CVE-2025-11678

Oct. 20, 2025, 2:15 p.m.

7.5
High

Description

Stack-based Buffer Overflow in lws_adns_parse_label in warmcat libwebsockets allows, when the LWS_WITH_SYS_ASYNC_DNS flag is enabled during compilation, to overflow the label_stack, when the attacker is able to sniff a DNS request in order to craft a response with a matching id containing a label longer than the maximum.

Product(s) Impacted

Vendor Product Versions
Warmcat
  • Libwebsockets
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-121
Stack-based Buffer Overflow
A stack-based buffer overflow condition is a condition where the buffer being overwritten is allocated on the stack (i.e., is a local variable or, rarely, a parameter to a function).

*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 warmcat libwebsockets / / / / / / / /

References

https://libwebsockets.org/git/libwebsockets/commit?id=2bb9598562b37c942ba5b04bcde3f7fdf66a9d3a
https://www.nozominetworks.com/labs/vulnerability-advisories-cve-2025-11678

Tags

CWE-121
prodsec@nozominetworks.com
2025-10-20
CVE-2025-11678

CVSS Score

7.5 / 10

CVSS Data - 4.0

  • Attack Vector: ADJACENT
  • Attack Complexity: LOW
  • Attack Requirements: PRESENT
  • Privileges Required: NONE
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: HIGH
  • Exploit Maturity: NOT_DEFINED

    • CVSS:4.0/AV:A/AC:L/AT:P/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: Oct. 20, 2025, 2:15 p.m.
Last Modified: Oct. 20, 2025, 2:15 p.m.

Status : Received

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

More info

Source

prodsec@nozominetworks.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.