Raw vector
CVSS:3.1/AV:N/AC:H/PR:H/UI:R/S:U/C:H/I:H/A:HSummary
CVE-2023-28836 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Torchbox Wagtail. Its CVSS base score is 6.4 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 47% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0278
Vulnerability Data
Wagtail is an open source content management system built on Django. Starting in version 1.5 and prior to versions 4.1.4 and 4.2.2, a stored cross-site scripting (XSS) vulnerability exists on ModelAdmin views within the Wagtail admin interface. A user with…
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a limited-permission editor account for the Wagtail admin could potentially craft pages and documents that, when viewed by a user with higher privileges, could perform actions with that user's credentials. The vulnerability is not exploitable by an ordinary site visitor without access to the Wagtail admin, and only affects sites with ModelAdmin enabled. For page, the vulnerability is in the "Choose a parent page" ModelAdmin view (`ChooseParentView`), available when managing pages via ModelAdmin. For documents, the vulnerability is in the ModelAdmin Inspect view (`InspectView`) when displaying document fields. Patched versions have been released as Wagtail 4.1.4 and Wagtail 4.2.2. Site owners who are unable to upgrade to the new versions can disable or override the corresponding functionality.
- 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
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
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.