CVE-2025-15247

Dec. 31, 2025, 8:43 p.m.

6.9
Medium

Description

A vulnerability was identified in gmg137 snap7-rs up to 153d3e8c16decd7271e2a5b2e3da4d6f68589424. Affected by this issue is the function snap7_rs::client::S7Client::download of the file client.rs. Such manipulation leads to heap-based buffer overflow. The attack can be executed remotely. The exploit is publicly available and might be used. This product implements a rolling release for ongoing delivery, which means version information for affected or updated releases is unavailable. The project was informed of the problem early through an issue report but has not responded yet.

Product(s) Impacted

Vendor Product Versions
Gmg137
  • Snap7-rs
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-119
Improper Restriction of Operations within the Bounds of a Memory Buffer
The product performs operations on a memory buffer, but it can read from or write to a memory location that is outside of the intended boundary of the buffer.

*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 gmg137 snap7-rs / / / / / / / /

CVSS Score

6.9 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: LOW
  • Integrity Impact: LOW
  • Availability Impact: LOW
  • Exploit Maturity: PROOF_OF_CONCEPT
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/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: Dec. 30, 2025, 12:15 p.m.
Last Modified: Dec. 31, 2025, 8:43 p.m.

Status : Awaiting Analysis

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

More info

Source

cna@vuldb.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.