Raw vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:NSummary
CVE-2023-5933 is a medium-severity Basic XSS (CWE-80) vulnerability in Gitlab Gitlab. Its CVSS base score is 6.4 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); 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.
An issue has been discovered in GitLab CE/EE involving improper input sanitization of user names that permits arbitrary API PUT requests. The vulnerability affects all versions after 13.7 before 16.6.6, 16.7 prior to 16.7.4, and 16.8 prior to 16.8.1. It is tracked under CWE-80 and CWE-79 with a CVSS 3.1 score of 6.4 reflecting network attack vector, high attack complexity, low privileges required, and user interaction.
An authenticated attacker with low privileges can supply a crafted user name that bypasses sanitization, enabling them to issue unauthorized API PUT requests. Successful exploitation can result in high impact to confidentiality and integrity on affected instances while availability remains unaffected.
GitLab security advisories for the 16.8.1 release and corresponding issue trackers recommend immediate upgrade to the fixed versions 16.6.6, 16.7.4, or 16.8.1 depending on the release line in use.
EPSS remains at 0.1036 with no material increase from its initial value after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-58205
Vulnerability Data
An issue has been discovered in GitLab CE/EE affecting all versions after 13.7 before 16.6.6, 16.7 prior to 16.7.4, and 16.8 prior to 16.8.1. Improper input sanitization of user name allows arbitrary API PUT requests.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect neutralization of script tags through targeted XSS test cases.
Input validation explicitly requires checking and neutralizing untrusted web inputs containing script-related characters before they reach a downstream renderer.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
Secure engineering principles include mandatory output encoding and neutralization of HTML metacharacters to stop injection at the source.
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 require output encoding and input validation that prevent basic XSS.
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.
Security testing in development catches unneutralized script tags before release.
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.
Secure SDLC mandates input validation and output encoding that directly prevent basic XSS.
Application security requirements explicitly call for neutralization of script-related HTML tags.
Secure coding standards require proper escaping of <, >, & to block XSS.