CVE-2014-9620 in File
Summary
by MITRE
The ELF parser in file 5.08 through 5.21 allows remote attackers to cause a denial of service via a large number of notes.
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Analysis
by VulDB Data Team • 03/08/2022
The vulnerability identified as CVE-2014-9620 resides within the ELF (Executable and Linkable Format) parser functionality of the file command version 5.08 through 5.21. This issue represents a classic denial of service vulnerability that can be exploited by remote attackers to disrupt system operations. The file command is widely used across various operating systems and security tools to identify file types and their characteristics, making it a critical component in system administration and security auditing processes. When an attacker crafts malicious ELF files containing an excessive number of notes sections, the parser becomes overwhelmed during the analysis process, leading to system resource exhaustion and potential service interruption.
The technical flaw stems from inadequate input validation and resource management within the ELF parsing logic. Specifically, the parser does not implement proper bounds checking or resource limiting mechanisms when processing the notes section of ELF files. In ELF format, notes are used to store additional information about the file, and while the format specification allows for multiple notes sections, the file command implementation fails to handle unusually large numbers of these sections gracefully. This weakness creates a path where an attacker can construct an ELF file with thousands or even millions of notes entries, causing the parser to consume excessive memory and processing cycles during analysis. The vulnerability manifests as the parser entering into a computationally expensive loop while attempting to process each note entry, ultimately leading to system resource exhaustion and denial of service conditions.
The operational impact of this vulnerability extends beyond simple service disruption to potentially affect critical infrastructure and security monitoring systems. Organizations relying on automated file analysis tools that utilize the file command may experience widespread service degradation when processing maliciously crafted files. Security operations centers and intrusion detection systems that depend on file type identification for threat analysis could face complete service outages, compromising their ability to monitor and respond to security incidents. The vulnerability is particularly concerning because it affects widely deployed software packages and can be exploited through various attack vectors including email attachments, web downloads, and file sharing systems. The low complexity of exploitation means that even unskilled attackers can potentially leverage this vulnerability to cause significant operational disruption.
Mitigation strategies for CVE-2014-9620 should focus on both immediate defensive measures and long-term architectural improvements. Organizations should immediately upgrade to file command versions 5.22 or later, where the vulnerability has been patched through enhanced input validation and resource limiting mechanisms. Network administrators should implement file type filtering and sandboxing techniques to prevent potentially malicious ELF files from reaching systems that rely on the file command for analysis. The implementation of rate limiting and resource quotas for file processing operations can help contain the impact of such attacks. From a defensive perspective, security teams should monitor for exploitation attempts through log analysis and implement automated detection mechanisms that can identify unusual file processing patterns. This vulnerability aligns with CWE-770, which addresses allocation of resources without limits or with inadequate limits, and maps to ATT&CK technique T1499.004 for network denial of service attacks. Organizations should also consider implementing file integrity monitoring solutions that can detect unauthorized updates to the file command binary and maintain regular vulnerability assessments to identify similar weaknesses in their software stack.