[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fDOIKWcaIy0e_bzF73jlYA6w7-SWQrP_vbJZLAUksCPo":3},{"article":4,"iocs":54,"watch_terms":55,"solutions":56,"lesson":150},{"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":31,"category":32,"article_tags":36},"88640b9c-6425-4352-a16b-8720e7970bfd","US says Chinese firms extracted billions of tokens from frontier AI models","us-says-chinese-firms-extracted-billions-of-tokens-from-frontier-ai-models-c6ee9d","U.S. cybersecurity and intelligence agencies say that six Chinese AI companies conducted industrial-scale distillation attacks on American frontier AI models since at least late 2024. [...]","US intelligence agencies have identified six Chinese AI companies engaging in industrial-scale \"distillation attacks\" against American frontier AI models. These firms, including DeepSeek and Moonshot AI, allegedly extracted billions of data tokens by making millions of API requests, significantly reducing their own AI development costs and timelines. The US government suspects Chinese government awareness of these operations, which leverage sophisticated techniques to bypass security measures.","Chinese firms accused of stealing billions of AI model tokens via industrial-scale distillation attacks.","https:\u002F\u002Fwww.bleepingcomputer.com\u002Fnews\u002Fsecurity\u002Fus-says-chinese-firms-extracted-billions-of-tokens-from-frontier-ai-models\u002F","https:\u002F\u002Fwww.bleepstatic.com\u002Fcontent\u002Fhl-images\u002F2026\u002F09\u002F09\u002Fdistillation.jpg","2026-09-09T16:48:33+00:00","2026-09-09T18:00:35.720553+00:00",8,[17,20,23,25,27,29],{"name":18,"type":19},"Chinese AI companies","threat_actor",{"name":21,"type":22},"CISA","vendor",{"name":24,"type":22},"NSA",{"name":26,"type":22},"FBI",{"name":28,"type":22},"OpenAI",{"name":30,"type":22},"Google","6cbdd207-aaa1-4176-9534-e156b125e917",{"id":31,"icon":33,"name":34,"slug":35},null,"Nation-state","nation-state",[37,39,44,49],{"category":38},{"id":31,"icon":33,"name":34,"slug":35},{"category":40},{"id":41,"icon":33,"name":42,"slug":43},"839da5c1-3c34-47e2-9499-f7201640e3ac","AI Security","ai-security",{"category":45},{"id":46,"icon":33,"name":47,"slug":48},"c5c77cdb-f7d7-4990-9436-c81dcbff1163","Policy","policy",{"category":50},{"id":51,"icon":33,"name":52,"slug":53},"e7b231c8-5f79-4465-8d38-1ef13aea5a14","Threat Intelligence","threat-intelligence",[],[30,21,24],{"controls":57,"vendors":144},[58,87,116],{"slug":59,"name":60,"problem":61,"products":62},"identity-threat-detection","Identity threat detection and response (ITDR)","Attackers who log in with real, stolen credentials get noticed.",[63,71,79],{"vendor_slug":64,"vendor_name":65,"vendor_logo":66,"product_slug":67,"product_name":68,"url":69,"description":70},"acalvio","Acalvio","\u002Fvendor-logos\u002Facalvio.png","shadowplex-identity-protection","ShadowPlex Identity Protection","https:\u002F\u002Fwww.acalvio.com\u002Fproducts\u002Fidentity-protection\u002F","Decoy accounts and credentials that expose identity attacks and credential misuse early.",{"vendor_slug":72,"vendor_name":73,"vendor_logo":74,"product_slug":75,"product_name":76,"url":77,"description":78},"huntress","Huntress","\u002Fvendor-logos\u002Fhuntress.png","managed-itdr","Huntress Managed ITDR","https:\u002F\u002Fwww.huntress.com\u002Fplatform\u002Fmanaged-itdr","Managed detection of suspicious activity in Microsoft 365 and Entra ID.",{"vendor_slug":80,"vendor_name":81,"vendor_logo":82,"product_slug":83,"product_name":84,"url":85,"description":86},"microsoft","Microsoft","\u002Fvendor-logos\u002Fmicrosoft.png","defender-for-identity","Microsoft Defender for Identity","https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fsecurity\u002Fbusiness\u002Fsiem-and-xdr\u002Fmicrosoft-defender-for-identity","Detects attacks against on-premises Active Directory and hybrid identities.",{"slug":88,"name":89,"problem":90,"products":91},"data-loss-prevention","Data loss prevention (DLP)","Sensitive data cannot quietly leave by email, upload, USB stick or AI