Python, Directory Traversal, CVE-2025-56427 (High)

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How the CVE Works

The vulnerability exists within the `_download_file_or_dir` function of the ComposioHQ Python package, version 0.7.20. This function is designed to handle file operations but improperly validates or sanitizes user-supplied input for file or directory paths. An attacker can exploit this by crafting a request with path traversal sequences (such as ../../). When the malicious input is processed by the vulnerable function, it fails to restrict access to the intended directory. This allows the attacker to traverse the server’s file system and read sensitive files located outside the application’s root directory. The attack can be performed remotely over a network (Attack Vector: Network) without requiring any privileges (Privileges Required: None) or user interaction (User Interaction: None), and has low attack complexity, making exploitation straightforward.

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Platform: Python (PyPI)
Version: 0.7.20
Vulnerability: Directory Traversal
Severity: High
date: 2025-12-04

Prediction: 2025-12-18

What Undercode Say

Check installed version
pip show composio
Upgrade to a patched version (post v0.7.20)
pip install --upgrade composio
Example of a vulnerable path manipulation
requested_path = user_input e.g., "../../../etc/passwd"
Flawed function call leading to traversal
_download_file_or_dir(requested_path) CWE-22, CWE-200

How Exploit

1. Attacker identifies endpoint using `_download_file_or_dir`.

  1. Crafts HTTP request with traversal sequences (e.g., ?file=../../secret.conf).

3. Sends request to target server.

  1. Server processes path, retrieves, and returns sensitive file content.
  2. Attacker extracts confidential data like configs, keys, or user data.

Protection from this CVE

  • Apply input validation.
  • Upgrade ComposioHQ package.
  • Use security controls.
  • Implement strict access policies.
  • Employ a web application firewall.
  • Conduct code audits.

Impact

  • Unauthorized sensitive information disclosure.
  • High confidentiality impact.
  • Potential data breach.
  • System compromise risk.
  • Compliance violations.

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Sources:

Reported By: nvd.nist.gov
Extra Source Hub:
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