CVE-2018-8050 in AFFLIB
Summary
by MITRE
The af_get_page() function in lib/afflib_pages.cpp in AFFLIB (aka AFFLIBv3) through 3.7.16 allows remote attackers to cause a denial of service (segmentation fault) via a corrupt AFF image that triggers an unexpected pagesize value.
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Analysis
by VulDB Data Team • 02/21/2023
The vulnerability identified as CVE-2018-8050 resides within the AFFLIB library, specifically in the af_get_page() function located in lib/afflib_pages.cpp. This issue affects AFFLIB versions through 3.7.16 and represents a significant security concern that can be exploited remotely to cause system instability. The vulnerability stems from inadequate input validation and error handling within the library's processing of Advanced Forensic Format (AFF) image files, which are commonly used in digital forensics for storing forensic data and evidence.
The technical flaw manifests when a maliciously crafted AFF image file contains a corrupt pagesize value that triggers an unexpected condition within the af_get_page() function. This condition leads to a segmentation fault, causing the application to crash and resulting in a denial of service condition. The vulnerability is particularly concerning because it can be exploited remotely through the processing of untrusted AFF image files, making it a potential vector for attackers to disrupt forensic analysis workflows and digital investigation processes. The root cause aligns with CWE-125, which describes out-of-bounds read vulnerabilities, and CWE-248, which covers unchecked exceptions in software systems.
From an operational perspective, this vulnerability poses substantial risks to digital forensics environments where AFFLIB is extensively used for forensic image processing and analysis. Organizations relying on AFF format for evidence storage and examination face potential disruption of their investigative processes when encountering maliciously crafted images. The denial of service condition can halt critical forensic workflows, potentially delaying investigations and compromising the integrity of forensic operations. Security teams and digital forensics professionals must consider this vulnerability as a potential threat to their operational continuity, particularly when dealing with untrusted image sources or when processing evidence from potentially compromised systems.
The impact of this vulnerability extends beyond simple service disruption, as it can compromise the reliability of forensic analysis tools that depend on AFFLIB. Attackers could exploit this weakness to target forensic workstations, servers, or automated analysis systems, potentially causing cascading failures in digital investigation environments. The vulnerability demonstrates the importance of robust input validation in security-critical libraries and highlights the need for proper error handling mechanisms to prevent unexpected crashes. Mitigation strategies should include immediate patching of affected AFFLIB versions, implementation of proper input validation procedures, and consideration of alternative forensic image formats or additional verification mechanisms for processing untrusted evidence files. This vulnerability also aligns with ATT&CK technique T1499, which covers network denial of service attacks, and emphasizes the importance of secure coding practices in forensic software development.