CVE-2012-1447 in Fortinet
Summary
by MITRE
The ELF file parser in Fortinet Antivirus 4.2.254.0, eSafe 7.0.17.0, Dr.Web 5.0.2.03300, and Panda Antivirus 10.0.2.7 allows remote attackers to bypass malware detection via an ELF file with a modified e_version field. NOTE: this may later be SPLIT into multiple CVEs if additional information is published showing that the error occurred independently in different ELF parser implementations.
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Analysis
by VulDB Data Team • 02/16/2019
The vulnerability described in CVE-2012-1447 represents a critical flaw in the executable file format parsing capabilities of multiple antivirus solutions, specifically targeting the ELF (Executable and Linkable Format) file parser implementation. This issue affects several major antivirus vendors including Fortinet, eSafe, Dr.Web, and Panda Antivirus, all of which utilize flawed ELF parsing logic that fails to properly validate file metadata during malware detection processes. The vulnerability stems from a specific field within the ELF file header known as e_version, which contains crucial metadata about the file's version and compatibility. When this field is deliberately modified by attackers, the affected antivirus systems incorrectly process the file, leading to bypass of security checks and potential malware execution.
The technical root cause of this vulnerability lies in the improper validation of ELF file headers, specifically the e_version field which should contain a standardized value indicating the file format version. Modern ELF files typically contain an e_version field with the value 1, representing the standard ELF version 1 specification. However, the vulnerable antivirus implementations fail to properly validate this field or perform adequate checks to ensure that modified values do not indicate malicious intent. This parsing error creates a condition where attackers can manipulate the e_version field to values that cause the antivirus engine to either ignore critical file analysis routines or misinterpret file structure information. The flaw operates at the core of the antivirus detection engine's file format analysis capabilities, effectively allowing malicious actors to craft ELF files that appear legitimate to the security software while containing hidden malicious code.
The operational impact of this vulnerability extends beyond simple detection bypass, creating significant risks for organizations relying on these antivirus solutions for endpoint protection. Attackers can leverage this weakness to deliver malware payloads that would normally be detected and blocked by standard antivirus scanning processes, potentially leading to system compromise, data exfiltration, and lateral movement within networks. The vulnerability affects systems running Linux and Unix-based environments where ELF files are commonly used for executables, making it particularly dangerous in enterprise settings where these operating systems are prevalent. The potential for exploitation increases when considering that the vulnerability affects multiple vendors, suggesting a widespread issue that could impact numerous organizations simultaneously, potentially allowing attackers to target specific antivirus implementations or combinations of products.
Security professionals should implement immediate mitigations including updating antivirus signatures and software versions to address the affected implementations, while also considering network-level monitoring to detect anomalous ELF file behavior. The vulnerability demonstrates the importance of robust input validation and proper file format parsing in security software, aligning with CWE-20 (Improper Input Validation) and CWE-129 (Improper Validation of Array Index) categories. From an ATT&CK framework perspective, this vulnerability maps to techniques involving execution through file format manipulation and evasion of security controls, specifically T1059.007 (Command and Scripting Interpreter: PowerShell) and T1070.004 (Indicator Removal on Host: File Deletion) through potential bypass of detection mechanisms. Organizations should also consider implementing additional layers of protection including behavioral analysis, network traffic monitoring, and regular security assessments to identify and remediate similar parsing vulnerabilities across their security infrastructure.