Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2025-61848 is a high-severity SQL Injection (CWE-89) vulnerability in Fortinet Fortianalyzer. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 41th 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-2025-61848 is an SQL injection vulnerability (CWE-89) stemming from improper neutralization of special elements used in an SQL command. It affects multiple versions of Fortinet FortiAnalyzer, including 7.6.0 through 7.6.4, 7.4.0 through 7.4.8, 7.2 all versions, and 7.0 all versions, as well as the corresponding FortiAnalyzer Cloud versions. The vulnerability also impacts FortiManager 7.6.0 through 7.6.4, 7.4.0 through 7.4.8, 7.2 all versions, and 7.0 all versions, including FortiManager Cloud editions.
A privileged authenticated attacker can exploit this vulnerability over the network via the JSON RPC API with low complexity and no user interaction required. Successful exploitation enables execution of unauthorized code or commands, leading to high confidentiality, integrity, and availability impacts, as reflected in the CVSS v3.1 base score of 7.2 (AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H).
The Fortinet product security incident response team advisory at https://fortiguard.fortinet.com/psirt/FG-IR-26-111 provides details on mitigation and available patches.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-209453
Vulnerability Data
An improper neutralization of special elements used in an sql command ('sql injection') vulnerability in Fortinet FortiAnalyzer 7.6.0 through 7.6.4, FortiAnalyzer 7.4.0 through 7.4.8, FortiAnalyzer 7.2 all versions, FortiAnalyzer 7.0 all versions, FortiAnalyzer Cloud 7.6.2 through 7.6.3, FortiAnalyzer-BigData 7.6.0 through…
more
7.6.1, FortiAnalyzer-BigData 7.4.0 through 7.4.5, FortiManager 7.6.0 through 7.6.4, FortiManager 7.4.0 through 7.4.8, FortiManager 7.2 all versions, FortiManager 7.0 all versions, FortiManager Cloud 7.6.2 through 7.6.4 may allow a privileged authenticated attacker to execute unauthorized code or commands via JSON RPC API
- 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.