Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2025-25064 is a high-severity SQL Injection (CWE-89) vulnerability in Synacor Zimbra Collaboration Suite. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 2% of CVEs by exploit likelihood; 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-2025-25064 is a SQL injection vulnerability in the ZimbraSync Service SOAP endpoint of Zimbra Collaboration versions 10.0.x prior to 10.0.12 and 10.1.x prior to 10.1.4. It stems from insufficient sanitization of a user-supplied parameter, allowing arbitrary SQL queries to be injected via the affected endpoint and potentially exposing email metadata.
Authenticated attackers with valid credentials can exploit the flaw over the network by crafting malicious requests that manipulate the vulnerable parameter. Successful exploitation grants the ability to retrieve sensitive email metadata, with the issue carrying a CVSS 3.1 score of 8.8 reflecting high impact on confidentiality, integrity, and availability.
Zimbra's release notes for versions 10.0.12 and 10.1.4, along with the vendor's security advisories page, document the fixes applied to address this and related issues in the affected releases. The current EPSS score of 0.4776 with a peak of 0.4829 shows no material rise from a low baseline.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-4006
Vulnerability Data
SQL injection vulnerability in the ZimbraSync Service SOAP endpoint in Zimbra Collaboration 10.0.x before 10.0.12 and 10.1.x before 10.1.4 due to insufficient sanitization of a user-supplied parameter. Authenticated attackers can exploit this vulnerability by manipulating a specific parameter in the…
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request, allowing them to inject arbitrary SQL queries that could retrieve email metadata.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V6.2.5
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.
Input validation directly stops untrusted data from reaching SQL query construction without neutralization.
Secure engineering principles require parameterized queries and input sanitization that structurally eliminate SQLi.
System monitoring can identify attempted SQLi exploitation via anomalous queries after the weakness exists.
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 injection flaws during coding and review so largely prevent CWE-89 introduction, yet the single broad outcome leaves residual risk from incomplete neutralization techniques or missed edge cases.
Training raises developer awareness of SQLi risks and can reduce introduction likelihood (partial) but removes none of the actual coding flaw's risk by itself since technical neutralization is still required.
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.
The same secure-coding and static-analysis activities surface missing neutralization of SQL metacharacters before the system is accepted.
Early warnings and shared best-practice information help organizations apply the latest remediation techniques against SQL-injection vulnerabilities.
Threat-intelligence feeds that surface new SQL-injection campaigns enable rapid updates to query-construction defenses and detection signatures before exploitation occurs.
Secure-coding rules and security testing phases mandate the use of parameterized queries or equivalent escaping, preventing the construction of dynamic SQL statements from untrusted input.
Language-specific secure coding rules, peer review and SAST together prevent the construction of SQL statements from untrusted data without proper parameterization or escaping.