Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:N/VI:N/VA:N/SC:L/SI:L/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-58402 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Gohugo Hugo. Its CVSS base score is 5.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique JavaScript (T1059.007); ranked at the 7th 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 SI-10 (Information Input Validation) and SC-8 (Transmission Confidentiality and Integrity) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-41904
Vulnerability Data
Hugo is a static site generator. From 0.60.0 until 0.163.3, Hugo's default code-block renderer wrote the Markdown code-fence language or info-string into the code class="language-…" data-lang="…" wrapper without HTML escaping. A fence info-string containing a quote and a script payload…
more
breaks out of the attribute and injects a live script element. This issue is fixed in 0.163.3.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Stored XSS via unescaped info-string directly enables JavaScript execution (T1059.007) in visitor browsers and facilitates drive-by compromise (T1189) of Hugo-generated public sites.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Requires validation and sanitization of all untrusted input (the Markdown info-string) before it is placed into HTML attribute values, directly blocking the reflected XSS vector.
Mandates cryptographic protection of transmitted content, which would prevent an attacker from injecting the malicious payload over the wire if the rendered site is served over HTTPS.
Provides integrity verification of generated static files, allowing detection of unauthorized script insertion after the fact.
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.