First reported forcepoint.com
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 · 2 reports medium.com
RAG Security Guide: Prevent Enterprise AI Data Leakage
A vendor guide from LangProtect explains how Retrieval-Augmented Generation (RAG) systems can leak sensitive enterprise data, using an illustrative case of a healthcare AI assistant that returned document excerpts across business units because a shared vector index was queried before document permissions were evaluated. The article outlines the mechanism of RAG data leakage and references academic work on adaptively attacking RAG systems to exfiltrate private knowledge bases. Details →First reported arxiv.org
An Evaluation of Data Leakage Risks in Tool-Using LLM Agents in Realistic Scenarios
A joint evaluation by the Singapore AI Safety Institute and the Korea AI Safety Institute (arXiv:2606.17114) tested three tool-using LLM agents across 12 realistic, non-adversarial tasks spanning customer support, DevOps, web automation, and productivity, measuring five data-handling risk types. None of the agents achieved fully correct and fully safe execution, with successful task completion often coinciding with data-handling failures such as accessing unnecessary information or disclosing data to inappropriate recipients. Details →First reported jackdavis.net
Maintaining Privacy With Agents: What Actually Works When Sensitive Data Is Part of the Workflow
A write-up releasing `agent-privacy`, an open-source privacy-control layer for CLI-style agent harnesses that intercept sensitive data (PII, identifiers) before it becomes model-visible context. It uses prompt/pre-tool/post-tool hooks with four actions — allow, redact, handoff, block — and integrates a local filter service, OpenAI Privacy Filter, and local Qwen models, with an operational pii-guard report covering ~6,343 screening decisions. Details →How the wire is made
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