Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2025-60036 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Bosch Rexroth Indraworks. Its CVSS base score is 7.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 30th 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 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.
CVE-2025-60036 is a deserialization vulnerability (CWE-502) in the UA.Testclient utility, which is included in Rexroth IndraWorks. All versions prior to 15V24 are affected. The flaw enables arbitrary code execution when the application parses a manipulated file containing malicious serialized data.
Exploitation requires local access (AV:L) with low complexity (AC:L) and no privileges (PR:N), but user interaction (UI:R) is necessary, such as opening a specially crafted file. A successful attack leads to remote code execution (RCE) on the system running UA.Testclient, resulting in high confidentiality, integrity, and availability impacts (C:I:A:H) and a CVSS v3.1 base score of 7.8.
For mitigation details, refer to the Bosch PSIRT security advisory at https://psirt.bosch.com/security-advisories/BOSCH-SA-591522.html. The vulnerability was published on 2026-02-18.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-207844
Vulnerability Data
A vulnerability has been identified in the UA.Testclient utility, which is included in Rexroth IndraWorks. All versions prior to 15V24 are affected. This flaw allows an attacker to execute arbitrary code on the user's system by parsing a manipulated file…
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containing malicious serialized data. Exploitation requires user interaction, specifically opening a specially crafted file, which then causes the application to deserialize the malicious data, enabling Remote Code Execution (RCE). This can lead to a complete compromise of the system running the UA.Testclient.
- 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.