CVE-2025-49127
Published: 06 June 2025
Summary
CVE-2025-49127 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability. Its CVSS base score is 8.9 (High).
Operationally, ranked in the top 17.2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis
Kafbat UI, a web-based interface for managing Apache Kafka clusters, is affected by an unsafe deserialization vulnerability (CWE-502) in version 1.0.0. The flaw stems from deserialization of untrusted data and carries a CVSS 4.0 score of 8.9, reflecting network-accessible attack conditions with no required authentication or user interaction.
An unauthenticated remote attacker can supply a malicious serialized payload to the application and achieve arbitrary code execution on the server, resulting in full compromise of confidentiality, integrity, and availability.
The issue is resolved in release 1.1.0, as documented in the corresponding GitHub security advisory GHSA-g3mf-c374-fgh2 and the project’s release notes; administrators should upgrade promptly to eliminate the exposure. The associated EPSS score has remained flat at 0.0171 with no material increase since disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-17363
Vulnerability details
Kafbat UI is a web user interface for managing Apache Kafka clusters. An unsafe deserialization vulnerability in version 1.0.0 allows any unauthenticated user to execute arbitrary code on the server. Version 1.1.0 fixes the issue.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates or rejects untrusted serialized data before deserialization occurs.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.