CVE-2025-69220 is a vulnerability classified under CWE-862 (Missing Authorization) and CWE-284 (Improper Access Control) affecting the LibreChat product by danny-avila. LibreChat is a ChatGPT clone that supports additional features including agent-based file contexts and file search capabilities. In versions from 0.8.1-rc2 up to but excluding 0.8.2-rc2, the software fails to enforce proper authorization checks when handling file uploads and file searches related to agents. Specifically, an attacker who is authenticated and knows the agent ID can upload files to or search files within the context of arbitrary agents without having the necessary permissions for those agents. This unauthorized access allows the attacker to change the behavior of these agents by injecting or modifying files, potentially leading to malicious command execution or disruption of agent functionality. The vulnerability requires network access (remote) and low privileges (authenticated user), but no user interaction is needed. The CVSS v3.1 base score is 7.1, reflecting high severity due to the impact on integrity and limited impact on availability, with no confidentiality loss. The scope is changed because the attacker can affect resources beyond their initial privileges. The vulnerability was publicly disclosed on January 7, 2026, and is fixed in LibreChat version 0.8.2-rc2. No exploits have been observed in the wild so far.

For European organizations using LibreChat versions 0.8.1-rc2 to 0.8.2-rc2, this vulnerability poses a significant risk to the integrity and availability of AI agent operations. Attackers with authenticated access can manipulate agent behavior by uploading malicious files, potentially leading to unauthorized actions, data corruption, or disruption of automated workflows relying on these agents. This could affect sectors relying on AI-driven chatbots or automation such as customer service, internal help desks, or data processing. The lack of proper authorization could also lead to lateral movement or privilege escalation within an organization's AI infrastructure. Although confidentiality is not directly impacted, the integrity compromise could result in misinformation or operational failures. The vulnerability's exploitation could disrupt business continuity and damage trust in AI systems. Since no known exploits are currently in the wild, proactive patching is critical to prevent future attacks.

European organizations should immediately upgrade LibreChat installations to version 0.8.2-rc2 or later, where the authorization checks are properly enforced. Until patching is possible, restrict access to LibreChat agents and their file contexts by implementing strict network segmentation and access controls, limiting authenticated user permissions to only necessary agents. Monitor logs for unusual file upload or search activity related to agents, especially from accounts with low privileges. Employ multi-factor authentication to reduce the risk of compromised credentials being used to exploit this vulnerability. Conduct regular audits of agent configurations and file contexts to detect unauthorized changes. Consider deploying runtime application self-protection (RASP) or web application firewalls (WAF) with custom rules to detect and block suspicious file upload attempts targeting agent contexts. Finally, educate users about the importance of credential security to prevent unauthorized authenticated access.