CVE-2024-56509
Published: 27 December 2024
Summary
CVE-2024-56509 is a high-severity Path Traversal (CWE-22) vulnerability. Its CVSS base score is 8.6 (High).
Operationally, ranked at the 26.6th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-3596
Vulnerability details
changedetection.io is a free open source web page change detection, website watcher, restock monitor and notification service. Improper input validation in the application can allow attackers to perform local file read (LFR) or path traversal attacks. These vulnerabilities occur when…
more
user input is used to construct file paths without adequate sanitization or validation. For example, using file:../../../etc/passwd or file: ///etc/passwd can bypass weak validations and allow unauthorized access to sensitive files. Even though this has been addressed in previous patch, it is still insufficient. This vulnerability is fixed in 0.48.05.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.