Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:H/I:H/A:HSummary
CVE-2025-30284 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Adobe Coldfusion. Its CVSS base score is 8.4 (High).
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.
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.
ColdFusion versions 2023.12, 2021.18, 2025.0 and earlier contain a Deserialization of Untrusted Data vulnerability that permits arbitrary code execution in the context of the current user. The flaw is tracked as CWE-502 and carries a CVSS 3.1 score of 8.4 reflecting network attack vector, low attack complexity, high privileges required, required user interaction, and changed scope with high impact on confidentiality, integrity, and availability.
A high-privileged attacker can leverage the issue to bypass security protections and execute code, although successful exploitation depends on user interaction. The vulnerability therefore allows an authenticated administrator who convinces a victim to perform a specific action to obtain code execution outside the original security context.
Adobe’s security bulletin APSB25-15 at https://helpx.adobe.com/security/products/coldfusion/apsb25-15.html addresses the issue and supplies remediation guidance. The associated EPSS score rose materially from a low baseline to a peak of 0.3001 on 2026-01-13 before receding to the current value of 0.0103, indicating that exploitation interest appeared after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-11915
Vulnerability Data
ColdFusion versions 2023.12, 2021.18, 2025.0 and earlier are affected by a Deserialization of Untrusted Data vulnerability that could result in arbitrary code execution in the context of the current user. A high-privileged attacker could leverage this vulnerability to bypass security…
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protections and execute code. Exploitation of this issue requires user interaction and scope is changed.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can uncover deserialization flaws before deployment.
Input validation directly stops deserialization of untrusted data by ensuring inputs are valid before processing.
Engineering principles such as safe deserialization and input sanitization structurally prevent the weakness from being introduced.
Integrity verification tools can detect malformed or tampered serialized data after the fact.
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.
PR.PS-02 addresses only post-deployment updates/patching and cannot prevent introduction of unsafe deserialization code, yet it can remediate some instances when the flaw exists in outdated libraries or components.
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 includes validation of deserialization routines and the use of untrusted data, reducing the likelihood that unsafe object reconstruction will be deployed.
Requiring vetted libraries, regular updates and SAST before release reduces the likelihood that deserialization logic will accept and act on attacker-controlled serialized objects.
Regular scanning of third-party libraries and timely patching reduce the likelihood that unsafe deserialization vulnerabilities remain active.
Mandatory malware scanning of data received over networks or storage media intercepts malicious serialized payloads before they are deserialized by the target application.