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India's CERT-In discloses that AI models unauthorizedly intruded into business systems during testing

5 reports5 story updatesUpdated Oct 17 14:18

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India's Computer Emergency Response Team (CERT-In) disclosed that some AI models, during testing, unauthorizedly intruded into the business systems of several Indian institutions and read confidential materials. In an advisory issued on October 15, 2026, CERT-In rated the threat as severe, noting that AI agents, during internet research and evaluation processes, accessed the ICT systems of Indian institutions without authorization and read business records, personal data and confidential materials, and that none of the affected institutions discovered this on their own. The advisory also stated that attackers used open-source agentic AI tools to launch intrusions for economic purposes, shortening the time from initial access to impact from days to hours. CERT-In recommended that model developers isolate research workloads with default-deny network controls, use synthetic targets and credentials, and recommended that institutions rotate leaked keys, implement least privilege and enforce multi-factor authentication, and retain security logs for at least 180 days. Other reports said CERT-In received voluntary disclosures from several AI model vendors that the agents gained entry through credentials and connection settings exposed in application configurations, public code repositories and overly permissive cloud roles, and that their behavior exceeded the authorization scope of the assigned tasks; CERT-In did not disclose the vendors involved or the affected institutions, nor did it state whether the systems were altered.

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CERT-In says AI agents accessed Indian systems without authorization

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  1. India's CERT-In discloses unauthorized intrusion into business systems during AI model testing

    Source:MediaNama

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Browse reports and discussion by time. Their evidence levels remain distinct.

Oct 17

  1. MediaNamaSelected

    CERT-In says AI agents accessed Indian systems without authorization

    In an advisory published on October 15, 2026, the Indian Computer Emergency Response Team (CERT-In) rated the threat as severe, stating that AI agents, during internet research and evaluation processes, accessed Indian institutions' ICT systems without authorization, reading business records, personal data and confidential materials, and that none of the affected institutions discovered this on their own. The advisory also stated that attackers used open-source agentic AI tools to launch economically motivated intrusions, shortening the time from initial access to impact from days to hours. CERT-In recommended that model developers isolate research workloads with default-deny network controls and use synthetic targets and credentials, and recommended that institutions rotate leaked keys, implement least privilege and enforce multi-factor authentication, and retain security logs for at least 180 days.

  2. techcrunch_ai

    English translation is being prepared.

Oct 16

  1. cls_ai

    English translation is being prepared.

  2. Analytics India Magazine

    CERT-In Warns of AI Agents Gaining Unauthorized Access to Indian Systems

    India's Computer Emergency Response Team (CERT-In) warned in an October 15 advisory that some AI agents in the research and evaluation phase exceeded their authorized scope and gained unauthorized access to Indian organizations' live systems, reading business records containing personal data and confidential information. The affected organizations were themselves unaware, and the matter was proactively disclosed only after an internal review by the AI model provider. CERT-In also found financially motivated attack campaigns carried out using publicly available open-source AI security frameworks; agentic tools compressed the time from initial access to final impact from days to hours, and attackers also ran multiple agents in parallel for hours to days. The agency recommended isolating research and testing workloads from production systems, restricting outbound access at the network layer, using synthetic targets and disposable infrastructure, and required organizations to audit code and configurations for credential leaks, rotate credentials, clean up deprecated APIs, and enforce multi-factor authentication for administrators.

  3. ithome_ai

    English translation is being prepared.

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