CVE-2026-22871

Jan. 14, 2026, 4:25 p.m.

8.7
High

Description

GuardDog is a CLI tool to identify malicious PyPI packages. Prior to 2.7.1, there is a path traversal vulnerability exists in GuardDog's safe_extract() function that allows malicious PyPI packages to write arbitrary files outside the intended extraction directory, leading to Arbitrary File Overwrite and Remote Code Execution on systems running GuardDog. This vulnerability is fixed in 2.7.1.

Product(s) Impacted

Vendor Product Versions
Guarddog
  • Guarddog
  • <*

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-22
Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a guarddog guarddog <* 2.7.1 / / / / / /

CVSS Score

8.7 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: Jan. 13, 2026, 9:15 p.m.
Last Modified: Jan. 14, 2026, 4:25 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.