[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$frAbeWKz-Ji3ZhScY6l808WqrYFS25qG5WrUFjgAs6SE":3},{"article":4,"iocs":47,"watch_terms":51,"solutions":52,"lesson":143},{"id":5,"title":6,"slug":7,"summary":8,"ai_summary":9,"brief":10,"url":11,"image_url":12,"published_at":13,"ingested_at":14,"relevance_score":15,"entities":16,"category_id":29,"category":30,"article_tags":34},"39611d11-47c2-4030-bd9a-1a200f3a8cd2","This Windows Malware is Built to Let Up to Four AI Models Vote on Its Next Move","this-windows-malware-is-built-to-let-up-to-four-ai-models-vote-on-its-next-move-1e2c3d","A Windows malware called CLOSEDQUORUM is built to take orders from a vote of up to four AI models instead of an attacker's server, Cisco Talos said on September 22. The models can choose to steal Windows credentials, saved browser passwords, and crypto wallet data. Talos has not seen this setup work from start to finish, and the public version of the malware does not work as it is.","A new Windows malware named CLOSEDQUORUM, discovered by Cisco Talos, leverages up to four AI models to decide its next move, rather than relying on traditional C2 servers. The AI models can vote to steal credentials, browser passwords, and crypto wallet data. While the public version is limited, the concept represents an early step in attackers delegating decision-making to AI.","Windows malware CLOSEDQUORUM uses AI models to vote on its next malicious action.","https:\u002F\u002Fthehackernews.com\u002F2026\u002F09\u002Fwindows-malware-is-built-to-let-up-to.html","https:\u002F\u002Fblogger.googleusercontent.com\u002Fimg\u002Fb\u002FR29vZ2xl\u002FAVvXsEiZdSpi6aqUlY2q-T-3eJ4YCn7G3jYa9Exo6BMffjdRLuqg9Gdn4ImZXKjcYX8s5Swz3W_WhxMZ_Z7qbu0Z60KrCk8EUhRV8bJ7l1mXOoDCo-XAXyq69_rtFDoVhvAiuJP1rCdSf9KixTqgAA52iwqWsqB5T0uJaRGFz1hpBcpfQuvPMYd17UcrfrnUV0c\u002Fs1600\u002Fclosed.jpg","2026-09-23T14:17:58+00:00","2026-09-23T20:00:12.699043+00:00",8,[17,20,22,24,26],{"name":18,"type":19},"DeepSeek","product",{"name":21,"type":19},"Qwen",{"name":23,"type":19},"Mistral",{"name":25,"type":19},"Google Gemini",{"name":27,"type":28},"Cisco Talos","vendor","89f78b1c-3503-45a1-9fc7-e23d2ce1c6d5",{"id":29,"icon":31,"name":32,"slug":33},null,"Malware","malware",[35,40,42],{"category":36},{"id":37,"icon":31,"name":38,"slug":39},"839da5c1-3c34-47e2-9499-f7201640e3ac","AI Security","ai-security",{"category":41},{"id":29,"icon":31,"name":32,"slug":33},{"category":43},{"id":44,"icon":31,"name":45,"slug":46},"e7b231c8-5f79-4465-8d38-1ef13aea5a14","Threat Intelligence","threat-intelligence",[48],{"type":33,"value":49,"context":50},"CLOSEDQUORUM","Name of the Windows malware that uses AI models for decision making.",[27,18,21],{"controls":53,"vendors":139},[54,83,111],{"slug":55,"name":56,"problem":57,"products":58},"endpoint-detection-response","Endpoint detection and response (EDR and XDR)","Malware and hands-on-keyboard attackers on laptops and servers get spotted and stopped.",[59,67,75],{"vendor_slug":60,"vendor_name":61,"vendor_logo":62,"product_slug":63,"product_name":64,"url":65,"description":66},"sentinelone","SentinelOne","\u002Fvendor-logos\u002Fsentinelone.png","singularity-endpoint","Singularity Endpoint","https:\u002F\u002Fwww.sentinelone.com\u002Fplatform\u002Fendpoint-security\u002F","Endpoint protection and detection with automated response and rollback.",{"vendor_slug":68,"vendor_name":69,"vendor_logo":70,"product_slug":71,"product_name":72,"url":73,"description":74},"elastic","Elastic","\u002Fvendor-logos\u002Felastic.png","elastic-security","Elastic Security","https:\u002F\u002Fwww.elastic.co\u002Fsecurity","SIEM and endpoint security built on Elasticsearch, with open detection rules.",{"vendor_slug":76,"vendor_name":77,"vendor_logo":78,"product_slug":79,"product_name":80,"url":81,"description":82},"crowdstrike","CrowdStrike","\u002Fvendor-logos\u002Fcrowdstrike.png","falcon-insight-xdr","Falcon Insight XDR","https:\u002F\u002Fwww.crowdstrike.com\u002Fen-us\u002Fplatform\u002Fendpoint-security\u002Ffalcon-insight-xdr\u002F","Endpoint detection and response with extended detection across other security tools.",{"slug":46,"name":84,"problem":85,"products":86},"Threat intelligence","Attack campaigns reach your sector, suppliers or software before your team hears about them.",[87,95,103],{"vendor_slug":88,"vendor_name":89,"vendor_logo":90,"product_slug":91,"product_name":92,"url":93,"description":94},"reliaquest","ReliaQuest","\u002Fvendor-logos\u002Freliaquest.png","greymatter-digital-risk-protection","GreyMatter