Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2025-27818 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Apache Kafka. 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 44% 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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-17639
Vulnerability Data
A possible security vulnerability has been identified in Apache Kafka. This requires access to a alterConfig to the cluster resource, or Kafka Connect worker, and the ability to create/modify connectors on it with an arbitrary Kafka client SASL JAAS config…
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and a SASL-based security protocol, which has been possible on Kafka clusters since Apache Kafka 2.0.0 (Kafka Connect 2.3.0). When configuring the broker via config file or AlterConfig command, or connector via the Kafka Kafka Connect REST API, an authenticated operator can set the `sasl.jaas.config` property for any of the connector's Kafka clients to "com.sun.security.auth.module.LdapLoginModule", which can be done via the `producer.override.sasl.jaas.config`, `consumer.override.sasl.jaas.config`, or `admin.override.sasl.jaas.config` properties. This will allow the server to connect to the attacker's LDAP server and deserialize the LDAP response, which the attacker can use to execute java deserialization gadget chains on the Kafka connect server. Attacker can cause unrestricted deserialization of untrusted data (or) RCE vulnerability when there are gadgets in the classpath. Since Apache Kafka 3.0.0, users are allowed to specify these properties in connector configurations for Kafka Connect clusters running with out-of-the-box configurations. Before Apache Kafka 3.0.0, users may not specify these properties unless the Kafka Connect cluster has been reconfigured with a connector client override policy that permits them. Since Apache Kafka 3.9.1/4.0.0, 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,com.sun.security.auth.module.LdapLoginModule" are disabled in Apache Kafka Connect 3.9.1/4.0.0. We advise the Kafka users to validate connector configurations and only allow trusted LDAP configurations. Also examine connector dependencies for vulnerable versions and either upgrade their connectors, upgrading that specific dependency, or removing the connectors as options for remediation. Finally, in addition to leveraging the "org.apache.kafka.disallowed.login.modules" system property, Kafka Connect users can also implement their own connector client config override policy, which can be used to control which Kafka client properties can be overridden directly in a connector config and which cannot.
- 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.