Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:NSummary
CVE-2026-26276 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Gogs Gogs. Its CVSS base score is 7.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 8th 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.
CVE-2026-26276 is a DOM-based cross-site scripting (XSS) vulnerability, classified under CWE-79, affecting Gogs, an open source self-hosted Git service. In versions prior to 0.14.2, the flaw allows an attacker to store an HTML/JavaScript payload in a repository's Milestone name. This payload is then triggered as a DOM-based XSS when another user selects that Milestone on the New Issue page (/issues/new). The vulnerability carries a CVSS v3.1 base score of 7.3 (AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:N), indicating high confidentiality and integrity impacts with no availability disruption.
An attacker requires low privileges, such as repository write access to create or modify a Milestone with a malicious payload. Exploitation occurs over the network with low complexity but demands user interaction, specifically a victim navigating to the New Issue page and selecting the tainted Milestone. Successful exploitation enables the payload to execute in the victim's browser context, potentially leading to session hijacking, data theft, or further phishing attacks against the targeted user.
The issue has been addressed in Gogs version 0.14.2, as detailed in the official release notes, a corresponding pull request, and the project's security advisory. Security practitioners should upgrade to version 0.14.2 or later to mitigate the vulnerability, with no additional workarounds specified in the provided references.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-9855
Vulnerability Data
Gogs is an open source self-hosted Git service. Prior to version 0.14.2, an attacker can store an HTML/JavaScript payload in a repository’s Milestone name, and when another user selects that Milestone on the New Issue page (/issues/new), a DOM-Based XSS…
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is triggered. 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.