CVE-2021-3402 in YARA
Summary
by MITRE • 05/15/2021
An integer overflow and several buffer overflow reads in libyara/modules/macho/macho.c in YARA v4.0.3 and earlier could allow an attacker to either cause denial of service or information disclosure via a malicious Mach-O file. Affects all versions before libyara 4.0.4
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Analysis
by VulDB Data Team • 05/20/2021
The vulnerability identified as CVE-2021-3402 represents a critical security flaw within the YARA threat hunting and malware analysis framework. This issue affects versions of YARA prior to 4.0.4 and specifically targets the macho.c module responsible for processing Mach-O binary files commonly used on macOS and iOS systems. The vulnerability stems from improper input validation and memory handling within the Mach-O file parsing logic, creating opportunities for malicious actors to exploit the software through carefully crafted binary payloads.
The technical implementation of this vulnerability involves integer overflow conditions combined with multiple buffer overflow read operations in the macho.c source file. When YARA processes a maliciously constructed Mach-O file, the integer overflow occurs during calculations related to file header parsing and section size computations. This overflow corrupts memory boundaries and creates conditions where subsequent buffer reads exceed allocated memory limits. The flaw is particularly dangerous because it operates at the core parsing layer of the YARA engine, meaning any analysis of suspicious files could trigger the vulnerability regardless of the analyst's intent or the file's apparent legitimacy.
Operationally, this vulnerability creates significant risks for security professionals and organizations relying on YARA for malware analysis and threat hunting activities. An attacker could craft a malicious Mach-O file designed to trigger the integer overflow and buffer overflows, potentially causing YARA to crash or behave unpredictably. In some scenarios, the vulnerability could also enable information disclosure attacks where adjacent memory contents are read and potentially exposed to the attacker. The denial of service aspect renders YARA unusable for its intended purpose during analysis sessions, while the information disclosure capability could expose sensitive data from the application's memory space. This affects not only individual analysts working with suspicious files but also automated analysis systems and security operations centers that depend on YARA's reliability.
The vulnerability aligns with CWE-190, which specifically addresses integer overflow conditions, and CWE-121, covering stack-based buffer overflow issues. From an adversarial perspective, this flaw maps to ATT&CK technique T1059.007 for executing malicious code through file analysis and T1497.001 for denial of service attacks. Organizations should immediately upgrade to YARA version 4.0.4 or later to address this vulnerability, as the fix includes proper input validation and memory boundary checks within the Mach-O parsing routines. Additionally, security teams should implement defensive measures such as sandboxed analysis environments and file validation protocols to mitigate potential exploitation attempts while awaiting the upgrade process. The vulnerability demonstrates the critical importance of input validation in binary parsing libraries and highlights how seemingly benign analysis tools can become attack vectors when not properly secured against malformed input data.