Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:NSummary
CVE-2026-27116 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Vikunja Vikunja. Its CVSS base score is 6.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 13th 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 SI-10 (Information Input Validation) and SI-15 (Information Output Filtering) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-8749
Vulnerability Data
Vikunja is an open-source self-hosted task management platform. Prior to version 2.0.0, a reflected HTML injection vulnerability exists in the Projects module where the `filter` URL parameter is rendered into the DOM without output encoding when the user clicks "Filter."…
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While `<script>` and `<iframe>` are blocked, `<svg>`, `<a>`, and formatting tags (`<h1>`, `<b>`, `<u>`) render without restriction — enabling SVG-based phishing buttons, external redirect links, and content spoofing within the trusted application origin. Version 2.0.0 fixes this issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Reflected HTML injection in a public-facing web app directly enables exploitation of the application (T1190) and arbitrary content injection for phishing/redirects (T1659).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Requires validation and sanitization of all inputs (including URL parameters such as `filter`) before they are rendered into HTML, directly blocking the unsanitized tag injection described in the CVE.
Mandates filtering of information outputs to remove or encode dangerous constructs (<svg>, <a>, etc.) before they reach the DOM, preventing the reflected HTML injection at the point of rendering.
Provides integrity verification of software, firmware, and information that can detect unauthorized modification or injection of active content within application responses.
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.
Application security requirements explicitly call for neutralization of script-related HTML tags.
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.