Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:NSummary
CVE-2026-26022 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Gogs Gogs. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 23th percentile by exploit likelihood (below the median); 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.
CVE-2026-26022 is a stored cross-site scripting (XSS) vulnerability (CWE-79) in Gogs, an open source self-hosted Git service. The flaw affects versions prior to 0.14.2 and resides in the comment and issue description functionality, where the HTML sanitizer explicitly permits data: URI schemes. This allows authenticated users to inject malicious links that enable arbitrary JavaScript execution when rendered in users' browsers.
An authenticated attacker with low privileges can exploit this vulnerability over the network with low complexity, though it requires user interaction from a victim viewing the tainted comment or issue. Successful exploitation leads to high confidentiality and integrity impacts with a changed scope, potentially allowing attackers to steal session cookies, perform actions on behalf of victims, or deface repository content. The CVSS v3.1 base score is 8.7 (AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:N).
The issue has been addressed in Gogs version 0.14.2, as detailed in the project's security advisory (GHSA-xrcr-gmf5-2r8j), release notes, associated pull request (#8174), and patching commit (441c64d7bd8893b2f4e48660a8be3a7472e14291). Security practitioners should urge users to upgrade immediately to mitigate the risk.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-9851
Vulnerability Data
Gogs is an open source self-hosted Git service. Prior to version 0.14.2, a stored cross-site scripting (XSS) vulnerability exists in the comment and issue description functionality. The application's HTML sanitizer explicitly allows data: URI schemes, enabling authenticated users to inject…
more
arbitrary JavaScript execution via malicious links. This issue has been patched in version 0.14.2.
- 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.