[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fmlDUPBZjX8v7drKVEtBmwDX8sWgU0LMncm8W8pR-79g":3},{"article":4,"iocs":49,"watch_terms":50,"solutions":51,"lesson":136},{"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":28,"category":29,"article_tags":33},"b3c1712d-d821-4c73-b181-22d19dab8fbb","Think You’ve Eliminated Chinese AI? Check the Model’s Lineage, Cisco Says","think-you-ve-eliminated-chinese-ai-check-the-model-s-lineage-cisco-says-6e51ba","New research shows that country-of-origin labels can obscure an AI model’s upstream dependencies, inherited behaviors and potential security risks. The post Think You’ve Eliminated Chinese AI? Check the Model’s Lineage, Cisco Says appeared first on SecurityWeek.","Cisco research reveals that country-of-origin labels for AI models are insufficient for assessing security risks. AI models can inherit behaviors and biases from upstream models, regardless of their stated origin, creating a 'provenance entanglement' that mirrors software supply chain vulnerabilities. This necessitates deeper due diligence beyond publisher identity, including lineage, training dependencies, and behavioral analysis.","AI model lineage can obscure origin and inherited risks, Cisco research finds.","https:\u002F\u002Fwww.securityweek.com\u002Fthink-youve-eliminated-chinese-ai-check-the-models-lineage-cisco-says\u002F","https:\u002F\u002Fwww.securityweek.com\u002Fwp-content\u002Fuploads\u002F2026\u002F07\u002FAI-artificial-intelligence-model-frontier.webp","2026-08-28T10:30:00+00:00","2026-08-28T12:00:30.550228+00:00",7,[17,20,23,26],{"name":18,"type":19},"Cisco","vendor",{"name":21,"type":22},"AI","technology",{"name":24,"type":25},"Nemotron","product",{"name":27,"type":25},"Qwen","e7b231c8-5f79-4465-8d38-1ef13aea5a14",{"id":28,"icon":30,"name":31,"slug":32},null,"Threat Intelligence","threat-intelligence",[34,39,44],{"category":35},{"id":36,"icon":30,"name":37,"slug":38},"26b0b636-0e31-4db1-bffb-61bdf9f20a58","Supply Chain","supply-chain",{"category":40},{"id":41,"icon":30,"name":42,"slug":43},"839da5c1-3c34-47e2-9499-f7201640e3ac","AI Security","ai-security",{"category":45},{"id":46,"icon":30,"name":47,"slug":48},"c5c77cdb-f7d7-4990-9436-c81dcbff1163","Policy","policy",[],[18,24,27],{"controls":52,"vendors":130},[53,81,106],{"slug":32,"name":54,"problem":55,"products":56},"Threat intelligence","Attack campaigns reach your sector, suppliers or software before your team hears about them.",[57,65,73],{"vendor_slug":58,"vendor_name":59,"vendor_logo":60,"product_slug":61,"product_name":62,"url":63,"description":64},"google","Google","\u002Fvendor-logos\u002Fgoogle.png","google-threat-intelligence","Google Threat Intelligence","https:\u002F\u002Fcloud.google.com\u002Fsecurity\u002Fproducts\u002Fthreat-intelligence","Threat intelligence from Mandiant's frontline investigations, Google's threat analysts, open sources and Google's own visibility, in one service.",{"vendor_slug":66,"vendor_name":67,"vendor_logo":68,"product_slug":69,"product_name":70,"url":71,"description":72},"dataminr","Dataminr","\u002Fvendor-logos\u002Fdataminr.png","dataminr-threat-intelligence","Dataminr Threat Intelligence","https:\u002F\u002Fwww.dataminr.com\u002Fproducts\u002Fcyber-defense\u002Fthreat-intelligence\u002F","Real-time alerts on emerging cyber threats, exploited vulnerabilities and attacks relevant to your organisation, detected with AI across a large set of public data sources.",{"vendor_slug":74,"vendor_name":75,"vendor_logo":76,"product_slug":77,"product_name":78,"url":79,"description":80},"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.",{"slug":43,"name":82,"problem":83,"products":84},"AI application security","Prompt