CVE-2025-9260
Published: 03 September 2025
Summary
CVE-2025-9260 is a medium-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Wordpress (inferred from references). Its CVSS base score is 6.5 (Medium).
Operationally, ranked in the top 27.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-26623
Vulnerability details
The Fluent Forms – Customizable Contact Forms, Survey, Quiz, & Conversational Form Builder plugin for WordPress is vulnerable to PHP Object Injection in versions 5.1.16 to 6.1.1 via deserialization of untrusted input in the parseUserProperties function. This makes it possible…
more
for authenticated attackers, with Subscriber-level access and above, to inject a PHP Object. The additional presence of a POP chain allows attackers to read arbitrary files. If allow_url_include is enabled on the server, remote code execution is possible. While the vendor patched this issue in version 6.1.0, the patch caused a fatal error in the vulnerable code, due to a missing class import, so we consider 6.1.2 to be the most complete and best patched version
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
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.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates or rejects untrusted serialized data before deserialization occurs.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.