Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:HSummary
CVE-2024-23724 is a critical-severity Cross-site Scripting (CWE-79) vulnerability in Ghost Ghost. Its CVSS base score is 9.0 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 12% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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.
Ghost through version 5.76.0 is affected by a stored cross-site scripting vulnerability tracked as CVE-2024-23724 and assigned CWE-79. The flaw resides in the handling of user profile pictures supplied in SVG format, which are persisted without sufficient sanitization and can later execute JavaScript when rendered. The CVSS 3.1 base score is 9.0, reflecting network attack vector, low complexity, and the ability to compromise confidentiality, integrity, and availability across security contexts.
An authenticated contributor account is sufficient to exploit the issue. The attacker uploads a crafted SVG containing JavaScript that reaches the Ghost administrative API listening on localhost TCP port 3001; successful execution allows the contributor to perform privileged actions that result in takeover of arbitrary user accounts, including those with administrative rights.
Public references include a detailed report and proof-of-concept from Rhino Security Labs together with Ghost pull request 19646. The vendor has stated that it does not consider the localhost API interaction a valid attack vector. The associated EPSS score rose from a low baseline to a peak of 0.4526, indicating measurable post-disclosure exploitation interest.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0591
Vulnerability Data
Ghost through 5.76.0 allows stored XSS, and resultant privilege escalation in which a contributor can take over any account, via an SVG profile picture that contains JavaScript code to interact with the API on localhost TCP port 3001. NOTE: The…
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discoverer reports that "The vendor does not view this as a valid vector."
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
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.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.