security mechanisms are centered on access control but do not adequately address the potential misuse of legitimate access by AI agents to perform damaging actions, manipulate APIs, or exfiltrate data. Cequence’s AI Gateway steps in to fill this gap by applying zero trust principles to scrutinize agent actions as well as identities.
Industry Perspectives and Expert Insights
Shreyans Mehta, CTO of Cequence Security, emphasized the industry's pivot towards securing agent behavior, stating, "Most security teams are still trying to tackle AI risk with prompt detection and short-lived tokens – basically, really tight sign-in security. But that misses the point entirely. You can nail authentication and still get burned by an agent running amok inside the castle.”
His sentiments are shared by Dr. Chase Cunningham, a prominent figure in zero trust security, who noted that "You have to extend zero trust inside, to cover not just authentication, but every action an agent takes."
Behavioral Monitoring and Real-Time Policy Enforcement
The focus on runtime behavior centers on intercepting, analyzing, and controlling AI agent actionsThe focus on runtime behavior emphasizes intercepting, analyzing, and controlling what AI agents can do, leveraging policy enforcement and threat detection throughout all interactions. This shift reframes AI security from focusing solely on identity to a broader view of agent actions.
Real-time behavioral monitoring is crucial, as AI agents can combine innocuous actions into harmful sequences that evade static defenses.
Integrating CIS Controls for AI Security
This approach aligns with the Center for Internet Security (CIS) and Cequence’s recent guidance, which integrates the Model Context Protocol (MCP) to regulate AI agent behavior.
The CIS MCP Companion Guide, published on April 20, 2026, outlines necessary controls for managing AI interactions with enterprise systems. Cequence Security has operationalized these recommendations through its AI Gateway, ensuring dynamic permissions and auditing.
Immediate Need for Advanced AI Security
With AI agents becoming central to production environments, they now frequently interact with sensitive data and critical systems. The potential for AI-driven threats has accelerated, necessitating real-time threat detection and prevention.
Cequence Security’s AI Gateway addresses these issues by continuously monitoring API calls and data flows, enabling immediate intervention against suspicious agent activities.
Cequence Security, the pioneer in application, API, and Agentic AI protection, highlighted a significant convergence in the AI security industry.
In a striking show of consensus, three leading voices in AI security, Anthropic, Dr. Chase Cunningham, and Cequence Security, have independently converged on a shared conviction: the biggest risk with AI agents isn’t access, it’s what they do once they’re in.
Anthropic’s recently published frameworks, Dr. Cunningham’s Agentic Zero Trust research, and Cequence’s AI Gateway architecture all emphasize the need to focus security efforts on controlling agent behavior, not just authentication.
Cequence’s AI Gateway
The key insight driving this convergence is that conventional security tools fixate on the login action, but for AI agents that can think, act, and cause damage autonomously, that’s guarding the wrong door. The real risk is an agent misusing legitimate access to take harmful actions, manipulate APIs, or exfiltrate data.
That’s the security gap Cequence’s AI Gateway was purpose-built to close, by extending zero trust principles to cover not just who the agent is, but what it does.
Ultimate validation
"Most security teams are still trying to tackle AI risk with prompt detection and short-lived tokens – basically, really tight sign-in security. But that misses the point entirely. You can nail authentication and still get burned by an agent running amok inside the castle,” said Shreyans Mehta, CTO at Cequence Security.
“Anthropic, Dr. Cunningham and Cequence all recognized early on that the gamechanger is securing agent behavior. Seeing the whole industry pivot hard toward that truth, toward the approach we baked into the AI Gateway from day one, is the ultimate validation. It crowns the AI Gateway as the new reference architecture for the space.”
Zero trust security expert
"Traditional security controls focus obsessively on the front gate – who gets in. But with AI agents, the real damage happens after the front gate, through totally authorized channels," said Dr. Chase Cunningham, a leading expert on Zero Trust security. "You have to extend zero trust inside, to cover not just authentication, but every action an agent takes. Cequence’s AI Gateway is a huge leap toward that goal, toward getting zero trust to fully cover the AI agent threat model.”
The behavior convergence
Anthropic's published frameworks, Dr. Cunningham’s research, and Cequence’s AI Gateway all recognize that for AI agents, authentication is necessary but nowhere near sufficient. Their core focus is on runtime behavior: intercept, analyze, and tightly control what each agent is allowed to do, with what resources, in what context, with policy enforcement and threat detection at every step of every transaction. It’s a fundamental reframing of the AI security problem around agent actions, not agent identity.
They also agree that behavioral monitoring and policy enforcement have to be dynamic and real-time, because AI agents can chain together individually legitimate steps into harmful patterns too complex to predict in advance. The line between good behavior and bad must be redrawn constantly, reactively, in the moment.
Extending CIS controls to cover AI agent behavior
This convergence aligns with the guidance in the newly released Model Context Protocol (MCP) Companion Guide from the Center for Internet Security (CIS), which frames MCP as a critical control point for governing AI agent behavior. The guide, published on 20 April 2026 and co-announced by CIS and Cequence, adapts the CIS Controls to cover the unique risks created when AI agents interact with enterprise tools, data, and systems.
"The CIS MCP Companion Guide defines what enterprises should do; the Cequence AI Gateway operationalises it," said Mehta. "The guide calls for explicit tool-level permissions, auditable interactions, and real-time sensitive data protection. AI Gateway delivers by generating least-privilege agent personas, logging every API call, and applying DLP scanning to tool requests and responses. It takes the CIS framework from theory to practice."
Why securing AI agent behavior matters now
AI agents are rapidly shifting from sandbox experiments to key players in production. They routinely access sensitive data, critical infrastructure, and powerful capabilities. Even carefully trained models can stitch together toxic patterns that evade static detection, while prompt-hacking techniques make it trivial to slip malicious instructions past login safeguards. Strict authentication matters, but it’s only the first line, not the front line.
At the same time, AI-powered attacks are drastically compressing threat timelines. What used to take adversaries months now takes hours. That means defenders have to spot and block threats in real time. Security must live where the agents live, at the level of API calls and data flows, in the moment, at machine speed.
Cequence’s AI Gateway delivers by extending zero trust security into the heart of agent operations – every API call, every data flow, every decision point, continuously analyzed and gated by find-grained policy. Questionable agent actions are surfaced, scored, and blocked immediately, before damage is done.
