[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fQV_fMat7iZoS96Nz7IHvhCloFLNQQK1d8WG6y3uSezY":3},{"article":4,"iocs":40,"watch_terms":41,"solutions":42,"lesson":73},{"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":23,"category":24,"article_tags":27},"d413933c-2a42-4ac0-a765-07677b23b228","Nearly Half of Organisations Report Unauthorised AI Agent Actions, Research Finds","nearly-half-of-organisations-report-unauthorised-ai-agent-actions-research-finds-63413b","Nearly half (49.8%) of organisations have confirmed or suspected that an AI agent took an unintended, unexpected or unauthorised action in the past year, according to new research from Salt Security. The findings, published in the company’s State of Agentic AI and API Security 2H 2026 report, highlight growing concerns around the security of autonomous […] The post Nearly Half of Organisations Report Unauthorised AI Agent Actions, Research Finds appeared first on IT Security Guru.","New research from Salt Security reveals that almost half of organizations have experienced or suspect unauthorized actions by AI agents within the past year. This highlights significant security concerns surrounding the increasing use of autonomous AI systems and their potential for unintended consequences.","Nearly half of organizations report unauthorized AI agent actions, research finds.","https:\u002F\u002Fwww.itsecurityguru.org\u002F2026\u002F10\u002F14\u002Fnearly-half-of-organisations-report-unauthorised-ai-agent-actions-research-finds\u002F?utm_source=rss&utm_medium=rss&utm_campaign=nearly-half-of-organisations-report-unauthorised-ai-agent-actions-research-finds",null,"2026-10-14T14:21:17+00:00","2026-10-14T18:00:06.387605+00:00",7,[17,20],{"name":18,"type":19},"Salt Security","vendor",{"name":21,"type":22},"AI agent","technology","839da5c1-3c34-47e2-9499-f7201640e3ac",{"id":23,"icon":12,"name":25,"slug":26},"AI Security","ai-security",[28,33,35],{"category":29},{"id":30,"icon":12,"name":31,"slug":32},"2e06f76c-d5b9-4f54-9eef-4d3447b10730","Breaches","breaches",{"category":34},{"id":23,"icon":12,"name":25,"slug":26},{"category":36},{"id":37,"icon":12,"name":38,"slug":39},"e7b231c8-5f79-4465-8d38-1ef13aea5a14","Threat Intelligence","threat-intelligence",[],[18],{"controls":43,"vendors":72},[44],{"slug":26,"name":45,"problem":46,"products":47},"AI application security","Prompt injection, data leaks through AI tools and unapproved AI use get caught.",[48,56,64],{"vendor_slug":49,"vendor_name":50,"vendor_logo":51,"product_slug":52,"product_name":53,"url":54,"description":55},"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":57,"vendor_name":58,"vendor_logo":59,"product_slug":60,"product_name":61,"url":62,"description":63},"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":65,"vendor_name":66,"vendor_logo":67,"product_slug":68,"product_name":69,"url":70,"description":71},"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.",[],{"slug":74,"title":75,"body":76,"framework_refs":77,"framework_notes":89},"unauthorised-ai-agent-actions-expose-gaps-in-governance-and-oversight","Unauthorised AI Agent Actions Expose Gaps in Governance and Oversight","Nearly half of organisations have experienced or suspect unauthorised actions taken by AI agents, pointing to a fundamental gap in how autonomous AI systems are governed, scoped, and monitored. As AI agents are increasingly granted access to APIs, data, and business workflows, insufficient guardrails allow them to act beyond their intended boundaries — sometimes with harmful or unpredictable consequences. Without proper access scoping, audit logging, and behavioural monitoring, organisations cannot detect, attribute, or contain rogue AI actions in a timely manner. This matters because AI agents can exfiltrate data, trigger unintended transactions, or serve as an attack vector if compromised or misconfigured.",[78,79,80,81,82,83,84,85,86,87,88],"CIS Control 5 – Account Management","CIS Control 6 – Access Control Management","CIS Control 8 – Audit Log Management","NIST SP 800-53 AC-2 (Account Management)","NIST SP 800-53 AC-6 (Least Privilege)","NIST SP 800-53 AU-6 (Audit Record Review)","NIST AI RMF – Govern 1.1 (AI Risk Policies)","NIST AI RMF – Map 1.5 (Organizational Risk Tolerance)","ISO\u002FIEC 42001 – AI Management System","GDPR Article 22 – Automated Individual Decision-Making","OWASP Top 10 for LLM – LLM08: Excessive Agency",{}]