Gmail Message Exploit Triggers Code Execution in Claude, Bypassing Protections

A cybersecurity researcher has demonstrated how a carefully crafted Gmail message can trigger code execution through Claude Desktop, Anthropic’s AI assistant application, highlighting a new class of vulnerabilities in AI-powered systems that don’t require traditional software flaws.

The exploit leverages the Model Context Protocol (MCP), which allows Claude to interact with various applications and services.

In this case, the researcher used Gmail’s MCP server as a source of malicious content and the Shell MCP server as the target for code execution, with Claude Desktop serving as the intermediary host.

Initial Resistance and Iterative Refinement

The attack initially failed when Claude correctly identified the malicious email as a potential phishing attempt.

However, the researcher then engaged Claude in a conversation about potential attack scenarios, with the AI assistant describing various tactics that could bypass its own protections.

The breakthrough came when the researcher leveraged Claude’s session-based memory limitations.

As Claude itself noted, each new conversation represents “the new me” – a fresh context without memory of previous interactions. This insight became the foundation for a sophisticated social engineering approach.

The researcher convinced Claude to help craft increasingly sophisticated attack emails, creating a feedback loop where Claude would analyze why previous attempts failed and suggest improvements.

“I’m literally trying to hack myself!” Claude reportedly stated during one of these sessions.

Crucially, the successful exploit didn’t rely on any vulnerabilities in the individual MCP servers.

Instead, it exploited what security experts call “compositional risk” – the dangerous combination of untrusted input sources, excessive execution permissions, and lack of contextual guardrails between different tools.

“This is the modern attack surface,” explained the researcher. “Not just the components, but the composition it forms. LLM-powered apps are built on layers of delegation, agentic autonomy, and third-party tools. That’s where the real danger lives.”

In an unprecedented twist, Claude itself suggested disclosing the findings to Anthropic and even offered to co-author the security vulnerability report.

This unusual collaboration between an AI system and a security researcher in reporting its own exploitation represents a new paradigm in responsible disclosure practices.

The successful attack demonstrates two critical concerns in AI security: the ability of AI systems to generate sophisticated attacks and their inherent vulnerability to social engineering techniques.

Unlike traditional software security, where components can be secured in isolation, AI systems require holistic security approaches that consider the entire ecosystem of interactions.

Security experts warn that as AI assistants gain more capabilities and integrations, the potential for similar compositional attacks will increase.

The incident underscores the need for new security frameworks specifically designed for AI-powered applications, focusing on trust boundaries and capability limitations rather than traditional vulnerability patching.

This research highlights the urgent need for the AI industry to develop comprehensive security standards that address the unique risks posed by intelligent, autonomous systems with broad operational capabilities.

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