Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2025-22461 is a high-severity SQL Injection (CWE-89) vulnerability in Ivanti Endpoint Manager. Its CVSS base score is 7.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 36% 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-2025-22461 is a SQL injection vulnerability affecting Ivanti Endpoint Manager prior to version 2024 SU1 and prior to version 2022 SU7. The flaw is tracked under CWE-89 and carries a CVSS 3.1 score of 7.2, reflecting high confidentiality, integrity, and availability impact when successfully exploited over a network.
A remote attacker who already possesses authenticated administrative privileges can supply crafted input that triggers the injection, ultimately allowing arbitrary code execution on the affected system. No unauthenticated or low-privileged attack paths are described.
The referenced Ivanti security advisory directs administrators to apply the fixed releases (2024 SU1 or 2022 SU7) to eliminate the vulnerable code paths.
EPSS values for the CVE rose from a low baseline to a recorded peak of 0.0408, indicating that exploitation interest increased after public disclosure and that the issue merits renewed monitoring despite the current score of 0.0118.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-10297
Vulnerability Data
SQL injection in Ivanti Endpoint Manager before version 2024 SU1 or before version 2022 SU7 allows a remote authenticated attacker with admin privileges to achieve code execution.
- 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.