CVE-2024-4743: LifterLMS (WordPress plugin) · SQL Injection
Affects LifterLMS (WordPress plugin)Source CVE Database V5
Not known to be exploited · CVSS 8.8 High.
Data as of 26 Oct 2026, 06:26 UTC
- EPSS
- 0.4% chance of exploitation in 30 days – higher than 39% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HExploitation evidence
Disclosed: evidence found.
CVE published 5 Jun 2024
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.
What to do
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| chrisbadgett LifterLMS – WP LMS for eLearning, Online Courses, & Quizzes | Affected
| Fixed in– |
AI-suggested
Until an official fix is released, restrict Contributor-level access where possible and monitor for suspicious activity related to the lifterlms_favorites shortcode usage. Avoid using the vulnerable shortcode with untrusted input. Do not rely on generic mitigations as the vulnerability specifically involves SQL injection via a shortcode parameter.
Description
The LifterLMS – WordPress LMS Plugin for eLearning plugin for WordPress is vulnerable to SQL Injection via the orderBy attribute of the lifterlms_favorites shortcode in all versions up to, and including, 7.6.2 due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query. This makes it possible for authenticated attackers, with Contributor-level access and above, to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.