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CVE-2024-10570VulnerabilityPublished Updated

CVE-2024-10570: Login Security, FireWall, Malware removal by CleanTalk (WordPress plugin) · SQL Injection

Affects Login Security, FireWall, Malware removal by CleanTalk (WordPress plugin)Source CVE Database V5

0

Not known to be exploited · CVSS 7.5 High.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 3.1 base score
7.5High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.5% chance of exploitation in 30 days – higher than 45% 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 26 Nov 2024

  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 2026-10-26.

What to do

Affected software

ProductAffectedFixed in
cleantalk Login Security, FireWall, Malware removal by CleanTalkAffected
  • =0
Fixed in–

AI-suggested

Until an official fix is released, consider disabling the affected plugin or restricting access to the vulnerable functionality. Monitor vendor channels for updates and apply patches promptly once available.

Description

The Security & Malware scan by CleanTalk plugin for WordPress is vulnerable to unauthorized SQL Injection due to an authorization bypass via reverse DNS spoofing on the checkWithoutToken function in all versions up to, and including, 2.145, as well as insufficient input sanitization and validation. 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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