Raw vector
CVSS:4.0/AV:N/AC:H/AT:P/PR:H/UI:N/VC:H/VI:H/VA:H/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:Y/R:U/V:C/RE:L/U:GreenSummary
CVE-2025-66524 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Apache Nifi. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 37th 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-2025-66524 is a high-severity vulnerability (CVSS 8.8) affecting Apache NiFi versions 1.20.0 through 2.6.0, specifically in the GetAsanaObject Processor from the nifi-asana-processors-nar bundle. This processor integrates with a configurable Distributed Map Cache Client Service to store and retrieve state information, but it employs unfiltered Java object serialization and deserialization (CWE-502). This lack of filtering exposes systems to risks from malicious payloads in the cached state data.
Exploitation requires an attacker to have low privileges (PR:L) and direct access to the configured cache server on an Apache NiFi instance running the GetAsanaObject Processor. The attack is feasible over the network (AV:N) with low complexity (AC:L) and no user interaction (UI:N), potentially leading to high impacts on confidentiality, integrity, and availability (C:H/I:H/A:H). A crafted state object stored in the cache can trigger dangerous deserialization gadgets when processed by the NiFi instance.
Apache advisories recommend upgrading to NiFi 2.7.0, which mitigates the issue by replacing Java object serialization with JSON serialization. Alternatively, removing the GetAsanaObject Processor from the nifi-asana-processors-nar bundle prevents exploitation entirely. Details are available in the Apache mailing list announcement and oss-security posting.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-204524
Vulnerability Data
Apache NiFi 1.20.0 through 2.6.0 include the GetAsanaObject Processor, which requires integration with a configurable Distribute Map Cache Client Service for storing and retrieving state information. The GetAsanaObject Processor used generic Java Object serialization and deserialization without filtering. Unfiltered Java…
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object deserialization does not provide protection against crafted state information stored in the cache server configured for GetAsanaObject. Exploitation requires an Apache NiFi system running with the GetAsanaObject Processor, and direct access to the configured cache server. Upgrading to Apache NiFi 2.7.0 is the recommended mitigation, which replaces Java Object serialization with JSON serialization. Removing the GetAsanaObject Processor located in the nifi-asana-processors-nar bundle also prevents exploitation.
- 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.