Apache Kafka DoS via Unauth Mem Allocation (<=2.8.0, 3.x fixed)
CVE-2022-34917 Published on September 20, 2022

Unauthenticated clients may cause OutOfMemoryError on Apache Kafka Brokers
A security vulnerability has been identified in Apache Kafka. It affects all releases since 2.8.0. The vulnerability allows malicious unauthenticated clients to allocate large amounts of memory on brokers. This can lead to brokers hitting OutOfMemoryException and causing denial of service. Example scenarios: - 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. We advise the users to upgrade the Kafka installations to one of the 3.2.3, 3.1.2, 3.0.2, 2.8.2 versions.

NVD

Vulnerability Analysis

CVE-2022-34917 can be exploited with network access, and does not require authorization privileges or user interaction. This vulnerability is considered to have a low attack complexity. The potential impact of an exploit of this vulnerability is considered to have no impact on confidentiality and integrity, and a high impact on availability.

Attack Vector:
NETWORK
Attack Complexity:
LOW
Privileges Required:
NONE
User Interaction:
NONE
Scope:
UNCHANGED
Confidentiality Impact:
NONE
Integrity Impact:
NONE
Availability Impact:
HIGH

Weakness Type

What is a Stack Exhaustion Vulnerability?

The product allocates memory based on an untrusted, large size value, but it does not ensure that the size is within expected limits, allowing arbitrary amounts of memory to be allocated.

CVE-2022-34917 has been classified to as a Stack Exhaustion vulnerability or weakness.


Products Associated with CVE-2022-34917

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Apache Kafka
 

Affected Versions

Apache Software Foundation Apache Kafka:

Exploit Probability

EPSS
0.07%
Percentile
22.16%

EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.