Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:NSummary
CVE-2025-66376 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Synacor Zimbra Collaboration Suite. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 3% of CVEs by exploit likelihood; CISA has added it to the Known Exploited Vulnerabilities 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-2025-66376 is a stored cross-site scripting (XSS) vulnerability (CWE-79) in the Classic UI of Zimbra Collaboration Suite (ZCS) versions 10 before 10.0.18 and 10.1 before 10.1.13. It arises from the improper handling of Cascading Style Sheets (CSS) @import directives embedded in HTML email messages, allowing malicious payloads to be stored and executed when rendered in the Classic UI.
Unauthenticated attackers (PR:N) can exploit this vulnerability over the network (AV:N) with low complexity (AC:L) and no user interaction required (UI:N), as indicated by its CVSS v3.1 base score of 7.2 (S:C/C:L/I:L/A:N). By sending a crafted HTML email containing a malicious CSS @import directive, the attacker can store the payload server-side. When victims access the email via the affected Classic UI, the XSS executes in the context of the Zimbra application, potentially enabling session hijacking, data theft, or further compromise with low confidentiality and integrity impacts due to the changed scope.
Zimbra's security advisories and release notes for versions 10.0.18 and 10.1.13 document fixes for this issue, recommending immediate upgrades to these patched releases. Additional guidance is available in the Zimbra Security Center, Security Advisories, and Responsible Disclosure Policy on their wiki.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-0850
Vulnerability Data
Zimbra Collaboration (ZCS) 10 before 10.0.18 and 10.1 before 10.1.13 allows Classic UI stored XSS via Cascading Style Sheets (CSS) @import directives in an HTML e-mail message.
- CWE(s)
- KEV Date Added
- 18 March 2026
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
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.