CVE-2025-67720

Dec. 11, 2025, 2:16 a.m.

6.5
Medium

Description

Pyrofork is a modern, asynchronous MTProto API framework. Versions 2.3.68 and earlier do not properly sanitize filenames received from Telegram messages in the download_media method before using them in file path construction. When downloading media, if the user does not specify a custom filename (which is the common/default usage), the method falls back to using the file_name attribute from the media object. The attribute originates from Telegram's DocumentAttributeFilename and is controlled by the message sender. This issue is fixed in version 2.3.69.

Product(s) Impacted

Vendor Product Versions
Pyrofork
  • Mtproto Api Framework
  • <2.3.68

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 pyrofork mtproto_api_framework <2.3.68 / / / / / / /

CVSS Score

6.5 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: NONE
  • Scope: UNCHANGED
  • Confidentiality Impact: NONE
  • Integrity Impact: HIGH
  • Availability Impact: NONE
  • CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:N

    View Vector String

Timeline

Published: Dec. 11, 2025, 2:16 a.m.
Last Modified: Dec. 11, 2025, 2:16 a.m.

Status : Received

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

More info

Source

security-advisories@github.com

*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.