Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:L/I:H/A:HSummary
CVE-2025-20124 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Cisco Identity Services Engine. Its CVSS base score is 9.9 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 3% 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.
A vulnerability in an API of Cisco ISE allows an authenticated remote attacker to execute arbitrary commands as the root user on an affected device. The issue stems from insecure deserialization of user-supplied Java byte streams and is tracked as CWE-502. Successful exploitation requires valid read-only administrative credentials and yields command execution with privilege elevation on the appliance.
An attacker can exploit the flaw by submitting a crafted serialized Java object to the affected API. In single-node deployments the attack may briefly disrupt new device authentications during any resulting reload. The vulnerability carries a CVSS 3.1 score of 9.9, reflecting network-accessible attack complexity that is low once read-only administrative credentials are obtained.
The published Cisco Security Advisory at https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-ise-multivuls-FTW9AOXF provides official mitigation guidance and patch information. The associated EPSS score has remained flat at 0.0951 with no material post-disclosure increase observed.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-2152
Vulnerability Data
A vulnerability in an API of Cisco ISE could allow an authenticated, remote attacker to execute arbitrary commands as the root user on an affected device. This vulnerability is due to insecure deserialization of user-supplied Java byte streams by the…
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affected software. An attacker could exploit this vulnerability by sending a crafted serialized Java object to an affected API. A successful exploit could allow the attacker to execute arbitrary commands on the device and elevate privileges. Note: To successfully exploit this vulnerability, the attacker must have valid read-only administrative credentials. In a single-node deployment, new devices will not be able to authenticate during the reload time.
- 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.