NewsPublished 15 Jan 2026

New ‘Reprompt’ Attack Silently Siphons Microsoft Copilot Data

Source SecurityWeek

Description

The attack bypassed Copilot’s data leak protections and allowed for session exfiltration even after the Copilot chat was closed. The post New ‘Reprompt’ Attack Silently Siphons Microsoft Copilot Data appeared first on SecurityWeek .

Impact

For European organizations, the 'Reprompt' attack poses a risk primarily to the confidentiality of sensitive data processed through Microsoft Copilot. Organizations relying on Copilot for document drafting, code generation, or data analysis could inadvertently expose proprietary or personal data if the attack is exploited. The silent nature of the exfiltration means that traditional monitoring might not detect the breach promptly, increasing the window of exposure. This could lead to data privacy violations under GDPR, reputational damage, and potential regulatory penalties. The attack does not appear to affect system integrity or availability directly but compromises trust in AI-assisted workflows. Sectors such as finance, healthcare, and government, which often use Microsoft enterprise tools extensively, are particularly vulnerable. The impact is amplified in environments where session management and endpoint security controls are weak or inconsistent.

Defensive guidance

To mitigate the 'Reprompt' attack, organizations should: 1) Monitor for unusual data flows from Copilot sessions, especially after chat closure, using advanced network and endpoint detection tools. 2) Enforce strict session termination policies ensuring that all session tokens and background processes are fully invalidated upon chat closure. 3) Apply the principle of least privilege to Copilot access, limiting data exposure to only necessary users and contexts. 4) Collaborate with Microsoft to obtain and deploy any patches or updates addressing this vulnerability as soon as they become available. 5) Conduct security reviews of AI assistant integrations, focusing on session lifecycle and data handling practices. 6) Educate users about the risks of sensitive data input into AI tools and encourage minimizing exposure of confidential information. 7) Implement data loss prevention (DLP) solutions tailored to monitor AI tool interactions. These steps go beyond generic advice by focusing on session management integrity and proactive monitoring specific to AI assistant environments.

References

securityweek.com/new-reprompt-attack-silently-siphons-microsoft-copilot-data/ (opens in a new tab)

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Description

AI analysisMachine-generated, updated 15 Jan 2026, 12:17 UTC

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