Apache Kafka Security Vulnerabilities

This page lists all security vulnerabilities fixed in released versions of Apache Kafka.

CVE-2024-31141 Files or Directories Accessible to External Parties, Improper Privilege Management vulnerability in Apache Kafka Clients

Apache Kafka Clients accept configuration data for customizing behavior, and includes ConfigProvider plugins in order to manipulate these configurations. Apache Kafka also provides FileConfigProvider, DirectoryConfigProvider, and EnvVarConfigProvider implementations which include the ability to read from disk or environment variables.

In applications where Apache Kafka Clients configurations can be specified by an untrusted party, attackers may use these ConfigProviders to read arbitrary contents of the disk and environment variables. In particular, this flaw may be used in Apache Kafka Connect to escalate from REST API access to filesystem/environment access, which may be undesirable in certain environments, including SaaS products.

Versions affected 2.3.0 - 3.7.0
Fixed versions 3.7.1, 3.8.0
Impact Contents of disks and environment variables of applications using Kafka Clients may be leaked to untrusted parties.
Advice
  • Users with affected applications are recommended to upgrade kafka-clients to version >=3.8.0, and set the JVM system property "org.apache.kafka.automatic.config.providers=none".
  • Users of Kafka Connect with one of the listed ConfigProvider implementations specified in their worker config are also recommended to add appropriate "allowlist.pattern" and "allowed.paths" to restrict their operation to appropriate bounds.
  • For users of Kafka Clients or Kafka Connect in environments that trust users with disk and environment variable access, it is not recommended to set the system property.
  • For users of the Kafka Broker, Kafka MirrorMaker 2.0, Kafka Streams, and Kafka command-line tools, it is not recommended to set the system property.
Issue announced 18 Nov 2024

CVE-2024-27309 Potential incorrect access control during migration from ZK mode to KRaft mode

While an Apache Kafka cluster is being migrated from ZooKeeper mode to KRaft mode, in some cases ACLs will not be correctly enforced. Two preconditions are needed to trigger the bug:

  1. The administrator decides to remove an ACL
  2. The resource associated with the removed ACL continues to have two or more other ACLs associated with it after the removal.
When those two preconditions are met, Kafka will treat the resource as if it had only one ACL associated with it after the removal, rather than the two or more that would be correct. The incorrect condition is cleared by removing all brokers in ZK mode, or by adding a new ACL to the affected resource. Once the migration is completed, there is no metadata loss (the ACLs all remain).

Versions affected 3.5.0 - 3.6.1
Fixed versions 3.6.2
Impact The impact depends on the ACLs in use. If only ALLOW ACLs were configured during the migration, the impact would be limited to availability impact. if DENY ACLs were configured, the impact could include confidentiality and integrity impact depending on the ACLs configured, as the DENY ACLs might be ignored due to this vulnerability during the migration period.
Advice We advise all Kafka users using ACLs to only perform ZooKeeper to KRaft migrations when using Kafka 3.6.2 or above.
Issue announced 12 Apr 2024

CVE-2023-34455 Clients using Snappy compression may cause out of memory error on brokers

This CVE identifies a vulnerability in snappy-java which could be used to cause an Out-of-Memory (OOM) condition, leading to Denial-of-Service(DoS) on the Kafka broker. The vulnerability allows any user who can producer data to the broker to exploit the vulnerability by sending a malicious payload in the record which is compressed using snappy. For more details on the vulnerability, please refer to the following link: snappy-java GitHub advisory.

Versions affected 0.8.0 - 3.5.0
Fixed versions 3.5.1
Impact This vulnerability allows any user who can produce data to the broker to exploit the vulnerability, potentially causing an Out-of-Memory (OOM) condition, leading to Denial-of-Service(DoS) on the Kafka broker. It could be exploited by sending a malicious payload in the record which is compressed using snappy. On receiving the record, the broker will try to de-compress the record to perform record validation and it will delegate decompression to snappy-java library. The vulnerability in the snappy-java library may cause allocation of an unexpected amount of heap memory, causing an OOM on the broker. Any configured quota will not be able to prevent this because a single record can exploit this vulnerability.
Advice We advise all Kafka users to promptly upgrade to a version of snappy-java (>=1.1.10.1) to mitigate this vulnerability. The latest version (1.1.10.1, as of July 5, 2023) of snappy-java is backward compatible with all affected versions of Kafka. The affected library jar for snappy-java should be replaced with this newer version.
Issue announced 5 Jul 2023

CVE-2023-25194 Possible RCE/Denial of service attack via SASL JAAS JndiLoginModule configuration using Apache Kafka Connect API

A possible security vulnerability has been identified in Apache Kafka Connect API. This requires access to a Kafka Connect worker, and the ability to create/modify connectors on it with an arbitrary Kafka client SASL JAAS config and a SASL-based security protocol, which has been possible on Kafka Connect clusters since Apache Kafka 2.3.0. This will allow to perform JNDI requests that result in Denial of service/remote code execution.

