Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-42323 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Apache Hertzbeat. Its CVSS base score is 8.8 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 6% 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.
Apache HertzBeat versions prior to 1.6.0 contain a deserialization vulnerability in the SnakeYAML component that permits loading of malicious XML input. The flaw is tracked as CVE-2024-42323 and is associated with CWE-502, allowing untrusted data to be processed during deserialization in the affected monitoring application.
Authenticated attackers with network access can exploit the issue at low complexity to achieve remote code execution, resulting in complete loss of confidentiality, integrity, and availability according to the CVSS 3.1 score of 8.8. The vulnerability is restricted to authorized users and does not affect unauthenticated or anonymous access paths.
Project advisories direct users to upgrade to HertzBeat 1.6.0, which contains the fix, and reference notifications issued through Apache mailing lists and the OSS-Security distribution for coordinated disclosure. The associated EPSS score has remained at 0.7555 without material increase since publication.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-39551
Vulnerability Data
SnakeYaml Deser Load Malicious xml rce vulnerability in Apache HertzBeat (incubating). This vulnerability can only be exploited by authorized attackers. This issue affects Apache HertzBeat (incubating): before 1.6.0. Users are recommended to upgrade to version 1.6.0, which fixes the issue.
- 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.