Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:HSummary
CVE-2025-5086 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in 3Ds Delmia Apriso. Its CVSS base score is 9.0 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 0.2% of CVEs by exploit likelihood; CISA has added it to the Known Exploited Vulnerabilities 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 deserialization of untrusted data vulnerability, tracked as CVE-2025-5086 and assigned CWE-502, affects Dassault Systèmes DELMIA Apriso releases from 2020 through 2025. The flaw carries a CVSS 3.1 score of 9.0 with a network attack vector, high complexity, no required privileges or user interaction, and changed scope, enabling remote code execution that can fully compromise confidentiality, integrity, and availability.
An unauthenticated attacker able to supply crafted serialized data over the network can trigger arbitrary code execution on affected systems. The high complexity rating indicates that successful exploitation requires specific conditions, yet the absence of authentication or user interaction lowers the barrier once those conditions are met.
Vendor advisories hosted at 3ds.com detail available patches and mitigation steps for supported releases, while CISA has added the CVE to its Known Exploited Vulnerabilities catalog. A SANS Internet Storm Center diary documents observed exploit attempts against the vulnerability.
The EPSS score reached a peak of 0.4651 and remains elevated at 0.4139, reflecting a clear post-disclosure increase in exploitation interest that warrants renewed defensive attention.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-16682
Vulnerability Data
A deserialization of untrusted data vulnerability affecting DELMIA Apriso from Release 2020 through Release 2025 could lead to a remote code execution.
- CWE(s)
- KEV Date Added
- 11 September 2025
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.