AWS and Vercel Patch Critical Flaws in AI Agent Platforms Allowing Unauthorized Tool Execution

AWS and Vercel have addressed multiple critical vulnerabilities in their AI agent platforms that enabled unauthorized execution of tools without legitimate model approval. The issues, grouped under the CoreBreak pattern, allowed attackers to bypass AI authorization checks by injecting crafted tool calls that the infrastructure misinterpreted as model-approved actions. In AWS, CVE-2026-18830 affected the InvokeHarness API in Amazon Bedrock AgentCore, permitting authenticated users to trigger sensitive tools directly. Vercel faced two separate flaws tracked as CVE-2026-64650 and CVE-2026-64651 that let sandboxed code reach host system tools, potentially exposing secrets or cloud APIs. No public evidence of active exploitation has been confirmed yet. Organizations are advised to apply updates immediately, restrict available tools for agents, and treat all external inputs as potentially malicious.

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AWS and Vercel have patched several critical vulnerabilities affecting platforms that power AI agents. The flaws allowed malicious actors to execute tools without proper authorization from the underlying model.

The vulnerabilities belong to a broader attack pattern researchers named CoreBreak. The core issue occurred when infrastructure treated a user-supplied tool call as evidence that the action had been generated and approved by the AI agent itself.

AWS Bedrock AgentCore Impact

In AWS, CVE-2026-18830 affected the InvokeHarness API of Amazon Bedrock AgentCore. An authenticated user could append a specially crafted tool invocation to the end of a request and directly trigger any tools available in the environment without the model reviewing or approving the operation.

Vercel Sandbox Escape Issues

Vercel addressed two vulnerabilities recorded as CVE-2026-64650 and CVE-2026-64651. These issues allowed code running inside a Linux sandbox to reach tools present on the host system. Depending on configured permissions, an attacker could read secrets, interact with cloud APIs, or perform deployment-related operations.

The flaws increased the risk posed by malicious code processed by AI coding agents. No confirmed cases of real-world exploitation have been reported publicly.

Security teams should update affected components, limit the set of tools exposed to agents, and treat conversation history, events, and external calls as untrusted input.

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