[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fN87-_LXnRRrlTzW1MpQr5Ef8QOAHHqEbZMZ2G4QPHQM":3},{"article":4,"iocs":54,"watch_terms":55,"solutions":56,"lesson":92},{"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},"55e042ef-25f8-4c6c-96fe-bc57edd4b091","Obsidian expands AI agent security with runtime policy enforcement","obsidian-expands-ai-agent-security-with-runtime-policy-enforcement-a6febb","Obsidian Security has announced its Runtime Policy Decision Engine, giving security teams centralized control over AI agent actions before they run. Building on Obsidian’s extensive AI agent discovery and governance coverage, the engine uses context about who is behind an agent, its access and the third-party applications involved to allow or block actions, or require human approval where supported. Context from your apps, identity systems and your own labels feeds one Policy Decision Engine; each … More → The post Obsidian expands AI agent security with runtime policy enforcement appeared first on Help Net Security.","Obsidian Security has introduced its Runtime Policy Decision Engine to provide centralized control over AI agent actions before they execute. The engine leverages context about the agent's operator, its access privileges, and involved third-party applications to permit, deny, or require human approval for actions. This new capability aims to mitigate risks associated with employees using AI platforms for coding and workflow initiation, as well as risks from vendors embedding agents into their products.","Obsidian Security launches Runtime Policy Decision Engine for AI agent action control.","https:\u002F\u002Fwww.helpnetsecurity.com\u002F2026\u002F11\u002F11\u002Fobsidian-security-runtime-policy-decision-engine\u002F","https:\u002F\u002Fimg.helpnetsecurity.com\u002Fwp-content\u002Fuploads\u002F2024\u002F11\u002F28150559\u002Fhns-large_logo.webp","2026-11-11T08:44:50+00:00","2026-11-11T09:00:21.588076+00:00",7,[17,20,23,25,27,29],{"name":18,"type":19},"Runtime Policy Decision Engine","product",{"name":21,"type":22},"Obsidian Security","vendor",{"name":24,"type":19},"Microsoft Copilot",{"name":26,"type":19},"OpenAI Codex",{"name":28,"type":19},"Claude Code and Cowork",{"name":30,"type":19},"Amazon Bedrock","839da5c1-3c34-47e2-9499-f7201640e3ac",{"id":31,"icon":33,"name":34,"slug":35},null,"AI Security","ai-security",[37,42,44,49],{"category":38},{"id":39,"icon":33,"name":40,"slug":41},"02371804-cf6d-4449-98de-f1a2d4d9b266","Tools","tools",{"category":43},{"id":31,"icon":33,"name":34,"slug":35},{"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},"c70f3a41-2f0c-4608-870d-b8cbcd8be076","Cloud Security","cloud-security",[],[21,18,24],{"controls":57,"vendors":86},[58],{"slug":35,"name":59,"problem":60,"products":61},"AI application security","Prompt injection, data leaks through AI tools and unapproved AI use get caught.",[62,70,78],{"vendor_slug":63,"vendor_name":64,"vendor_logo":65,"product_slug":66,"product_name":67,"url":68,"description":69},"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":71,"vendor_name":72,"vendor_logo":73,"product_slug":74,"product_name":75,"url":76,"description":77},"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":79,"vendor_name":80,"vendor_logo":81,"product_slug":82,"product_name":83,"url":84,"description":85},"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.",[87],{"slug":88,"name":21,"logo_path":89,"roles":90},"obsidian-security","\u002Fvendor-logos\u002Fobsidian-security.png",[91],"reported_by",{"slug":93,"title":94,"body":95,"framework_refs":96,"framework_notes":102},"ai-agent-actions-need-runtime-policy-controls-before-they-execute","AI Agent Actions Need Runtime Policy Controls Before They Execute","As AI agents are increasingly embedded in employee workflows and vendor products, they can take consequential actions—like writing code or initiating processes—with little human oversight. The core risk is that these agents may operate with excessive privileges or act on behalf of users in ways that bypass traditional access controls. Without a policy enforcement layer that evaluates context before execution, a misconfigured or compromised agent can cause significant harm. This matters because both internally adopted AI platforms and third-party vendor-embedded agents represent expanding attack surfaces that existing identity and access management systems were not designed to govern.",[97,98,99,100,101],"NIST SP 800-53 AC-6: Least Privilege","NIST SP 800-53 AC-3: Access Enforcement","NIS2 Article 21(2)(d)","NIST CSF 2.0 PR.AA-05: Access permissions, entitlements, and authorizations are defined in a policy, managed, enforced, and reviewed","CIS Control 6: Access Control Management",{"NIS2 Article 21(2)(d)":103,"NIST SP 800-53 AC-6: Least Privilege":104,"NIST SP 800-53 AC-3: Access Enforcement":105,"CIS Control 6: Access Control Management":106,"NIST CSF 2.0 PR.AA-05: Access permissions, entitlements, and authorizations are defined in a policy, managed, enforced, and reviewed":107},"NIS2 supply chain security requirements apply here because vendor-embedded AI agents introduce third-party risk that organizations must assess and control before those agents can act within their environments.","AC-6 requires that processes and users operate with only the minimum necessary privileges, which directly addresses the risk of AI agents being granted excessive access to execute unauthorized actions.","AC-3 mandates that access control policies be enforced at system boundaries before actions are permitted, aligning directly with the need for runtime policy decisions on AI agent actions.","CIS Control 6 calls for managing access rights and permissions across all users and systems, which extends to AI agent identities that must be governed with the same rigor as human accounts.","This category directly covers the need to define and enforce authorization policies for entities—including AI agents—before they are permitted to take actions on organizational resources."]