Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2025-0724 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Metagauss Profilegrid. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Client Execution (T1203); ranked at the 49th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2025-0724 is a PHP Object Injection vulnerability (CWE-502) affecting the ProfileGrid – User Profiles, Groups and Communities plugin for WordPress in all versions up to and including 5.9.4.5. The issue arises from deserialization of untrusted input in the get_user_meta_fields_html function, enabling authenticated attackers to inject a PHP Object. The vulnerability carries a CVSS v3.1 base score of 8.8 (AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H), indicating high severity due to its network accessibility and low complexity.
Authenticated attackers with Subscriber-level access or higher can exploit this vulnerability remotely. While no known Proof-of-Presence (POP) chain exists within the vulnerable plugin itself, making it benign in isolation, the injection could be leveraged if another plugin or theme on the target site provides a POP chain. In such cases, attackers may achieve severe impacts, including deletion of arbitrary files, retrieval of sensitive data, or arbitrary code execution, depending on the specific POP chain available.
Advisories reference the vulnerable code location in the WordPress plugin trac at https://plugins.trac.wordpress.org/browser/profilegrid-user-profiles-groups-and-communities/tags/5.9.4.2/includes/class-profile-magic-html-generator.php#L259 and provide further details via Wordfence threat intelligence at https://www.wordfence.com/threat-intel/vulnerabilities/id/6bb1de69-7bc2-4785-9789-0a2d1cf35b9b?source=cve.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7194
Vulnerability Data
The ProfileGrid – User Profiles, Groups and Communities plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 5.9.4.5 via deserialization of untrusted input in the get_user_meta_fields_html function. This makes it possible for authenticated…
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attackers, with Subscriber-level access and above, to inject a PHP Object. No known POP chain is present in the vulnerable software, which means this vulnerability has no impact unless another plugin or theme containing a POP chain is installed on the site. If a POP chain is present via an additional plugin or theme installed on the target system, it may allow the attacker to perform actions like delete arbitrary files, retrieve sensitive data, or execute code depending on the POP chain present.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can uncover deserialization flaws before deployment.
Input validation directly stops deserialization of untrusted data by ensuring inputs are valid before processing.
Engineering principles such as safe deserialization and input sanitization structurally prevent the weakness from being introduced.
Integrity verification tools can detect malformed or tampered serialized data after the fact.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing includes validation of deserialization routines and the use of untrusted data, reducing the likelihood that unsafe object reconstruction will be deployed.
Requiring vetted libraries, regular updates and SAST before release reduces the likelihood that deserialization logic will accept and act on attacker-controlled serialized objects.
Regular scanning of third-party libraries and timely patching reduce the likelihood that unsafe deserialization vulnerabilities remain active.