Menlo Security unveiled an expansion of its Agent Runtime Security (MARS) platform at Black Hat USA 2026, extending protection to AI coding agents including Claude Code, Microsoft Copilot, and Google Gemini. The approach — browser-isolated cloud proxying — takes a fundamentally different architectural stance on securing AI coding agents than the model-level guardrails most vendors have pursued.

What MARS Does

MARS stands for Agent Runtime Security. The platform intercepts the environment that an AI coding agent reads from — web pages, files, downloaded content, and other inputs — and sanitizes that content before the agent ever processes it.

The core protection is against prompt injection attacks: attempts to embed hidden instructions in content that an AI agent reads, causing the agent to take actions the user didn’t intend. Rather than trying to detect or filter injections at the model level, MARS removes injected content from the agent’s input stream before it reaches the model.

The platform also addresses data exfiltration: preventing AI coding agents from including sensitive data from the local environment in outputs sent to external services or model providers.

The Architecture: Browser Isolation

What distinguishes MARS from model-level guardrail approaches is its reliance on browser-isolated cloud proxying. When an AI coding agent accesses web content through the MARS-protected environment, that content is isolated and rendered in Menlo Security’s cloud infrastructure before being delivered to the agent. The isolation layer allows sanitization without requiring access to the model itself or modification of the agent’s codebase.

This architecture has meaningful implications for enterprise deployments:

  • No model access required — MARS works as an infrastructure layer, not a model wrapper
  • Works across vendors — the same proxy infrastructure protects Claude Code, Copilot, and Gemini without vendor-specific integrations
  • Doesn’t require agent modification — enterprises don’t need to modify their coding agent deployments to use MARS

From Menlo’s press release: the platform sanitizes “web pages, files, and downloads before AI agents access them, removing hidden injections.”

Why This Matters at Black Hat 2026

Menlo Security’s timing is deliberate. Black Hat 2026 featured multiple major agentic AI security disclosures — including Novee Security’s Cordyceps research showing how AI coding agents can achieve supply chain compromise through CI/CD vulnerabilities, and Zenity Labs’ disclosure of a 1.7 million installation malicious skills campaign targeting Claude Enterprise.

Together, these presentations paint a consistent picture: the surface area for attacking AI coding agent deployments is large, diverse, and actively being exploited or demonstrated at scale. Prompt injection specifically has been identified as a persistent and difficult-to-solve problem by AI vendors themselves — Anthropic’s own SECURITY.md for Claude Code Action explicitly acknowledges that injection sanitizers can be bypassed and new bypass techniques will continue emerging.

MARS addresses the prompt injection surface not by solving it at the model level (which vendors have struggled to do reliably) but by moving the trust boundary to the network layer, where browser isolation has a long track record in securing browsers against web-based attacks.

The Covered Agents

Menlo’s press release names three AI assistants and coding agents as covered by the MARS expansion:

  • Claude Code (Anthropic)
  • Microsoft Copilot
  • Google Gemini in Chrome

The coverage for Gemini in Chrome is particularly notable: it suggests MARS can protect AI assistants operating within the browser itself, not just standalone coding agent tooling.

Enterprise Context

Menlo Security’s browser isolation platform already serves a significant enterprise install base for traditional web security. The MARS expansion represents the company extending that footprint into AI coding agent security — a market that’s clearly heating up given the pace of Black Hat disclosures.

For enterprise security teams evaluating coverage for AI coding agent deployments, MARS represents one of the first purpose-built runtime security products that works across multiple AI vendors without requiring model-level access. That’s a meaningful differentiator in an environment where the attack surfaces span multiple vendors and deployment models.

The company describes this as “the industry’s first browser security platform to govern AI agents,” framing the browser-isolation heritage as the foundation for a broader AI agent security posture.

The Limits of Any Single Approach

It’s worth noting what browser-isolated proxying doesn’t cover. MARS addresses the content injection surface — what the AI agent reads from web and file inputs. It doesn’t address:

  • Supply chain compromise via CI/CD workflow vulnerabilities (the Cordyceps attack class)
  • Malicious installed skills or plugins (the Zenity attack class)
  • Model-level issues or training data risks

No single security product covers the full agentic AI attack surface. MARS fills a meaningful gap on the input sanitization side, complementing the scanning and workflow security mitigations that other vendors and researchers are developing in parallel.

Sources

  1. Menlo Security Press Release — MARS Extended to Claude Code and Copilot
  2. Novee Security — Cordyceps: Critical Flaws in AI Coding Agents at Black Hat 2026

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