CVE-2022-4261
Nexpose vulnerability analysis and mitigation

Overview

CVE-2022-4261 is a vulnerability discovered in Rapid7 Nexpose and InsightVM versions prior to 6.6.172, where the systems failed to reliably validate the authenticity of update contents. The vulnerability was discovered on November 14, 2022, by Rapid7's product engineering team and was classified as an instance of CWE-494. The issue was assigned a CVSSv3.1 base rating of 4.4 (Medium) and was fixed in the December 7, 2022 release (Rapid7 Blog).

Technical details

The vulnerability involved the internal cryptographic validation of received updates in Nexpose and InsightVM, which are vulnerability management systems used by enterprises to assess and manage vulnerability exposures in their networks. The issue specifically pertained to the mechanism used to validate the source of update files, which was found to be unreliable (Rapid7 Blog).

Impact

The impact of this vulnerability was considered relatively limited due to the complexity of exploitation. If successfully exploited, an attacker could introduce new malicious functionality to Nexpose through compromised updates. However, the attacker would need to already have a privileged position on the network or local machine, making the practical impact largely academic since such an adversary would likely have easier methods of compromising the target network (Rapid7 Blog).

Mitigation and workarounds

The vulnerability was resolved in version 6.6.172 released on December 7, 2022. For administrators concerned about being targeted during updates, Rapid7 recommended disabling automatic updates and using the documented 'Managing Updates without an Internet Connection' procedure after manually validating the update package's authenticity. Disabling automatic updates completely removes the risk of exploitation. Most administrators using automated updates were advised to apply updates on their established schedules or as soon as convenient (Rapid7 Blog).

Additional resources


SourceThis report was generated using AI

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