CVE Vulnerabilities

CVE-2025-41429

Improper Output Neutralization for Logs

Published: May 19, 2025 | Modified: Sep 30, 2025
CVSS 3.x
9.8
CRITICAL
Source:
NVD
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
CVSS 2.x
RedHat/V2
RedHat/V3
Ubuntu

a-blog cms multiple versions neutralize logs improperly. If this vulnerability is exploited with CVE-2025-36560, a remote unauthenticated attacker may hijack a legitimate users session.

Weakness

The product constructs a log message from external input, but it does not neutralize or incorrectly neutralizes special elements when the message is written to a log file.

Affected Software

Name Vendor Start Version End Version
A-blog_cms Appleple 2.8.0 (including) 2.8.85 (including)
A-blog_cms Appleple 2.9.0 (including) 2.9.52 (including)
A-blog_cms Appleple 2.10.0 (including) 2.10.63 (including)
A-blog_cms Appleple 2.11.0 (including) 2.11.75 (including)
A-blog_cms Appleple 3.0.0 (including) 3.0.47 (including)
A-blog_cms Appleple 3.1.0 (including) 3.1.43 (including)

Potential Mitigations

  • Assume all input is malicious. Use an “accept known good” input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
  • When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, “boat” may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as “red” or “blue.”
  • Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code’s environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.

References