Cyber Resilience

CVE-2021-22242

XSS in Gitlab 11.4.0 – 13.12.9

High EPSSXSS
Published
25 August 2021
Modified
21 November 2024
Patch / advisory
View advisory
CVSS Score v3.1 8.7
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:N
EPSS Score 0.64 99.1th percentile
Risk Priority 80 floored blend · peak EPSS

Summary

CVE-2021-22242 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Gitlab Gitlab. Its CVSS base score is 8.7 (High).

Operationally, ranked in the top 0.9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

OWASP Top 10 for Web (2025)

A05:2025 Injection

EU & UK References

Vulnerability Data

Insufficient input sanitization in Mermaid markdown in GitLab CE/EE version 11.4 and up allows an attacker to exploit a stored cross-site scripting vulnerability via a specially-crafted markdown

CWE(s)
CWE-79

Related Threats

Likely ATT&CK TechniquesAI

Techniques this vulnerability likely enables, inferred from its description, weakness type, and attributed-actor tradecraft. Confidence is per-technique.

T1189 Drive-by Compromise Initial Accessconfidence: HIGH
Stored XSS via malicious Mermaid markdown enables drive-by compromise when a victim views the crafted content.
attack.mitre.org →
T1056.003 Web Portal Capture Collectionconfidence: MEDIUM
XSS payload can capture credentials or session tokens from the web portal.
attack.mitre.org →
T1185 Browser Session Hijacking Collectionconfidence: MEDIUM
XSS can hijack the victim's browser session within GitLab.
attack.mitre.org →
T1539 Steal Web Session Cookie Credential Accessconfidence: MEDIUM
XSS can steal web session cookies from the authenticated user.
attack.mitre.org →
inferred from description + CWE · MITRE ATT&CK Enterprise v19.0

CVEs Like This One

CVE-2020-13340Same product: Gitlab Gitlab
CVE-2023-0050Same product: Gitlab Gitlab
CVE-2023-0523Same product: Gitlab Gitlab
CVE-2023-2015Same product: Gitlab Gitlab
CVE-2023-1836Same product: Gitlab Gitlab
CVE-2023-6033Same product: Gitlab Gitlab
CVE-2023-2164Same product: Gitlab Gitlab
CVE-2022-1190Same product: Gitlab Gitlab
CVE-2022-1175Same product: Gitlab Gitlab
CVE-2023-2442Same product: Gitlab Gitlab

Affected Assets

gitlab
gitlab
11.4.0 — 13.12.9 · 11.4.0 — 13.12.9 · 14.0.0 — 14.0.7

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V1.1.2
  • V1.3.2

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.

CA-8 Penetration Testing
addresses: CWE-79

Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.

SI-10 Information Input Validation
addresses: CWE-79

Validates web inputs to reject script-related content that could produce XSS.

SI-15 Information Output Filtering
addresses: CWE-79

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.

PR.PS-06 mostly match
prevents

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).

PR.PS-02 partial match
prevents

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.

A.8.29 Security testing in development and acceptance mostly match
detects

Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.

A.5.6 Contact with special interest groups partial match
prevents

Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.

A.5.7 Threat intelligence partial match
prevents

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.

A.8.25 Secure development life cycle partial match
prevents

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.

A.8.28 Secure coding partial match
prevents

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.

A.8.7 Protection against malware none match
none

Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.

References