CVE-2025-14674
Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:X/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-2025-14674 is a medium-severity Injection (CWE-74) vulnerability in Gitee (inferred from references). Its CVSS base score is 5.3 (Medium).
Operationally, ranked at the 23th 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 SI-10 (Information Input Validation) and SI-2 (Flaw Remediation) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-203309
Vulnerability Data
A vulnerability was found in aizuda snail-job up to 1.6.0. Affected by this vulnerability is the function QLExpressEngine.doEval of the file snail-job-common/snail-job-common-core/src/main/java/com/aizuda/snailjob/common/core/expression/strategy/QLExpressEngine.java. The manipulation results in injection. The attack can be launched remotely. Upgrading to version 1.7.0-beta1 addresses this issue.…
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The patch is identified as 978f316c38b3d68bb74d2489b5e5f721f6675e86. The affected component should be upgraded.
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
- 6 hardening rules · 4 OS baselines
V1.3.9V1.2.1V1.2.3V1.2.5
Mitigating Controls (NIST 800-53 r5) AI
Directly requires validation and sanitization of untrusted inputs to the QLExpressEngine.doEval function, blocking the expression injection described in CVE-2025-14674.
Mandates timely application of the vendor patch (upgrade to 1.7.0-beta1) that eliminates the injection flaw in QLExpressEngine.java.
Requires integrity verification of software components, enabling detection of unauthorized or vulnerable versions of snail-job prior to exploitation.
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.
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.
Secure coding standards directly require proper neutralization of inputs and outputs, eliminating CWE-707.
Security testing in development catches injection vulnerabilities before release.
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.
Application security requirements explicitly call for controls against injection attacks in software design.