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# Static Security Policies Can't Keep Up With Agentic AI
- URL: https://www.cybrsecmedia.com/static-security-policies-cant-keep-up-with-agentic-ai/
- Published: 2026-10-06T17:23:17.000Z
- Updated: 2026-10-06T17:24:20.000Z
- Description: Agentic AI is exposing the limits of static security policies, excessive permissions and decades of technical debt. Enterprises need dynamic, runtime security controls that evaluate what AI agents are doing in real time. (Sponsored by Eve Security)
- Author: Bill Brenner
- Tags: AI Governance, Agentic AI, Article

Enterprise security policies were built for a world in which identities, permissions and applications behaved somewhat predictably. Agentic AI is blowing holes in that assumption.

AI agents can operate autonomously, connect to multiple systems, make decisions and execute actions at machine speed. And they're entering enterprise environments already burdened by excessive permissions, inconsistent processes and decades of technical debt.

That combination creates a problem static security policies weren't designed to solve.

"You have to be able to, on the fly, understand the behaviors and modify policies based on organizational needs," Nadav Cornberg, founder and CEO of Eve Security, told Michael Farnum and Sam Van Ryder during the latest episode of CYBR.SEC.CAST. His conclusion was even more direct: "Nothing here can be static."

**Full episode and related article:**

[The Wild West of Deploying Agents with Nadav CornbergCYBR.SEC.CAST explores securing agentic AI with Eve Security CEO Nadav Cornberg, from governance and MCP to dynamic AI risk.![](https://storage.ghost.io/c/ab/67/ab676516-71e3-473d-8f73-9e0692f5aaee/content/images/icon/CYBR.SEC.Media-Logo-copy-f9e05239-b9fa-474b-9aba-fef7128a4f89.jpg)CYBR.SEC.Media, and CYBR.SEC.Media![](https://storage.ghost.io/c/ab/67/ab676516-71e3-473d-8f73-9e0692f5aaee/content/images/thumbnail/Nadav-Cornberg_Ghost-4220f400-fbb1-4b3b-b9bb-be82e755d2dc.png)](https://www.cybrsecmedia.com/the-wild-west-of-deploying-agents-with-nadav-cornberg/)

[Agentic AI Security Must Prepare for AI Agent MistakesAs enterprises deploy autonomous AI agents across critical systems, security teams must assume those agents will make mistakes. Agentic AI security requires continuous monitoring of behavior, intent and context — not blind trust in permissions. (Sponsored by Eve Security)![](https://storage.ghost.io/c/ab/67/ab676516-71e3-473d-8f73-9e0692f5aaee/content/images/icon/CYBR.SEC.Media-Logo-copy-a5ab3e3e-b6e0-4efa-bb54-319e490c5c05.jpg)CYBR.SEC.MediaBill Brenner![](https://storage.ghost.io/c/ab/67/ab676516-71e3-473d-8f73-9e0692f5aaee/content/images/thumbnail/136019c9-9e00-48dd-b044-36e248e68c50-ea0d17e2-687b-4364-a913-91671355053a.png)](https://www.cybrsecmedia.com/ai-agents-will-make-mistakes-enterprise-security-must-be-ready-when-they-do/)

"If all you're doing is writing static policies to say this is allowed, then that to me is not far enough," he said.

Instead, an agent attempting a sensitive operation could potentially be checked against change-management systems and other sources of business context in real time.

A legitimate change scheduled for Tuesday afternoon might be approved. The exact same action at 3 a.m. Saturday without a corresponding ticket could trigger an investigation or be blocked.

The action hasn't changed. The context has.

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## AI agents are entering an already imperfect environment

That would be challenging enough if enterprises had pristine identity environments. They don't.

Organizations have spent years accumulating excessive privileges, stale accounts, inconsistent authorization and technical debt. Employees often don't know precisely what permissions they possess. Access gets granted for projects and never removed. Processes exist on paper but aren't always followed.

AI agents will inherit that mess. Cornberg warned that agents may present a particularly difficult challenge because they can determine what they're capable of accessing and potentially find different ways to accomplish their objectives.

"The reality is, which is shared by many CISOs, it is not that black and white," he said. Identities can be overprovisioned, procedures won't always be followed and organizations need security capable of compensating for those imperfections.

That's an important distinction. Agentic AI isn't creating all of these security weaknesses. It's being dropped directly on top of them.

## Technical debt meets machine speed

The cybersecurity industry has spent years warning organizations about technical debt. Clean up excessive permissions. Modernize legacy systems. Improve identity governance. Fix broken processes. Apply least privilege. All good advice. But large enterprises can't simply stop operating for several years while security teams clean everything up.

Cornberg argued that technical debt persists in part because organizations constantly weigh the cost of eliminating a problem against the risk of leaving it alone. Sometimes there simply isn't enough return on investment to fix everything.

"You can't tackle everything," he said.

Agentic AI raises the stakes of that calculation because autonomous systems can operate across those imperfect environments at machine speed. An excessive permission that sat unused for years becomes considerably more interesting when an AI agent discovers it can use it. A process employees occasionally bypass becomes more dangerous when autonomous systems begin executing thousands of actions.

And an authorization mistake that previously required a human to recognize and exploit it can potentially become part of an agent's automated workflow.

The result is a collision between two very different eras of enterprise technology.

## Runtime security could become the new control point

That helps explain why the CYBR.SEC.CAST discussion repeatedly returned to runtime security.

Instead of trying to eliminate every underlying weakness before allowing AI agents to operate, enterprises may need another layer of control capable of evaluating what agents are actually doing as they do it. Farnum framed the challenge as a runtime problem rather than purely a posture problem.

Could organizations use AI itself to help compensate for existing technical debt without first having to repair every permission, workflow and legacy system underneath it? That doesn't eliminate the need for identity governance, least privilege or better security hygiene. It recognizes that those controls will never be perfect.

Runtime controls could provide another layer: observe an agent's behavior, compare it against expected activity, examine the business context and determine whether an action makes sense before allowing it to proceed. That also changes the security model.

Instead of:

**Identity → Permission → Allow/Deny**

Agentic AI pushes enterprises toward something closer to:

**Identity → Permission → Behavior → Intent → Context → Decision**

The additional layers matter because authorization alone doesn't explain why an agent is doing something.

Cornberg described an approach in which an agent performing an unusual action could effectively be interrogated: Why are you doing this? Where did the instruction originate? Is there a corresponding ticket? Who approved it?

Those answers can then be compared with other enterprise systems before the action proceeds.

## Security has to become as dynamic as the systems it protects

None of this means traditional security controls suddenly become irrelevant. Identity still matters. Least privilege matters. Change management matters. Zero trust matters.

But autonomous AI introduces a new requirement: those controls increasingly need to understand what's happening right now, not merely what someone decided should be allowed when a policy was written six months ago. That may become one of the defining challenges of agentic AI security.

Enterprises are deploying autonomous systems because they want speed, efficiency and greater productivity. Businesses aren't likely to surrender those benefits while security teams spend years eliminating every piece of technical debt.

Security will have to operate inside that imperfect reality. Static policies can establish the boundaries.

But when AI agents begin testing those boundaries at machine speed, enterprises will need security controls capable of moving just as fast.

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