injection, data leaks through AI tools and unapproved AI use get caught.",[85,93,101],{"vendor_slug":86,"vendor_name":87,"vendor_logo":88,"product_slug":89,"product_name":90,"url":91,"description":92},"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":94,"vendor_name":95,"vendor_logo":96,"product_slug":97,"product_name":98,"url":99,"description":100},"palo-alto-networks","Palo Alto Networks","\u002Fvendor-logos\u002Fpalo-alto-networks.png","prisma-airs","Prisma AIRS","https:\u002F\u002Fwww.paloaltonetworks.com\u002Fai-security\u002Fprisma-airs","Security for AI applications, models and agents, including runtime protection against prompt injection.",{"vendor_slug":86,"vendor_name":87,"vendor_logo":88,"product_slug":102,"product_name":103,"url":104,"description":105},"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.",{"slug":107,"name":108,"problem":109,"products":110},"software-supply-chain","Software supply chain security","Malicious and vulnerable open-source packages are caught before they ship.",[111,119,124],{"vendor_slug":112,"vendor_name":113,"vendor_logo":114,"product_slug":115,"product_name":116,"url":117,"description":118},"jfrog","JFrog","\u002Fvendor-logos\u002Fjfrog.png","jfrog-xray","JFrog Xray","https:\u002F\u002Fjfrog.com\u002Fxray\u002F","Software composition analysis and SBOM generation for artifacts.",{"vendor_slug":112,"vendor_name":113,"vendor_logo":114,"product_slug":120,"product_name":121,"url":122,"description":123},"jfrog-curation","JFrog Curation","https:\u002F\u002Fjfrog.com\u002Fcuration\u002F","Blocks malicious and risky open-source packages before they enter your repositories.",{"vendor_slug":125,"vendor_name":126,"vendor_logo":127,"product_slug":125,"product_name":126,"url":128,"description":129},"socket","Socket","\u002Fvendor-logos\u002Fsocket.png","https:\u002F\u002Fsocket.dev\u002F","Detects and blocks malicious and risky packages in npm, PyPI and other ecosystems.",[131],{"slug":132,"name":18,"logo_path":133,"roles":134},"cisco","\u002Fvendor-logos\u002Fcisco.png",[135],"reported_by",{"slug":137,"title":138,"body":139,"framework_refs":140,"framework_notes":151},"ai-model-lineage-exposes-hidden-supply-chain-risks","AI Model Lineage Exposes Hidden Supply Chain Risks","Cisco's research highlights that simply verifying the stated country of origin or publisher of an AI model is insufficient for assessing its true security posture. AI models trained on or fine-tuned from upstream base models can inherit embedded behaviors, biases, and potential backdoors from those foundational models — a phenomenon dubbed 'provenance entanglement.' This mirrors well-understood software supply chain vulnerabilities, where a trusted package can silently carry malicious dependencies. Organizations that assume a rebranded or domestically published AI model is free of foreign influence are exposed to risks they may not even be aware of. Rigorous lineage analysis and behavioral testing must become standard practice before deploying any AI model in sensitive environments.",[141,142,143,144,145,146,147,148,149,150],"NIST AI RMF: GOVERN 1.6 (Policies for AI risk)","NIST AI RMF: MAP 5.2 (AI supply chain risks)","NIST SP 800-161r1: Supply Chain Risk Management","CIS Control 15: Service Provider Management","CIS Control 16: Application Software Security","NIST CSF: ID.SC-2 (Suppliers and third-party partners assessed for risk)","NIST CSF: ID.SC-4 (Suppliers evaluated using audits and assessments)","ISO\u002FIEC 42001: AI Management System (Clause 6.1 – Risk Assessment)","EU AI Act: Article 13 (Transparency and provision of information to deployers)","SLSA Framework: Supply chain integrity levels for software and model artifacts",{}]