Versions affected Apache Kafka Connect API (connect-api,connect-runtime) : 2.3.0 - 3.3.2
Fixed versions Apache Kafka Connect API (connect-api,connect-runtime) : 3.4.0
Impact When configuring the connector via the 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.JndiLoginModule", 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.
Advice 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 3.4.0, 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.
We advise the Kafka Connect users to validate connector configurations and only allow trusted JNDI 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.
Issue announced 8 Feb 2023

CVE-2022-34917 Unauthenticated clients may cause OutOfMemoryError on brokers

This CVE identified a flaw where it allows the malicious unauthenticated clients to allocate large amounts of memory on brokers. This can lead to brokers hitting OutOfMemoryException and causing denial of service.

Versions affected 2.8.0 - 2.8.1, 3.0.0 - 3.0.1, 3.1.0 - 3.1.1, 3.2.0 - 3.2.1
Fixed versions 2.8.2, 3.0.2, 3.1.2, 3.2.3
Impact Example scenarios in which attacker can cause OutOfMemoryError on brokers
- Kafka cluster without authentication: Any clients able to establish a network connection to a broker can trigger the issue.
- Kafka cluster with SASL authentication: Any clients able to establish a network connection to a broker, without the need for valid SASL credentials, can trigger the issue.
- Kafka cluster with TLS authentication: Only clients able to successfully authenticate via TLS can trigger the issue.
Issue announced 19 Sep 2022

CVE-2022-23302 Deserialization of Untrusted Data Flaw in JMSSink of Apache Log4j logging library in versions 1.x

This CVE identified a flaw where it allows the attacker to provide a TopicConnectionFactoryBindingName configuration that will cause JMSSink to perform JNDI requests that result in remote code execution in a similar fashion to CVE-2021-4104.

Versions affected All AK versions
Fixed versions In the absence of a new log4j 1.x release, one can remove JMSSink class from the log4j-1.2.17.jar artifact.
Impact When the attacker has write access to the Log4j configuration or if the configuration references an LDAP service the attacker has access to. The attacker can provide a configuration causing JMSSink to perform JNDI requests that result in remote code execution.
Issue announced 18 Jan 2022

CVE-2022-23305 SQL injection Flaw in Apache Log4j logging library in versions 1.x

This CVE identified a flaw where it allows a remote attacker to run SQL statements in the database if the deployed application is configured to use JDBCAppender with certain interpolation tokens.

Versions affected All AK versions
Fixed versions In the absence of a new log4j 1.x release, one can remove JDBCAppender class from the log4j-1.2.17.jar artifact.
Impact This issue could result in a SQL injection attack when the application is configured to use JDBCAppender.
Issue announced 18 Jan 2022

CVE-2022-23307 Deserialization of Untrusted Data Flaw in Apache Log4j logging library in versions 1.x

This CVE identified a flaw where it allows an attacker to send a malicious request with serialized data to the component running log4j 1.x to be deserialized when the chainsaw component is run. Chainsaw is a standalone GUI for viewing log entries in log4j. An attacker not only needs to be able to generate malicious log entries, but also, have the necessary access and permissions to start chainsaw (or if it is already enabled by a customer / consumer of Apache Kafka).

Versions affected All AK versions
Fixed versions In the absence of a new log4j 1.x release, one can remove Chainsaw from the log4j-1.2.17.jar artifact.
Impact When an attacker has the ability to start Chainsaw and is able to generate malicious log entries it allows deserialization of untrusted data.
Issue announced 18 Jan 2022

CVE-2021-45046 Flaw in Apache Log4j logging library in versions from 2.0-beta9 through 2.12.1 and from 2.13.0 through 2.15.0

Some components in Apache Kafka use Log4j-v1.2.17 there is no dependence on Log4j v2.*. Check with the vendor of any connector plugin that includes a Log4J 2.x JAR file.

Users should NOT be impacted by this vulnerability

Versions affected NA
Fixed versions NA
Impact NA
Issue announced 14 Dec 2021

CVE-2021-44228 Flaw in Apache Log4j logging library in versions from 2.0.0 and before 2.15.0

Some components in Apache Kafka use Log4j-v1.2.17 there is no dependence on Log4j v2.*. Check with the vendor of any connector plugin that includes a Log4J 2.x JAR file.

