CVE-2025-1947
Command Injection in Hzmanyun Education And Training System 2.1.3
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:XCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2025-1947 is a medium-severity Injection (CWE-74) vulnerability in Hzmanyun Education And Training System. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Command and Scripting Interpreter (T1059); ranked in the top 8% 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 critical command injection vulnerability has been identified in hzmanyun Education and Training System version 2.1.3, specifically in the scorm function of UploadImageController.java. The flaw arises from improper handling of the param argument, which maps to CWE-74 and CWE-77 and permits arbitrary command execution when manipulated by an attacker.
The issue can be triggered remotely by an authenticated user with low privileges, allowing the attacker to inject and execute operating system commands on the affected server. CVSS 4.0 scoring rates the impact as limited to confidentiality, integrity, and availability on the vulnerable component itself, without broader scope effects.
Public references including a detailed disclosure on GitHub and entries in Vuldb indicate the exploit has already been published, though no official patch or mitigation guidance is described in the available advisories. The associated EPSS score rose from a low baseline to a peak of 0.0388 before settling at 0.0222, indicating emerging exploitation interest after public disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7447
Vulnerability Data
A vulnerability classified as critical has been found in hzmanyun Education and Training System 2.1.3. This affects the function scorm of the file UploadImageController.java. The manipulation of the argument param leads to command injection. It is possible to initiate the…
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attack remotely. The exploit has been disclosed to the public 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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V1.2.1V1.2.3V1.2.5V1.2.8
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover command-construction flaws before deployment.
SI-10 directly requires validation of information inputs to reject malformed or special-element content before it reaches downstream parsers.
Secure engineering principles include proper neutralization and safe command construction practices.
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.
Runtime monitoring of software and data can detect anomalous command execution resulting from injection.
Identifying recorded vulnerabilities enables remediation of command-injection flaws before exploitation.
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 require proper escaping and parameterization of commands, directly eliminating CWE-77.
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.