CVE-2025-27819
Published: 10 June 2025
Summary
CVE-2025-27819 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Apache Kafka. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 23.9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-17641
Vulnerability details
In CVE-2023-25194, we announced the RCE/Denial of service attack via SASL JAAS JndiLoginModule configuration in Kafka Connect API. But not only Kafka Connect API is vulnerable to this attack, the Apache Kafka brokers also have this vulnerability. To exploit this…
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vulnerability, the attacker needs to be able to connect to the Kafka cluster and have the AlterConfigs permission on the cluster resource. Since Apache Kafka 3.4.0, we have added a system property ("-Dorg.apache.kafka.disallowed.login.modules") to disable the problematic login modules usage in SASL JAAS configuration. Also by default "com.sun.security.auth.module.JndiLoginModule" is disabled in Apache Kafka 3.4.0, and "com.sun.security.auth.module.JndiLoginModule,com.sun.security.auth.module.LdapLoginModule" is disabled by default in in Apache Kafka 3.9.1/4.0.0
- 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.