CVE-2024-6884
Published: 08 August 2024
Summary
CVE-2024-6884 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Kadencewp Gutenberg Blocks With Ai. Its CVSS base score is 5.4 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique JavaScript (T1059.007); ranked in the top 41.6% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as Enterprise AI Assistants; in the Other ATLAS/OWASP Terms risk domain.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-47874
Vulnerability details
The Gutenberg Blocks with AI by Kadence WP WordPress plugin before 3.2.39 does not validate and escape some of its block options before outputting them back in a page/post where the block is embed, which could allow users with the…
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contributor role and above to perform Stored Cross-Site Scripting attacks
- 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 vulnerability affects 'Gutenberg Blocks with AI by Kadence WP', a WordPress plugin providing AI-enhanced Gutenberg blocks for content creation, fitting the Enterprise AI Assistants category as it integrates AI features into enterprise-level WordPress sites for assisted content generation.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
The stored XSS vulnerability enables content injection (T1659) into WordPress Gutenberg blocks by contributor+ users, leading to arbitrary JavaScript execution (T1059.007) for drive-by compromise (T1189), exploitation of a public-facing application (T1190), and stealing web session cookies (T1539).
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 submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.