First reported deepinspect.ai
Lead dispatch
First reported · updated · 2 reports island.io
AgentBaiting: How Fake AI Skills Deliver Malware at Scale
The FakeGit campaign, detailed by Island security researcher Oleg Zaytsev, uses roughly 7,600 malicious GitHub repositories—over 800 posing as AI Skills or MCP servers—to deliver SmartLoader malware, which establishes persistence and installs the StealC information stealer. Researchers coined the technique 'AgentBaiting,' where AI agents like Claude Code, Gemini, and ChatGPT autonomously discover the attacker repositories, treat the malicious READMEs as legitimate documentation, and hand installation instructions to users; the operation recorded over 14 million downloads and peaked in April 2026.supply-chain · tool-abuse · malware-distribution · agent-baiting
mcp · ai-agents · llm · github
Severity
0.78
The wire · latest
First reported · updated · 3 reports appsentinels.ai
One Poisoned MCP Server Can Hijack All the Others — Coograph
MCP tool poisoning hides malicious instructions inside a Model Context Protocol server's tool descriptions, parameter schemas, or return values — invisible to human reviewers but fully read by the LLM, which then selects and executes the poisoned tool, enabling data exfiltration, credential theft, or lateral movement. The technique spans schema poisoning, tool shadowing, and rug pulls, and is catalogued as OWASP MCP03:2025; a single malicious server can influence an agent's decisions across all connected tools (cross-tool poisoning). Details →First reported · updated · 3 reports medium.com
Your AI Agent Trusts Every Tool It's Ever Been Introduced To
An analysis piece, 'The MCP paradox,' argues that the Model Context Protocol standardized not only how agents reach tools but also how attackers reach agents, walking through concrete vectors like tool poisoning attacks where a malicious tool description instructs an agent to exfiltrate secrets (e.g. SSH keys) via text the user never sees. The article cites Invariant Labs' April 2025 tool-poisoning proof of concept and MCP's own design choices, and proposes defensive controls to harden MCP servers. Details →First reported acm.org
Confused Deputy Attack Against Model Context Protocol | ACM Transactions on Software Engineering and Methodology
An ACM TOSEM paper uncovers the "confused deputy attack" against the Model Context Protocol (MCP), where an adversarial server with subtly manipulated metadata overshadows a benign server and intercepts tool invocations without overt malicious behavior. The authors built Puppet, an automated evaluation framework that rewrites benign tool descriptions to hijack tool selection, achieving hijacking rates up to 90.89% and payload execution up to 86.46% across 14 models, while evading MCP-Scan and McpSafetyScanner which cannot detect metadata-level manipulation. Details →How the wire is made
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