CVE-2025-61765
Python vulnerability analysis and mitigation

Overview

A remote code execution vulnerability (CVE-2025-61765) was discovered in python-socketio versions prior to 5.14.0. The vulnerability affects multi-server deployments where attackers can execute arbitrary Python code through malicious pickle deserialization if they have gained access to the message queue used for internal server communications. The issue was disclosed on October 3, 2025, and affects versions from 0.8.0 to versions before 5.14.0 (GitHub Advisory).

Technical details

The vulnerability occurs when Socket.IO servers are configured to use a message queue backend (such as Redis) for inter-server communication. Messages between servers are encoded using Python's pickle module, and when a server receives these messages, it immediately deserializes them using pickle.loads() without proper validation. An attacker with access to the message queue can exploit this by sending a crafted pickle payload that executes arbitrary code during deserialization through Python's reduce method. The vulnerability has been assigned a CVSS v3.1 score of 6.4 (Moderate) with the vector string CVSS:3.1/AV:A/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:L (GitHub Advisory).

Impact

The vulnerability only affects deployments with a compromised message queue. When successfully exploited, it allows attackers to execute arbitrary code in the context of the Socket.IO server process, with the same privileges as the server. Single-server systems that do not use a message queue and multi-server systems with properly secured message queues are not affected by this vulnerability (GitHub Advisory).

Mitigation and workarounds

Users should upgrade to python-socketio version 5.14.0 or newer, which removes the pickle module and replaces it with safer JSON encoding for inter-server messaging. Additionally, standard security practices should be followed in the deployment of the message queue to prevent unauthorized access (GitHub Advisory).

Additional resources


SourceThis report was generated using AI

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