Lookups feature was introduced in Log4j v2.x in order to allow specifying Log4j configuration parameters in arbitrary locations (even outside of the configuration files). Log4j v1.x does not offer the same functionality and thus is not vulnerable to CVE-2021-44228.

Users should NOT be impacted by this vulnerability

Versions affected NA
Fixed versions NA
Impact NA
Issue announced 09 Dec 2021

CVE-2021-4104 Flaw in Apache Log4j logging library in versions 1.x

The following components in Apache Kafka use Log4j-v1.2.17: broker, controller, zookeeper, connect, mirrormaker and tools. Clients may also be configured to use Log4j-v1.x.

Version 1.x of Log4J can be configured to use JMS Appender, which publishes log events to a JMS Topic. Log4j 1.x is vulnerable if the deployed application is configured to use JMSAppender.

Versions affected All versions
Fixed versions In the absence of a new log4j 1.x release, one can remove JMSAppender from the log4j-1.2.17.jar artifact. Commands are listed in the page http://slf4j.org/log4shell.html.

We also recommend that configuration files be protected against write access as stated in http://slf4j.org/log4shell.html.
Impact This issue could result in a remote code execution attack when the application is configured to use JMSAppender AND the attacker has access to directly modify the TopicBindingName or TopicConnectionFactoryBindingName configuration variables in property files which is typically an unlikely exploitation scenario.
Issue announced 09 Dec 2021

CVE-2021-38153 Timing Attack Vulnerability for Apache Kafka Connect and Clients

Some components in Apache Kafka use Arrays.equals to validate a password or key, which is vulnerable to timing attacks that make brute force attacks for such credentials more likely to be successful. Users should upgrade to 2.8.1 or higher, or 3.0.0 or higher where this vulnerability has been fixed.

Versions affected 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.2.0, 2.2.1, 2.2.2, 2.3.0, 2.3.1, 2.4.0, 2.4.1, 2.5.0, 2.5.1, 2.6.0, 2.6.1, 2.6.2, 2.7.0, 2.7.1, 2.8.0.
Fixed versions 2.6.3, 2.7.2, 2.8.1, 3.0.0 and later
Impact This issue could result in privilege escalation.
Issue announced 21 Sep 2021

CVE-2019-12399 Apache Kafka Connect REST API may expose plaintext secrets in tasks endpoint

When Connect workers in Apache Kafka 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.2.0, 2.2.1, or 2.3.0 are configured with one or more config providers, and a connector is created/updated on that Connect cluster to use an externalized secret variable in a substring of a connector configuration property value (the externalized secret variable is not the whole configuration property value), then any client can issue a request to the same Connect cluster to obtain the connector's task configurations and the response will contain the plaintext secret rather than the externalized secrets variable. Users should upgrade to 2.2.2 or higher, or 2.3.1 or higher where this vulnerability has been fixed.

Versions affected 2.0.0, 2.0.1, 2.1.0, 2.1.1, 2.2.0, 2.2.1, 2.3.0
Fixed versions 2.2.2, 2.3.1 and later
Impact This issue could result in exposing externalized connector secrets.
Issue announced 13 Jan 2020

CVE-2018-17196 Authenticated clients with Write permission may bypass transaction/idempotent ACL validation

In Apache Kafka versions between 0.11.0.0 and 2.1.0, it is possible to manually craft a Produce request which bypasses transaction/idempotent ACL validation. Only authenticated clients with Write permission on the respective topics are able to exploit this vulnerability. Users should upgrade to 2.1.1 or later where this vulnerability has been fixed.

Versions affected 0.11.0.0 to 2.1.0
Fixed versions 2.1.1 and later
Impact This issue could result in privilege escalation.
Issue announced 10 July 2019

CVE-2018-1288 Authenticated Kafka clients may interfere with data replication

Authenticated Kafka users may perform action reserved for the Broker via a manually created fetch request interfering with data replication, resulting in data loss.

Versions affected 0.9.0.0 to 0.9.0.1, 0.10.0.0 to 0.10.2.1, 0.11.0.0 to 0.11.0.2, 1.0.0
Fixed versions 0.10.2.2, 0.11.0.3, 1.0.1, 1.1.0
Impact This issue could potentially lead to data loss.
Issue announced 26 July 2018

CVE-2017-12610 Authenticated Kafka clients may impersonate other users

Authenticated Kafka clients may use impersonation via a manually crafted protocol message with SASL/PLAIN or SASL/SCRAM authentication when using the built-in PLAIN or SCRAM server implementations in Apache Kafka.

Versions affected 0.10.0.0 to 0.10.2.1, 0.11.0.0 to 0.11.0.1
Fixed versions 0.10.2.2, 0.11.0.2, 1.0.0
Impact This issue could result in privilege escalation.
Issue announced 26 July 2018