Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:NSummary
CVE-2026-29191 is a critical-severity Cross-site Scripting (CWE-79) vulnerability in Zitadel Zitadel. Its CVSS base score is 9.3 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 33th 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-2026-29191 is a cross-site scripting (XSS) vulnerability, classified under CWE-79, in the login V2 interface of ZITADEL, an open-source identity management platform. The issue affects versions 4.0.0 through 4.11.1 and resides in the /saml-post endpoint, enabling potential account takeover. It carries a CVSS v3.1 base score of 9.3 (AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:N), indicating critical severity due to its network accessibility, low complexity, and high potential impact on confidentiality and integrity.
Attackers require no privileges and can exploit the vulnerability remotely by tricking authenticated users into interacting with malicious content, such as through a crafted SAML POST request delivered via phishing or similar vectors. Successful exploitation expands the scope of impact, allowing attackers to steal session tokens or credentials, resulting in full account takeover and unauthorized access to the victim's identity management resources.
The vulnerability has been patched in ZITADEL version 4.12.0. Administrators are advised to upgrade immediately to mitigate the risk. Additional details are available in the GitHub Security Advisory at https://github.com/zitadel/zitadel/security/advisories/GHSA-pr34-2v5x-6qjq.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-10148
Vulnerability Data
ZITADEL is an open source identity management platform. From version 4.0.0 to 4.11.1, a vulnerability in Zitadel's login V2 interface was discovered that allowed a possible account takeover via XSS in /saml-post Endpoint. This issue has been patched in version…
more
4.12.0.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
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.