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The Coding-Agent Trap: When a "Free" LLM Endpoint Is the Adversary, (Mon, Aug 31st)
A SANS honeypot caught a real coding-agent session routed to a rogue "free" LLM endpoint, exposing a Windows user's transcript and tool outputs.
A SANS analyst describes how an internet-exposed inference honeypot was discovered, relabeled with sought-after model names like DeepSeek, and enrolled in infrastructure serving "free" LLM backends. On 2026-08-30 an opencode terminal coding agent sent an 88-message, 224 KB transcript 210 times in 91 seconds via a China Unicom relay, exposing directory listings, tool outputs and read file portions. The analyst frames tool-enabled agents treating model endpoints as trusted control planes as a novel risk — a "rogue model endpoint" that could request tool executions on the user's machine.
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Infostealers Target Claude, Cursor, Codex and Other AI Agents to Steal Credentials and Sensitive Data
Gen Digital researchers report infostealer families Amatera, Remus and CallbackBeaver now harvest Claude, Cursor and Codex agent data, including tokens and MCP configs.
Gen Digital researchers found commodity infostealers extending their collection rules to local AI coding agent data from Claude, Cursor, Codex, Cline, Continue and OpenCode on Windows and macOS. Amatera targets Cline and Continue, Remus targets Claude, Cursor and OpenCode, and CallbackBeaver added Claude and Cursor with more than 5,000 samples observed in 30 days; Djinn Stealer hits Claude, Codex, Gemini, Cline, OpenCode and Kilo on macOS. Stolen data includes access and refresh tokens, prompt histories, conversation databases and MCP configurations holding API keys, potentially exposing connected source-control, cloud and ticketing systems. Remus is assessed as a Lumma Stealer variant using EtherHiding C2 resolution via Ethereum smart contracts.
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NICE Actimize enhances Integrated Fraud Management platform to help financial services prevent scams
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North Korean IT Workers Scheme: Detection IOCs and Tactics for Government and Corporate SOCs
ANY.RUN details the expanding North Korean IT worker infiltration scheme using forged identities and AI-assisted workflows, sharing detection IOCs for SOCs.
ANY.RUN describes how North Korean IT workers infiltrate American and European organizations using forged identities and AI-assisted workflows to become trusted insiders. The operation bypasses traditional security perimeters and has expanded beyond the private sector to government targets. The post provides detection IOCs and tactics for government and corporate SOCs.
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