Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:L/I:L/A:NSummary
CVE-2023-0523 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Gitlab Gitlab. Its CVSS base score is 5.4 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 48th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
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 XSS vulnerability has been identified in GitLab, affecting all versions from 15.6 before 15.8.5, from 15.9 before 15.9.4, and from 15.10 before 15.10.1. The flaw, tracked as CWE-79, allows a malicious email address to trigger cross-site scripting in certain instances, carrying a CVSS 3.1 score of 5.4.
An authenticated attacker with low privileges can supply a crafted email address that executes arbitrary script in a victim's browser when the address is rendered. Successful exploitation yields limited confidentiality and integrity impact with changed scope, though user interaction is required and availability is unaffected.
GitLab advisories direct users to apply the listed patches, upgrading to 15.8.5, 15.9.4, or 15.10.1 depending on the release line in use. The associated EPSS score has remained in the 0.21 range with only a minor peak, indicating no pronounced post-disclosure exploitation surge.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-12568
Vulnerability Data
An issue has been discovered in GitLab affecting all versions starting from 15.6 before 15.8.5, 15.9 before 15.9.4, and 15.10 before 15.10.1. An XSS was possible via a malicious email address for certain instances.
- 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
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.
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.