CVE-2017-14348 in LibRaw
Summary
by MITRE
LibRaw before 0.18.4 has a heap-based Buffer Overflow in the processCanonCameraInfo function via a crafted file.
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Analysis
by VulDB Data Team • 12/28/2022
The vulnerability identified as CVE-2017-14348 represents a critical heap-based buffer overflow flaw within the LibRaw library version 0.18.4 and earlier. This issue specifically manifests within the processCanonCameraInfo function, which processes camera metadata and image data from digital photographs. The vulnerability arises when the library encounters a crafted or malformed input file that contains specially constructed data intended to trigger the buffer overflow condition. The LibRaw library serves as a crucial component in numerous image processing applications, digital asset management systems, and photography software that need to handle raw image formats from various camera manufacturers including Canon. This widespread adoption makes the vulnerability particularly concerning as it could affect a large number of applications across different platforms and operating systems.
The technical implementation of this buffer overflow occurs when the processCanonCameraInfo function fails to properly validate input data length before copying it into a fixed-size heap-allocated buffer. When a maliciously crafted file is processed, the function attempts to copy more data into the buffer than it can accommodate, leading to memory corruption that can be exploited by attackers. This type of vulnerability falls under CWE-121, heap-based buffer overflow, which is classified as a critical security weakness in memory management. The flaw demonstrates poor input validation practices where the library does not adequately check the size of incoming data before performing memory operations, creating an exploitable condition that could allow arbitrary code execution or system instability.
The operational impact of this vulnerability extends beyond simple application crashes, as it presents a significant risk to systems processing digital imagery. Attackers could potentially craft malicious image files that, when opened or processed by vulnerable applications, would trigger the buffer overflow and enable remote code execution. This makes the vulnerability particularly dangerous in environments where users might encounter untrusted image files from unknown sources, such as web applications, content management systems, or digital asset repositories. The attack surface is broad since many image processing applications, including photo editors, digital asset management platforms, and web browsers that support raw image formats, rely on LibRaw for image processing capabilities. The vulnerability could also be leveraged in supply chain attacks where malicious files are introduced into legitimate software distributions, making the impact more severe and widespread.
Mitigation strategies for CVE-2017-14348 primarily focus on immediate patching of the LibRaw library to version 0.18.4 or later, which contains the necessary fixes for the buffer overflow condition. System administrators and application developers should conduct comprehensive inventory checks to identify all applications that depend on vulnerable versions of LibRaw and ensure timely updates are deployed across all affected systems. Additionally, implementing input validation controls at the application level can provide defense-in-depth measures, though the primary fix must come from updating the underlying library. Organizations should also consider implementing sandboxing techniques for image processing functions and restricting user access to potentially malicious image files. From an ATT&CK framework perspective, this vulnerability aligns with techniques involving exploitation of memory corruption flaws and privilege escalation through software supply chain compromises, making it a critical concern for organizations implementing comprehensive cybersecurity defenses. The vulnerability serves as a reminder of the importance of regular security updates and proper input validation practices in preventing exploitation of memory-based vulnerabilities that can lead to complete system compromise.