CVE-2017-16910 in LibRaw
Summary
by MITRE
An error within the "LibRaw::xtrans_interpolate()" function (internal/dcraw_common.cpp) in LibRaw versions prior to 0.18.6 can be exploited to cause an invalid read memory access and subsequently a Denial of Service condition.
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Analysis
by VulDB Data Team • 06/13/2023
The vulnerability identified as CVE-2017-16910 resides within the LibRaw library's image processing functionality, specifically in the xtrans_interpolate() function located in internal/dcraw_common.cpp. This library serves as a crucial component for digital camera raw image processing, widely utilized across various applications and systems for handling proprietary camera file formats. The flaw manifests as a memory access error that occurs during the interpolation process of raw image data, particularly when processing certain camera sensor patterns that employ xtrans interpolation methods. The vulnerability represents a classic case of improper input validation and memory handling that can be exploited by malicious actors to disrupt system operations.
The technical implementation of this vulnerability stems from inadequate bounds checking within the xtrans_interpolate() function, which processes raw image data from digital cameras that utilize specific sensor arrangements. When the function encounters malformed or unexpected input data during the interpolation phase, it fails to properly validate memory access boundaries, leading to invalid read operations that can result in segmentation faults or access violations. This type of error falls under the CWE-125 weakness category, which describes out-of-bounds read conditions that can lead to system instability and denial of service scenarios. The function's failure to properly handle edge cases in the interpolation algorithm creates a pathway for attackers to craft specific raw image files that trigger the memory access violation.
The operational impact of this vulnerability extends beyond simple denial of service conditions, as it can affect any system or application that relies on LibRaw for image processing operations. When exploited, the vulnerability can cause applications to crash or become unresponsive, effectively denying service to legitimate users who attempt to process raw camera images. This is particularly concerning in environments where automated image processing systems or server applications handle large volumes of camera raw data, as the vulnerability could be leveraged to create sustained denial of service attacks. The vulnerability's exploitation does not typically allow for code execution or privilege escalation, but the service disruption potential makes it a significant concern for system reliability and availability.
Mitigation strategies for CVE-2017-16910 primarily focus on upgrading to LibRaw version 0.18.6 or later, which contains the necessary patches to address the memory access validation issues. System administrators should prioritize updating all affected applications and services that utilize LibRaw, particularly those handling user-provided image data. Additional protective measures include implementing input validation mechanisms at application layers to sanitize raw image data before processing, deploying intrusion detection systems to monitor for exploitation attempts, and establishing robust error handling routines that can gracefully manage memory access violations. Organizations should also consider implementing network segmentation and access controls to limit exposure of systems that process raw image files. The vulnerability's characteristics align with ATT&CK technique T1499.004, which covers network disruption through resource exhaustion or access violation conditions. Regular security assessments and vulnerability scanning should be conducted to ensure all systems remain protected against similar memory handling flaws that could potentially lead to more severe exploitation vectors.