CVE-2026-40021

April 10, 2026, 5:17 p.m.

6.3
Medium

Description

Apache Log4net's XmlLayout https://logging.apache.org/log4net/manual/configuration/layouts.html#layout-list and XmlLayoutSchemaLog4J https://logging.apache.org/log4net/manual/configuration/layouts.html#layout-list , in versions before 3.3.0, fail to sanitize characters forbidden by the XML 1.0 specification https://www.w3.org/TR/xml/#charsets in MDC property keys and values, as well as the identity field that may carry attacker-influenced data. This causes an exception during serialization and the silent loss of the affected log event. An attacker who can influence any of these fields can exploit this to suppress individual log records, impairing audit trails and detection of malicious activity. Users are advised to upgrade to Apache Log4net 3.3.0, which fixes this issue.

Product(s) Impacted

Vendor Product Versions
Apache
  • Log4net
  • <3.3.0

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-116
Improper Encoding or Escaping of Output
The product prepares a structured message for communication with another component, but encoding or escaping of the data is either missing or done incorrectly. As a result, the intended structure of the message is not preserved.

CVSS Score

6.3 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: HIGH
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: NONE
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:N/VI:N/VA:N/SC:N/SI:L/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: April 10, 2026, 4:16 p.m.
Last Modified: April 10, 2026, 5:17 p.m.

Status : Received

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.