Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2026-21643 is a critical-severity SQL Injection (CWE-89) vulnerability in Fortinet Forticlientems. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 0.2% of CVEs by exploit likelihood; CISA has added it to the Known Exploited Vulnerabilities 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-2026-21643 is an SQL injection vulnerability, tracked as CWE-89, affecting Fortinet FortiClientEMS version 7.4.4. The flaw stems from improper neutralization of special elements in SQL commands and can be triggered by specifically crafted HTTP requests, carrying a CVSS 3.1 score of 9.8.
An unauthenticated attacker with network access can exploit the issue without credentials or user interaction, achieving full read, write, and disruption capabilities on the affected system. The attack requires only low complexity and targets the exposed management interface directly.
Fortinet has published advisory FG-IR-25-1142, while CISA lists the CVE in its Known Exploited Vulnerabilities catalog. A public proof-of-concept is available, and the EPSS score has reached 0.7089, indicating substantial real-world exploitation interest.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-5681
Vulnerability Data
An improper neutralization of special elements used in an sql command ('sql injection') vulnerability in Fortinet FortiClientEMS 7.4.4 may allow an unauthenticated attacker to execute unauthorized code or commands via specifically crafted HTTP requests.
- CWE(s)
- KEV Date Added
- 13 April 2026
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.