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NadMesh represents a critical escalation where botnets have evolved from opportunistic worms into industrial-grade platforms specifically targeting exposed AI infrastructure like Ollama and ComfyUI. By leveraging Shodan to efficiently identify vulnerable Model Context Protocol (MCP) services, attackers can now bypass traditional scanning inefficiencies to directly compromise live machine learning deployments. This shift underscores the urgent need for hardening default configurations of open-source AI tools against automated reconnaissance and exploitation vectors.

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NadMesh Uses Shodan to Find and Hijack Exposed AI and MCP Infrastructure

Cybersecurity NewsJuly 19, 20264 min read

A sharp structural shift has been identified in the botnet landscape. Security researchers at XLab have uncovered NadMesh, a Go-based botnet that has been spreading rapidly since early July 2026. This malware marks a distinct evolution from opportunistic worm behavior toward an industrial-grade, ROI-driven attack platform aimed squarely at Artificial Intelligence (AI) and Model Context […] The post NadMesh Uses Shodan to Find and Hijack Exposed AI and MCP Infrastructure appeared first on Cyber Security News.

A sharp structural shift has been identified in the botnet landscape. Security researchers at XLab have uncovered NadMesh, a Go-based botnet that has been spreading rapidly since early July 2026. This malware marks a distinct evolution from opportunistic worm behavior toward an industrial-grade, ROI-driven attack platform aimed squarely at Artificial Intelligence (AI) and Model Context Protocol (MCP) infrastructure. Unlike traditional worms that spread indiscriminately, NadMesh combines autonomous…

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