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FIRST LOOK Microsoft Sentinel and Defender Experts Add Multi-Cloud MDR Coverage // HIGH Claude Code Auto Mode Bypassed via Zip Payload at 80% Rate // CRITICAL AI Agents Install Unowned Packages via Poisoned llms.txt Files // HIGH ChatGPT Abused by Cambodia Scam Network for Social Engineering // CRITICAL OpenAI AI Agents Escape Sandbox and Hack Hugging Face // HIGH AI Gateways Targeted: LiteLLM, RAGFlow, Kestra Compromised // FIRST LOOK GitHub Releases LLM Pre-Production Evaluation Guide for Developers // HIGH CVE-2026-75149: Marimo Notebook MCP Code Injection Flaw // FIRST LOOK AWS Adds Agentic Observability via OpenSearch Service MCP Apps // HIGH NVIDIA NemoClaw Flaw Lets Malicious Page Poison Local AI Model //
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Kimsuky Runs Offline LLMs to Sharpen Phishing, Build Malware

Kimsuky Runs Offline LLMs to Sharpen Phishing, Build Malware

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 The Hacker News

North Korean APT group Kimsuky has assembled a private, offline AI stack — including Ollama, GPT4All, and RAG tooling — to enhance spear-phishing lure quality and automate malware development in C#/.NET. South Korean firm Genians found configured instances of these tools on Kimsuky-linked infrastructure, alongside developer libraries such as LLaMaSharp and Microsoft Semantic Kernel, indicating deliberate integration of AI into the group's attack pipeline. The shift erodes traditional phishing detection signals like poor grammar and formatting, forcing defenders to pivot toward behavioural indicators on the endpoint.

GreyVibe Deploys ChatGPT and Gemini in LLM Attack Chain

GreyVibe Deploys ChatGPT and Gemini in LLM Attack Chain

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.5 SecurityWeek

WithSecure has documented GreyVibe, a Russia-nexus threat actor systematically deploying ChatGPT, Google Gemini, and Ideogram AI across every phase of its attack chain — from phishing lure creation to custom malware development — against Ukrainian targets since August 2025. The group's LLM-assisted malware, LegionRelay, contained design flaws introduced during AI-generated development, which paradoxically allowed researchers to track the group over an extended period. The case illustrates both the operational leverage AI provides to moderately skilled threat actors and the novel forensic signatures that AI-assisted development can inadvertently introduce.

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