CVE-2024-9314
Published: 05 October 2024
Summary
CVE-2024-9314 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Rankmath Seo. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked in the top 16.0% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Enterprise AI Assistants; in the Other ATLAS/OWASP Terms risk domain.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-49853
Vulnerability details
The Rank Math SEO – AI SEO Tools to Dominate SEO Rankings plugin for WordPress is vulnerable to PHP Object Injection in all versions up to, and including, 1.0.228 via deserialization of untrusted input 'set_redirections' function. This makes it possible…
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for authenticated attackers, with Administrator-level access and above, to inject a PHP Object. No known POP chain is present in the vulnerable software. If a POP chain is present via an additional plugin or theme installed on the target system, it could allow the attacker to delete arbitrary files, retrieve sensitive data, or execute code.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Enterprise AI Assistants
- Risk Domain
- Other ATLAS/OWASP Terms
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- The Rank Math SEO plugin explicitly includes 'AI SEO Tools' for SEO optimization, positioning it as an enterprise AI assistant integrated into WordPress environments.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
PHP Object Injection enables authenticated admins to potentially retrieve sensitive data (T1005), execute code via PHP interpreter (T1059), delete arbitrary files (T1070.004), and escalate privileges (T1068) if a POP chain exists in the software or other plugins/themes.
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.