CVE-2022-4344 in Wireshark
Summary
by MITRE • 01/12/2023
Memory exhaustion in the Kafka protocol dissector in Wireshark 4.0.0 to 4.0.1 and 3.6.0 to 3.6.9 allows denial of service via packet injection or crafted capture file
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Analysis
by VulDB Data Team • 05/07/2026
The vulnerability identified as CVE-2022-4344 represents a critical memory exhaustion flaw within the Kafka protocol dissector component of Wireshark versions 3.6.0 through 3.6.9 and 4.0.0 through 4.0.1. This issue arises from inadequate input validation and memory management within the protocol parsing logic that processes Kafka network traffic captures. The flaw specifically affects how Wireshark handles malformed or specially crafted Kafka protocol messages during packet analysis, creating a condition where excessive memory allocation occurs without proper bounds checking or resource limitation mechanisms.
The technical implementation of this vulnerability stems from the protocol dissector's failure to properly validate the size and structure of Kafka message components during packet parsing. When processing maliciously constructed Kafka traffic, the dissector attempts to allocate memory buffers based on values specified within the protocol headers without sufficient validation of these parameters. This behavior aligns with CWE-129, Input Validation and Representation Issues, and more specifically CWE-770, Allocation of Resources Without Limits or Throttling, which governs improper resource management in network protocol analysis tools. The vulnerability manifests when an attacker can either inject malicious packets into a network capture or craft a specific capture file containing oversized or malformed Kafka messages that trigger excessive memory consumption during analysis.
From an operational perspective, this vulnerability presents a significant denial of service risk to network analysts and security professionals who rely on Wireshark for network traffic analysis. The impact extends beyond simple service disruption to potentially compromise the entire analysis environment, as the memory exhaustion can cause Wireshark to crash or become unresponsive during capture file processing. This threat is particularly concerning in enterprise environments where network monitoring tools are critical for security operations and incident response activities. The vulnerability can be exploited through two primary vectors: network packet injection where an attacker sends malformed Kafka packets to a Wireshark instance in real-time monitoring mode, or through capture file manipulation where an attacker creates a malicious .pcap file containing crafted Kafka protocol data that triggers the memory exhaustion when opened by Wireshark.
The attack surface for this vulnerability encompasses any network analyst or security professional who uses Wireshark to analyze network traffic containing Kafka protocol messages, particularly in environments where Kafka is used for message queuing and distributed system communication. Organizations utilizing Kafka-based architectures for microservices communication, event streaming, or data pipelines face heightened risk when their network monitoring tools process traffic from these systems. The vulnerability's exploitation requires minimal technical expertise to craft malicious traffic or capture files, making it particularly dangerous in environments where untrusted network traffic is analyzed without proper security controls. This flaw can be categorized under the ATT&CK technique T1499.001, Network Denial of Service, and specifically relates to the broader category of resource exhaustion attacks that target analysis tools and security infrastructure.
Mitigation strategies for CVE-2022-4344 primarily involve immediate software updates to Wireshark versions that have addressed the memory management issues in the Kafka protocol dissector. Users should upgrade to Wireshark 3.6.10 or 4.0.2, which contain patches specifically designed to prevent excessive memory allocation during Kafka protocol message processing. Additional defensive measures include implementing network segmentation to limit exposure to potentially malicious Kafka traffic, employing capture file validation procedures before opening unknown or untrusted .pcap files, and establishing monitoring for unusual memory consumption patterns in network analysis environments. Organizations should also consider implementing automated patch management processes to ensure timely deployment of security updates across all network monitoring tools within their infrastructure. The vulnerability demonstrates the importance of proper resource management in protocol dissector implementations and highlights the need for robust input validation in network analysis tools that process potentially malicious network traffic.