Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:H/A:NSummary
CVE-2026-33979 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Express Xss Sanitizer Project Express Xss Sanitizer. Its CVSS base score is 8.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 31th 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-2026-33979 affects Express XSS Sanitizer, a middleware for Express 4.x and 5.x applications that sanitizes user input from req.body, req.query, req.headers, and req.params to prevent cross-site scripting (XSS) attacks. In versions prior to 2.0.2, the middleware silently ignores restrictive sanitization configurations, such as explicitly provided empty allowedTags or allowedAttributes options. This flaw, linked to CWE-79 (Improper Neutralization of Input During Web Page Generation) and CWE-183 (Permissive List of Allowed Inputs), carries a CVSS v3.1 base score of 8.2 (AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:H/A:N), indicating high severity due to its potential for integrity compromise.
Unauthenticated attackers can exploit this vulnerability remotely over the network with low complexity by submitting malicious input through the sanitized request parameters. The ignored configurations allow harmful HTML and JavaScript to bypass sanitization via the underlying sanitize-html library, enabling XSS execution in the application's output. This results in low confidentiality impact but high integrity impact, as attackers could steal session cookies, perform actions on behalf of users, or deface content, depending on the application's rendering of sanitized data.
The GitHub security advisory (GHSA-3843-rr4g-m8jq), release notes for v2.0.2, and related commit (5623009ef11dcf095c163a38dea07b9cc22ad19f) detail the fix: version 2.0.2 updates validation logic to honor explicitly provided empty configurations, passing allowedTags or allowedAttributes directly to sanitize-html without overrides. Security practitioners should upgrade to Express XSS Sanitizer 2.0.2 or later and review configurations to ensure restrictive sanitization is enforced as intended.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-16876
Vulnerability Data
Express XSS Sanitizer is Express 4.x and 5.x middleware which sanitizes user input data (in req.body, req.query, req.headers and req.params) to prevent Cross Site Scripting (XSS) attack. A vulnerability has been identified in versions prior to 2.0.2 where restrictive sanitization…
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configurations are silently ignored. In version 2.0.2, the validation logic has been updated to respect explicitly provided empty configurations. Now, if allowedTags or allowedAttributes are provided (even if empty), they are passed directly to sanitize-html without being overridden.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.5.2V4.4.2V1.1.2V1.3.2
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.
Application security requirements can mandate strict, minimal allow-lists and input validation rules that prevent overly permissive lists.
Secure system architecture and engineering principles require explicit, least-privilege input validation designs that directly address permissive allow-lists.