tool.",[92,100,108],{"vendor_slug":93,"vendor_name":94,"vendor_logo":95,"product_slug":96,"product_name":97,"url":98,"description":99},"netskope","Netskope","\u002Fvendor-logos\u002Fnetskope.png","netskope-dlp","Netskope DLP","https:\u002F\u002Fwww.netskope.com\u002Fproducts\u002Fdata-loss-prevention","Data loss prevention for web, cloud apps, AI tools and endpoints.",{"vendor_slug":101,"vendor_name":102,"vendor_logo":103,"product_slug":104,"product_name":105,"url":106,"description":107},"forcepoint","Forcepoint","\u002Fvendor-logos\u002Fforcepoint.png","forcepoint-dlp","Forcepoint DLP","https:\u002F\u002Fwww.forcepoint.com\u002Fproduct\u002Fdlp-data-loss-prevention","Data loss prevention for endpoints, network, email and cloud applications.",{"vendor_slug":109,"vendor_name":110,"vendor_logo":111,"product_slug":112,"product_name":113,"url":114,"description":115},"proofpoint","Proofpoint","\u002Fvendor-logos\u002Fproofpoint.png","enterprise-dlp","Proofpoint Enterprise DLP","https:\u002F\u002Fwww.proofpoint.com\u002Fus\u002Fproducts\u002Fdata-loss-prevention","Data loss prevention across email, cloud and endpoints.",{"slug":43,"name":117,"problem":118,"products":119},"AI application security","Prompt injection, data leaks through AI tools and unapproved AI use get caught.",[120,128,136],{"vendor_slug":121,"vendor_name":122,"vendor_logo":123,"product_slug":124,"product_name":125,"url":126,"description":127},"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.",{"vendor_slug":129,"vendor_name":130,"vendor_logo":131,"product_slug":132,"product_name":133,"url":134,"description":135},"boomi","Boomi","\u002Fvendor-logos\u002Fboomi.png","boomi-agentstudio","Boomi Agentstudio","https:\u002F\u002Fboomi.com\u002Fplatform\u002Fagentstudio\u002F","Agent builder whose Agent Control Tower registers and monitors Boomi agents and agents on Amazon Bedrock, Microsoft Copilot and other platforms, keeps audit logs and can switch agents off where the provider allows it.",{"vendor_slug":137,"vendor_name":138,"vendor_logo":139,"product_slug":140,"product_name":141,"url":142,"description":143},"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.",[145],{"slug":146,"name":30,"logo_path":147,"roles":148},"google","\u002Fvendor-logos\u002Fgoogle.png",[149],"affected",{"slug":151,"title":152,"body":153,"framework_refs":154,"framework_notes":169},"chinese-firms-drain-us-ai-models-via-industrial-scale-api-abuse","Chinese Firms Drain US AI Models via Industrial-Scale API Abuse","Six Chinese AI companies allegedly conducted 'distillation attacks' by making millions of API requests to extract billions of tokens from US frontier AI models, effectively stealing the intellectual value embedded in those systems. The root failure lies in insufficient access controls and rate-limiting on API endpoints, combined with inadequate monitoring to detect anomalous usage patterns indicative of systematic data harvesting. This matters because AI model outputs encode enormous R&D investment, and bulk extraction dramatically lowers barriers for adversaries to replicate cutting-edge capabilities without equivalent cost or time. The incident illustrates that AI APIs must be treated as high-value data assets requiring the same protective controls applied to proprietary databases or source code.",[155,156,157,158,159,160,161,162,163,164,165,166,167,168],"CIS Control 3: Data Protection","CIS Control 6: Access Control Management","CIS Control 8: Audit Log Management","CIS Control 13: Network Monitoring and Defense","NIST SP 800-53 AC-2: Account Management","NIST SP 800-53 AC-17: Remote Access","NIST SP 800-53 AU-6: Audit Record Review, Analysis, and Reporting","NIST SP 800-53 SI-4: System Monitoring","NIST AI RMF: GOVERN 1.1, MAP 5.1 (AI-specific risk management)","NIST SP 800-171 3.1.1: Limit system access to authorized users","EO 14110 (Safe, Secure, and Trustworthy AI): API security obligations for frontier model providers","GDPR Article 25: Data Protection by Design (applicable to EU-exposed APIs)","ITIL Service Management: Access Management process controls","MITRE ATLAS AML.T0049: API Querying for Model Extraction",{}]