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VulnerabilityPublished Updated

CVE-2025-12750: Groundhogg (WordPress plugin) · SQL Injection

Affects Groundhogg (WordPress plugin)Source CVE Database V5

0

Not known to be exploited · CVSS 4.9 Medium.

Data as of 26 Oct 2026, 12:54 UTC

CVSS 3.1 base score
4.9Medium
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.3% chance of exploitation in 30 days – higher than 25% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:N/A:N

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 21 Nov 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
trainingbusinesspros Groundhogg — CRM, Newsletters, and Marketing AutomationAffected
  • =0
Fixed in–

AI-suggested

Until an official fix is available, restrict Administrator-level access to trusted users only and monitor for suspicious activity related to SQL queries involving the 'term' parameter. Avoid using vulnerable versions of the plugin if possible.

Description

The Groundhogg — CRM, Newsletters, and Marketing Automation plugin for WordPress is vulnerable to SQL Injection via the 'term' parameter in all versions up to, and including, 4.2.6.1 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 Administrator-level access and above, 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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