AI Agents Act at Machine Speed. Menlo Security Governs What They Actually Do. | A Brand Briefing at Black Hat USA 2026 with Eric Avigdor, Vice President of Product of Menlo Security | Hosted by Sean Martin

Recorded on location at Black Hat USA 2026, Eric Avigdor of Menlo Security describes an adoption pattern he hears in customer conversation after customer conversation. AI makes teams measurably more productive. The guardrails that keep company data inside the business arrive later, if they arrive at all.

Eric Avigdor leads product for AI security and data security at Menlo Security, and he splits the problem into two categories that get very different levels of attention. One is how people use AI in the browser, including what data gets pasted into an assistant and how much of that usage anyone knows about. The other is autonomous agents built to run business processes, where the question is how to keep them productive without letting their goals get hijacked.

The category Eric Avigdor says compliance teams skip past is the agent that holds sensitive data and internet access at the same time. Read a poisoned web page, take the hidden instruction, and the goal changes. What is the difference between an agent running analysis on an internal database and an agent doing financial analysis at a bank with customer records and web access? One of them can be told to send the data somewhere else.

So who owns AI governance? In most companies, nobody does, at least not with authority. Responsibility lands with the endpoint team, the network team, or the browser team, and each one works its own angle. An endpoint team tracks agent traffic on the endpoint and then loses the trail when the agent moves data cloud to cloud. A cloud team has the reverse blind spot.

Menlo Agent Runtime Security, or MARS, is built around what an agent actually does rather than what it intends to do. Agent traffic is proxied through the Menlo Security cloud browser, where data masking, indirect prompt injection prevention, and web-based and file-based threat prevention are applied before an incident becomes cleanup work. Browser and web traffic today, MCP traffic next.

For regulated organizations, that architecture produces something auditors can use. Logging, dashboarding, and a visual record of what an agent attempted in the real world. Europe has the AI Act. The US has not landed comparable rules yet, and Eric Avigdor says that gap concerns him enough that he is talking with people working to close it.

GUEST

Eric Avigdor, Vice President of Product, Menlo Security | On LinkedIn: https://www.linkedin.com/in/eric-avigdor-0b561118/

RESOURCES

Black Hat USA 2026 event coverage: https://www.itspmagazine.com/black-hat-usa-2026-cybersecurity-event-coverage-in-las-vegas

Menlo Security: https://www.menlosecurity.com/

Menlo AI Agent Security: https://www.menlosecurity.com/product/ai-agent-security

Menlo AI Adaptive DLP: https://www.menlosecurity.com/product/ai-adaptive-dlp

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KEYWORDS

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