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CVE-2024-13476VulnerabilityPublished Updated

CVE-2024-13476: LTL Freight Quotes (WordPress plugin) · SQL Injection

Affects LTL Freight Quotes (WordPress plugin)Source CVE Database V5

0

Not known to be exploited · CVSS 7.5 High.

Data as of 26 Oct 2026, 08:30 UTC

CVSS 3.1 base score
7.5High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.4% chance of exploitation in 30 days – higher than 38% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 20 Feb 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq 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 26 Oct 2026.

What to do

Affected software

ProductAffectedFixed in
enituretechnology LTL Freight Quotes – GlobalTranz EditionAffected
  • =0
Fixed in–

AI-suggested

Until an official fix is released, users should consider disabling or restricting access to the vulnerable AJAX endpoint if possible. Monitor for updates from enituretechnology regarding patches or mitigations. Avoid exposing the affected plugin to untrusted users or networks.

Description

The LTL Freight Quotes – GlobalTranz Edition plugin for WordPress is vulnerable to SQL Injection via the 'engtz_wd_save_dropship' AJAX endpoint in all versions up to, and including, 2.3.11 due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query. This makes it possible for unauthenticated attackers to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.

References

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