Digital Risk Protection","https:\u002F\u002Freliaquest.com\u002Fsecurity-operations-platform\u002Fdark-web-and-digital-risk-protection\u002F","Watches the open, deep and dark web for threats aimed at an organisation and alerts its security team in real time.",{"vendor_slug":96,"vendor_name":97,"vendor_logo":98,"product_slug":99,"product_name":100,"url":101,"description":102},"dataminr","Dataminr","\u002Fvendor-logos\u002Fdataminr.png","agentic-threat-intelligence-platform","Agentic Threat Intelligence Platform","https:\u002F\u002Fwww.dataminr.com\u002Fproducts\u002Fcyber-defense\u002Fagentic-threat-intelligence-platform\u002F","Threat intelligence platform, formerly ThreatConnect TI Ops, that collects, scores and structures intelligence and pushes it into security tools.",{"vendor_slug":104,"vendor_name":105,"vendor_logo":106,"product_slug":107,"product_name":108,"url":109,"description":110},"recorded-future","Recorded Future","\u002Fvendor-logos\u002Frecorded-future.png","recorded-future-cyber-operations","Recorded Future Cyber Operations","https:\u002F\u002Fwww.recordedfuture.com\u002Fproducts\u002Fcyber-operations","Threat intelligence built into security operations workflows, to prioritise alerts and act on threats before they arrive.",{"slug":39,"name":112,"problem":113,"products":114},"AI application security","Prompt injection, data leaks through AI tools and unapproved AI use get caught.",[115,123,131],{"vendor_slug":116,"vendor_name":117,"vendor_logo":118,"product_slug":119,"product_name":120,"url":121,"description":122},"boomi","Boomi","\u002Fvendor-logos\u002Fboomi.png","boomi-ai-gateway","Boomi AI Gateway","https:\u002F\u002Fboomi.com\u002Fplatform\u002Fai-gateway\u002F","Gateway for AI model and MCP tool traffic, built on Lunar.dev technology. It limits which tools each agent can call. Its enterprise version adds an approval step for new MCP servers and logs each call with the user or agent behind it.",{"vendor_slug":124,"vendor_name":125,"vendor_logo":126,"product_slug":127,"product_name":128,"url":129,"description":130},"cisco","Cisco","\u002Fvendor-logos\u002Fcisco.png","ai-defense","Cisco AI Defense","https:\u002F\u002Fwww.cisco.com\u002Fsite\u002Fus\u002Fen\u002Fproducts\u002Fsecurity\u002Fai-defense\u002Findex.html","Discovery of AI use, testing of models and guardrails for AI applications.",{"vendor_slug":132,"vendor_name":133,"vendor_logo":134,"product_slug":135,"product_name":136,"url":137,"description":138},"hiddenlayer","HiddenLayer","\u002Fvendor-logos\u002Fhiddenlayer.png","hiddenlayer-ai-security","HiddenLayer AI Security Platform","https:\u002F\u002Fhiddenlayer.com\u002F","Model scanning, AI red teaming and runtime protection for AI applications.",[140],{"slug":124,"name":125,"logo_path":126,"roles":141},[142],"reported_by",{"slug":144,"title":145,"body":146,"framework_refs":147,"framework_notes":158},"ai-powered-malware-uses-multi-model-voting-to-autonomously-execute-attacks","AI-Powered Malware Uses Multi-Model Voting to Autonomously Execute Attacks","CLOSEDQUORUM represents a significant evolution in malware design, replacing traditional command-and-control infrastructure with a consensus-based AI decision engine — making it harder to detect through conventional C2 traffic analysis. By delegating attack decisions to AI models, threat actors can reduce their operational footprint and increase adaptability, as the malware can reason about its environment rather than follow static instructions. This matters because traditional defenses — such as blocking known C2 domains or signatures — are less effective against AI-driven, locally autonomous malware. Organizations that rely solely on perimeter and signature-based detection will be especially vulnerable as this technique matures. The theft of credentials, browser passwords, and crypto wallet data means the blast radius of a single infection can be severe and far-reaching.",[148,149,150,151,152,153,154,155,156,157],"CIS Control 10 – Malware Defenses","CIS Control 13 – Network Monitoring and Defense","CIS Control 14 – Security Awareness and Skills Training","NIST SP 800-53 SI-3 – Malicious Code Protection","NIST SP 800-53 AU-6 – Audit Record Review, Analysis, and Reporting","NIST SP 800-53 IR-4 – Incident Handling","NIST SP 800-53 AC-6 – Least Privilege","MITRE ATT&CK T1555 – Credentials from Password Stores","MITRE ATT&CK T1657 – Financial Theft (Crypto Wallets)","GDPR Article 32 – Security of Processing",{}]