CVE-2025-10090
SQLi in Jinher Oa ≤ 1.2
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2025-10090 is a medium-severity Injection (CWE-74) vulnerability in Jinher Jinher Oa. Its CVSS base score is 5.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 23% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV 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.
A flaw has been identified in Jinher OA versions up to 1.2, specifically an unknown function within the file /C6/Jhsoft.Web.departments/GetTreeDate.aspx. Manipulation of the ID argument in this component allows SQL injection, classified under CWE-74 and CWE-89, with a CVSS 4.0 score of 5.5 reflecting network attack vector, low complexity, and no required privileges or user interaction.
Remote attackers can exploit the vulnerability without authentication to inject SQL commands, resulting in limited impacts to confidentiality, integrity, and availability of the affected system. The attack can be launched over the network, and a functional exploit has already been made public.
Public references, including a GitHub issue and multiple Vuldb entries, document the flaw and its disclosure but do not detail official patches or mitigation steps. The EPSS score shows only a minor increase from a low baseline to a peak of 0.0183, indicating limited observed exploitation interest to date.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-27119
Vulnerability Data
A flaw has been found in Jinher OA up to 1.2. The impacted element is an unknown function of the file /C6/Jhsoft.Web.departments/GetTreeDate.aspx. Executing manipulation of the argument ID can lead to sql injection. The attack may be launched remotely. The…
more
exploit has been published and may be used.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.
SI-10 directly requires validation of information inputs to reject malformed or special-element content before it reaches downstream parsers.
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 require input validation and output encoding that prevent injection flaws.
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.
Security testing in development catches injection vulnerabilities before release.
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.
Logging supports detection of injection attempts but does not prevent the weakness.
Monitoring activities can identify active injection attacks after they occur.
Secure development life cycle mandates input validation and output encoding that directly prevent injection flaws.