CVE-2024-1209
Published: 05 February 2024
Summary
CVE-2024-1209 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Learndash Learndash. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Services File Permissions Weakness (T1574.010); ranked in the top 2.2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis
The CVE-2024-1209 vulnerability is a sensitive information exposure issue in the LearnDash LMS plugin for WordPress, present in all versions through 4.10.1. It stems from insufficient protection of uploaded assignment files, which permits direct file access and is tracked under CWE-200 with a CVSS 3.1 score of 5.3.
Unauthenticated attackers can exploit the flaw remotely without credentials or user interaction to retrieve the contents of assignment uploads that should otherwise remain restricted.
References including LearnDash release notes and Wordfence threat intelligence entries point to patched versions that remediate the direct-access exposure. The associated EPSS values remain essentially flat near 0.47 with no material rise from a low baseline.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-16976
Vulnerability details
The LearnDash LMS plugin for WordPress is vulnerable to Sensitive Information Exposure in all versions up to, and including, 4.10.1 via direct file access due to insufficient protection of uploaded assignments. This makes it possible for unauthenticated attackers to obtain…
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those uploads.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
CVE-2024-1209 enables unauthenticated attackers to list assignments via REST API (T1083), directly access files due to insufficient file protections (T1044), exploit a public-facing WordPress plugin vulnerability (T1190), and collect data from the LMS information repository (T1213).
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.