CVE-2023-23930 in vantage6
Summary
by MITRE • 10/25/2023
vantage6 is privacy preserving federated learning infrastructure. Versions 4.0.2 and prior use pickle, which has known security issue, as a default serialization module but that has known security issues. All users of vantage6 that post tasks with the default serialization are affected. No patches are currently available, but users may specify JSON serialization as a workaround.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Analysis
by VulDB Data Team • 10/31/2023
The vantage6 platform represents a privacy-preserving federated learning infrastructure designed to enable collaborative machine learning without compromising data privacy. This system facilitates secure computation across distributed datasets by implementing various security mechanisms to protect sensitive information during collaborative model training processes. The platform's architecture relies on specific serialization methods to transmit and store task data between participating nodes within the federated network. However, a critical security vulnerability has been identified in versions 4.0.2 and earlier that fundamentally compromises the system's security posture.
The core technical flaw resides in the platform's default usage of the pickle serialization module, which presents well-documented security vulnerabilities classified under CWE-502. Pickle is a Python-specific binary serialization format that can execute arbitrary code during deserialization processes, making it inherently dangerous when processing untrusted data. This vulnerability allows attackers to craft malicious serialized objects that, when processed by the vantage6 system, can execute arbitrary commands on the target system. The flaw exists because pickle does not perform input validation and can interpret and execute Python bytecode contained within serialized data, creating a direct execution path for remote code injection attacks.
The operational impact of this vulnerability is severe and affects all users who submit tasks using the default serialization method. Attackers who can compromise the communication channels or gain access to the task submission process can exploit this weakness to execute arbitrary code on the vantage6 nodes. This compromises the entire federated learning infrastructure, potentially allowing attackers to access sensitive training data, manipulate model outputs, or establish persistent backdoors within the distributed system. The vulnerability undermines the fundamental security assumptions of the privacy-preserving framework, as it allows attackers to bypass the intended data isolation mechanisms and gain unauthorized access to the computational resources.
Security practitioners should immediately implement the recommended workaround of specifying JSON serialization instead of the default pickle method. JSON serialization provides a safer alternative that does not support arbitrary code execution and maintains the necessary data interchange functionality for task processing. Organizations using vantage6 should also consider implementing network-level monitoring to detect suspicious serialization patterns and establish more robust access controls around task submission endpoints. The vulnerability highlights the importance of secure coding practices and the dangers of using inherently unsafe serialization formats in distributed systems. This issue aligns with ATT&CK technique T1059.006 for remote code execution and demonstrates the critical need for proper input validation and secure data serialization practices in federated learning environments. Until official patches are released, system administrators must ensure that all task submissions utilize the safer JSON serialization method and conduct thorough security reviews of any custom serialization implementations within the platform.