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AI Coding Tools Leak Repos as RemControl Trojan Uses AI Dev

AI Coding Tools Leak Repos as RemControl Trojan Uses AI Dev

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.8 The Hacker News

Two distinct AI security concerns emerged this week: Z.ai's ZCode coding assistant was found silently exfiltrating users' local code repositories to Alibaba Cloud servers without consent, echoing a similar incident with SpaceXAI's Grok Build CLI. Separately, the RemControl Android banking trojan demonstrates AI-assisted malware development, with verbatim AI assistant responses embedded in live phishing pages served to banking victims across Western Europe, the Middle East, and Canada. Together, these incidents highlight the dual threat of AI tools as both accidental data exfiltration vectors and force multipliers for threat actors.

Zhipu AI Releases GLM-5.2 Open-Weight Model

Zhipu AI Releases GLM-5.2 Open-Weight Model

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 The Verge AI

Zhipu AI (Z.ai) has released GLM-5.2, an open-weight model that researchers report matches Anthropic's Mythos in bug-finding and cybersecurity-related tasks, while remaining freely downloadable and runnable on commodity hardware. The open-weight distribution removes access controls and usage monitoring that restrict frontier closed models, enabling unconstrained offensive security use by any actor. Defenders face a materially elevated threat from nation-state and cybercriminal actors who can now fine-tune, deploy, and weaponise a frontier-class vulnerability-discovery model without API gatekeeping or usage telemetry.

Z.ai Releases GLM-5.2 Open-Weights 753B LLM

Z.ai Releases GLM-5.2 Open-Weights 753B LLM

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 6.2 Simon Willison

Z.ai has released GLM-5.2, a 753-billion-parameter mixture-of-experts model under an MIT license, ranking as the top open-weights model on the Artificial Analysis Intelligence Index and second on the Code Arena WebDev leaderboard. For defenders, the combination of frontier-level capability, unrestricted open-weights distribution, and a 1-million-token context window materially lowers the barrier for threat actors to self-host a highly capable model outside any provider's safety controls. The model's agentic coding performance and massive context window expand the viable attack surface for automated code generation, targeted phishing, and large-scale document analysis without API-level monitoring.

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