First reported · updated · 6 reports huggingface.co
Lead dispatch
First reported island.io
AgentBaiting: How Fake AI Skills Deliver Malware at Scale
Island security researchers uncovered the FakeGit campaign, which used roughly 7,600 malicious GitHub repositories—over 800 posing as AI Skills or MCP servers—to deliver SmartLoader malware that installs the StealC information stealer. The campaign introduces a technique called AgentBaiting, in which AI agents such as Claude Code, Gemini, and ChatGPT autonomously discover the attacker repositories, treat the malicious README as legitimate documentation, and pass installation instructions to users; the operation recorded over 14 million downloads.supply-chain · tool-abuse · malware-delivery · agentbaiting
mcp · ai-agents · ai-skills · llm · copilot
Severity
0.75
The wire · latest
First reported cyberscoop.com
Sysdig clocks first documented case of agentic ransomware
CyberScoop, reporting on Sysdig research, describes JadePuffer — the first documented case of agentic ransomware, where an AI agent autonomously drove an end-to-end extortion operation spanning reconnaissance, credential theft, lateral movement, persistence, encryption and ransom-note delivery. The late-June 2026 attack gained initial access via Langflow flaw CVE-2025-3248, targeted a MySQL/Alibaba Nacos production server, ran more than 600 purposeful payloads, and used keys for OpenAI, Anthropic, DeepSeek and Gemini, with the agent fixing a failed backdoor in 31 seconds. Details →First reported proofpoint.com
Anthropic Leak & Mercor Attack | Enterprise AI Security Risks | Proofpoint US
Proofpoint reports two April 2026 AI security incidents: an Anthropic leak that exposed internal files and Claude Code source code via a release packaging error, and a Mercor supply-chain attack in which malicious code embedded in the open-source LiteLLM library (used to connect applications to AI services) stole API keys and customer data, attributed to Team PCP within the Lapsus$ group. The piece frames these as evidence that AI security failures are operational and governance failures involving human error, insecure integrations, and compromised dependencies. Details →First reported jscrambler.com
Unauthorized Publication of a Malicious npm Package affecting CI
Jscrambler disclosed that a threat actor used compromised npm publishing credentials to publish a malicious version of its 'jscrambler' npm package (versions 8.14, 8.16, 8.17, 8.20), which ran an infostealer during the preinstall hook and was downloaded around 1,479 times in a two-hour window. Per Socket's analysis, the malware harvested developer credentials, cloud secrets, crypto wallets, browser data, and notably AI coding tool and MCP configurations (Claude, Cursor, Windsurf, VS Code, Zed), using ChaCha20-Poly1305 obfuscation to resist analysis. Jscrambler revoked credentials and released a safe version 8.22. Details →First reported sygnia.co
Lone Attacker Uses AI to Breach AWS Cloud Environment in 72 Hours
Incident response firm Sygnia published research describing how a lone, financially motivated attacker used agentic AI workflows to accelerate reconnaissance, attack-tool development, command structuring, and environment-specific adaptation to compromise a large AWS environment in roughly 72 hours and extort an unnamed global enterprise. The attacker chained cloud weaknesses and stolen credentials, using AI to operate at a speed and scope atypical for a small-scale operation. Details →First reported · updated · 2 reports sysdig.com
Understanding Langflow CVE-2026-55255, and why higher CVSS vulnerabilities aren't always the most exploited
CISA added CVE-2026-55255, an actively exploited Insecure Direct Object Reference (IDOR) authorization-bypass flaw in the Langflow visual framework for building AI agents, to its Known Exploited Vulnerabilities catalog and ordered federal agencies to patch it. The flaw lets authenticated attackers access other users' flows via the /api/v1/responses endpoint using a victim's flow UUID, and Sysdig observed in-the-wild exploitation aimed at leaking API keys, delivering second-stage loaders, and stealing LLM/cloud credentials and compute. Details →How the wire is made
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