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Adversaries may compromise macOS-based Generative AI (GenAI) tools through prompt injection, malicious Model Context Protocol (MCP) servers, or poisoned plugins to establish Command and Control (C2) channels or exfiltrate sensitive data by causing them to connect to unusual domains.

CVE-2026-63093 describes a binary planting vulnerability in Cursor for Windows version 3.2.16 that allows a remote attacker to achieve arbitrary code execution by placing a malicious `git.exe` file in a crafted repository's root, which the Cursor IDE automatically executes during startup or on a recurring cadence when a developer opens the repository, running the malicious binary under the privileges of the current user.

The adoption of AI coding tools introduces significant security risks, such as the generation of vulnerable code with OWASP Top 10 flaws, the inadvertent leakage of sensitive secrets and hardcoded credentials, and supply chain compromise via 'slopsquatting,' alongside specific vulnerabilities like 'GhostApproval' which allows remote code execution on developer machines.

Tracking brief for the Shai-Hulud campaign; individual sightings are folded in as reported.

A high-severity vulnerability (CVE-2026-12957) in the Amazon Q Developer Extension for Visual Studio Code allowed attackers to achieve arbitrary code execution and cloud credential theft by automatically loading and executing malicious Model Context Protocol (MCP) server configurations from a `.amazonq/mcp.json` file in a repository without user consent, providing full access to a developer's environment and cloud credentials.

This rule detects Elastic Defend alerts originating from or directly related to GenAI coding utilities, indicating potential prompt injection, malicious skills, or supply-chain compromise.

Unsecured Model Context Protocol (MCP) servers, used to connect AI agents to enterprise tools, lack authentication and audit trails, leading to data exfiltration, private repo leaks, cross-tenant exposure, and remote code execution due to AI agents using valid user credentials to make API calls based on potentially poisoned context.

This rule detects unusual modifications to GenAI tool configuration files, potentially indicating an attacker injecting malicious MCP server configurations to hijack AI agents for persistence, command and control, or data exfiltration.