Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2022-47523 is a critical-severity SQL Injection (CWE-89) vulnerability in Zohocorp Manageengine Access Manager Plus. Its CVSS base score is 9.8 (Critical).
Operationally, ranked in the top 0.7% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SI-10 (Information Input Validation) and SI-2 (Flaw Remediation) — 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.
Zoho ManageEngine Access Manager Plus before version 4309, Password Manager Pro before 12210, and PAM360 before 5801 contain a SQL injection vulnerability tracked as CVE-2022-47523. The issue is also associated with CWE-89 and CWE-79 and carries a CVSS 3.1 base score of 9.8 reflecting network attack vector, low complexity, and no required privileges or user interaction.
An unauthenticated remote attacker can supply crafted input to exploit the flaw and obtain full read, write, and disruption capabilities over the affected installation. The same vector may additionally enable cross-site scripting behavior consistent with the listed CWEs.
Vendor advisories published at https://www.manageengine.com/privileged-session-management/advisory/cve-2022-47523.html direct customers to apply the corrected releases (Access Manager Plus 4309, Password Manager Pro 12210, and PAM360 5801) to eliminate the injection paths. The associated EPSS score reached a peak of 0.5828 before receding to its current value of 0.4555.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-50284
Vulnerability Data
Zoho ManageEngine Access Manager Plus before 4309, Password Manager Pro before 12210, and PAM360 before 5801 are vulnerable to SQL Injection.
- CWE(s)
Related Threats
Likely ATT&CK TechniquesAI
Techniques this vulnerability likely enables, inferred from its description, weakness type, and attributed-actor tradecraft. Confidence is per-technique.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly requires validation of all inputs to block crafted SQL payloads that exploit the unauthenticated injection flaw in ManageEngine.
Mandates timely application of vendor patches (4309/12210/5801) that close the documented SQL injection paths before exploitation.
Enables continuous monitoring and anomaly detection on database queries or web requests that could indicate successful or attempted SQL injection.
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.
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.
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.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.