Vulnerability DatabaseGHSA-29fh-xcjr-p7rx

GHSA-29fh-xcjr-p7rx
JavaScript vulnerability analysis and mitigation

Overview

The vulnerability GHSA-29fh-xcjr-p7rx affects the npm package web3-eht, which was identified as a malicious package. The issue was discovered and reviewed on August 31, 2020, published to the GitHub Advisory Database on September 3, 2020, and last updated on January 9, 2023. This critical severity vulnerability affects all versions of the package (>= 0.0.0) with no patched versions available (GitHub Advisory).

Technical details

The vulnerability has been assigned a Critical severity rating with a CVSS score of 9.1. The CVSS v3 base metrics indicate a Network attack vector, Low attack complexity, No privileges required, No user interaction needed, Unchanged scope, High impact on both Confidentiality and Integrity, and No impact on Availability. The vulnerability is associated with CWE-506 (GitHub Advisory).

Impact

The malicious package was specifically designed to find and exfiltrate cryptocurrency wallets. Any computer with this package installed or running should be considered fully compromised, with potential unauthorized access to all secrets and keys stored on the affected system (GitHub Advisory).

Exploitability

The package is inherently malicious, requiring no special exploitation as its malicious functionality is built into all versions. The low attack complexity and absence of required privileges or user interaction make this particularly dangerous (GitHub Advisory).

Mitigation and workarounds

Due to the malicious nature of the package, there are no patches available. The recommended mitigation steps include: immediately rotating all secrets and keys from a different computer, removing the package from affected systems, and considering that full system compromise may have occurred. It's important to note that removing the package may not eliminate all malicious software resulting from its installation (GitHub Advisory).

Additional resources


SourceThis report was generated using AI

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