CVE-2017-5896 in MuPDF
Summary
by MITRE
Heap-based buffer overflow in the fz_subsample_pixmap function in fitz/pixmap.c in MuPDF 1.10a allows remote attackers to cause a denial of service (out-of-bounds read and crash) via a crafted image.
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Analysis
by VulDB Data Team • 08/15/2020
The CVE-2017-5896 vulnerability represents a critical heap-based buffer overflow flaw within the MuPDF document processing library version 1.10a. This vulnerability specifically affects the fz_subsample_pixmap function located in the fitz/pixmap.c source file, which handles image processing operations. The flaw occurs when MuPDF processes specially crafted image files that trigger improper memory management during pixmap subsampling operations. Attackers can exploit this vulnerability by delivering maliciously formatted image content that causes the application to read beyond allocated memory boundaries, resulting in out-of-bounds read conditions and subsequent application crashes. The vulnerability falls under the CWE-121 heap-based buffer overflow category, which is classified as a common weakness in software security practices. This type of vulnerability is particularly dangerous because it can be leveraged for remote code execution or denial of service attacks, depending on the specific implementation and system configuration. The ATT&CK framework categorizes this as a memory corruption vulnerability that can be exploited through crafted input delivery mechanisms, specifically targeting the application's image processing pipeline.
The technical exploitation of CVE-2017-5896 requires attackers to construct a malicious image file that triggers the vulnerable code path within the fz_subsample_pixmap function. During normal operation, this function processes image data by subsampling pixel values to reduce memory consumption and improve rendering performance. However, when malformed image parameters are provided, the function fails to properly validate input boundaries before performing memory operations. The heap-based nature of the overflow means that memory corruption occurs within the heap allocation region, potentially affecting adjacent memory blocks and leading to unpredictable application behavior. The vulnerability manifests as an out-of-bounds read operation that can cause the application to crash or behave erratically, effectively creating a denial of service condition. This type of memory corruption vulnerability is particularly challenging to detect and prevent because it often requires careful analysis of the input data structure and memory management patterns within the affected code segment.
The operational impact of CVE-2017-5896 extends beyond simple denial of service scenarios, as it can significantly compromise the availability and stability of systems that rely on MuPDF for document processing. Applications using affected versions of MuPDF, including web browsers, document viewers, and content management systems, become vulnerable to remote exploitation when processing untrusted image content. The vulnerability affects both desktop and server environments where MuPDF is integrated, potentially creating widespread service disruption across multiple platforms and applications. Security researchers have noted that the exploitability of this vulnerability is relatively high due to the common usage patterns of image processing libraries and the ease with which attackers can craft malicious image files. Organizations relying on MuPDF for document handling must consider the broader implications of this vulnerability, particularly in environments where users can upload or receive untrusted content. The vulnerability also highlights the importance of proper input validation and memory boundary checking in multimedia processing libraries, as these components are frequently targeted by attackers seeking to exploit memory corruption flaws.
Mitigation strategies for CVE-2017-5896 should focus on immediate patching of affected MuPDF installations to version 1.11 or later, where the vulnerability has been addressed through improved input validation and boundary checking mechanisms. Organizations should implement strict image validation protocols that sanitize all incoming image content before processing, particularly in web applications and document handling systems. Network-level protections such as content filtering and sandboxing mechanisms can provide additional layers of defense against exploitation attempts. The vulnerability serves as a reminder of the critical importance of regular security updates and vulnerability management processes, particularly for widely-used open source libraries that handle untrusted input data. Security teams should also consider implementing monitoring and alerting mechanisms to detect potential exploitation attempts, as the out-of-bounds read conditions may leave detectable traces in system logs or memory dumps. Additionally, developers should adopt secure coding practices and conduct thorough code reviews focusing on memory management and input validation, particularly for functions that handle image processing and memory allocation operations. The remediation process should include comprehensive testing to ensure that patched versions maintain functionality while eliminating the vulnerability conditions that lead to heap-based buffer overflows.