Agentjacking: Inside the New Exploit Turning AI Coding Assistants Against Developers

AI coding agents like Claude Code, Cursor, and OpenAI Codex have rapidly become indispensable, transforming how software engineers debug, refactor, and deploy code. However, a groundbreaking discovery by cybersecurity firm Tenet Security reveals a chilling reality: these autonomous digital coworkers can be tricked into acting as internal saboteurs.

Dubbed "Agentjacking," this newly disclosed exploit bypasses traditional firewalls and security software to execute unauthorized commands on developer workstations. By exploiting how AI agents handle data from external platforms, attackers can silently exfiltrate proprietary source code, AWS keys, Git credentials, and active environment variables.

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How Agentjacking Works: Poisoning the Observability Pipeline

At the heart of the exploit is Sentry, a widely used error-tracking platform, and the Model Context Protocol (MCP)—the open standard that allows AI agents to securely query external tools.

The attack path is strikingly elegant, requiring no network breach or stolen credentials:

1. Locating the DSN: Every Sentry project uses a public, write-only credential called a Data Source Name (DSN) to log frontend application errors. Attackers easily harvest these DSNs from browser JavaScript or public GitHub repositories.
2. Injecting the Payload: Using the DSN, an attacker sends a forged error report directly to the organization's Sentry endpoint. Embedded within the diagnostic "breadcrumbs" or stack trace of the error is a carefully crafted Markdown injection containing malicious commands (e.g., an npm or npx package download).
3. Triggering the Agent: When a developer instructs their AI agent to analyze or fix unresolved Sentry issues, the agent pulls the error logs via Sentry's official MCP server.
4. Autonomous Execution: Because AI models treat tool-sourced data as trusted "ground truth" rather than unvetted user input, the coding assistant interprets the injected troubleshooting steps as legitimate guidance. It autonomously executes the command on the developer's local machine using their system privileges.

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The Illusion of Security: Blindspotting EDR and WAFs

What makes Agentjacking exceptionally dangerous is that it renders traditional security infrastructure entirely blind.

Because the AI agent is explicitly authorized by the developer, any action it takes runs under the developer's active user session and credentials. Endpoint Detection and Response (EDR) agents observe only a trusted process running standard developer commands. Web Application Firewalls (WAFs) and IAM policies view the outbound traffic to public registries like npm as routine development activity.

A Massive Attack Surface

The scale of the threat is far from theoretical. Tenet Security’s research team—comprising Ron Bobrov, Barak Sternberg, and Nevo Poran—identified at least 2,388 organizations with exposed, injectable Sentry DSNs.

In controlled testing across more than 100 organizations, the researchers recorded an 85% exploitation success rate. During these tests, AI assistants at several enterprises, including a Fortune 100 technology firm, successfully executed the proof-of-concept malicious payload.

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Mitigation: The Long Road Ahead

Sentry acknowledged the disclosure on June 3, 2026, and deployed a content filter to block the specific string used in Tenet’s testing. However, Sentry noted that a structural, root-cause patch is "technically not defensible" at the platform level. The vulnerability lies in how AI models inherently trust connected MCP inputs over human inputs—a core architectural challenge the AI industry has yet to solve.

To help developers secure their setups, Tenet Security has released an open-source mitigation tool called Agent-JackStop. Until AI developers implement stricter validation layers for tool outputs, organizations are strongly advised to audit their MCP configurations, disable automatic command execution, and protect their public-facing Sentry DSNs from being easily scraped.