CVE-2017-11116 in OpenExif
Summary
by MITRE
The ExifImageFile::readDQT function in ExifImageFileRead.cpp in OpenExif 2.1.4 allows remote attackers to cause a denial of service (heap-based buffer over-read and application crash) via a crafted jpg file.
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Analysis
by VulDB Data Team • 11/02/2019
The vulnerability identified as CVE-2017-11116 represents a critical heap-based buffer over-read flaw within the ExifImageFile::readDQT function of OpenExif version 2.1.4. This issue resides in the ExifImageFileRead.cpp source file and manifests when processing specially crafted jpeg image files. The flaw stems from inadequate input validation and bounds checking during the parsing of quantization tables within jpeg metadata structures. Attackers can exploit this vulnerability by preparing a malicious jpeg file that contains malformed quantization table data, which when processed by the vulnerable library triggers memory access violations. The vulnerability specifically targets the heap memory management aspects of the application, where the software attempts to read beyond the allocated buffer boundaries when parsing the DQT (Define Quantization Table) segments of jpeg files.
The technical execution of this vulnerability follows a well-established pattern of memory corruption exploits that aligns with CWE-125, which describes out-of-bounds read conditions. When the ExifImageFile::readDQT function processes the malicious input, it fails to properly validate the length of quantization table data before attempting to read from the heap memory region. This allows an attacker to craft a jpeg file with oversized or malformed quantization table markers that exceed the expected buffer size. The application's failure to implement proper bounds checking results in a buffer over-read condition where the program attempts to access memory locations beyond the allocated heap buffer. This memory corruption directly leads to application instability and ultimately causes a crash or denial of service condition. The vulnerability demonstrates characteristics consistent with heap-based buffer overflow patterns that are commonly exploited in application security attacks.
The operational impact of CVE-2017-11116 extends beyond simple application crashes to encompass broader system availability and reliability concerns. Systems that process jpeg files through the vulnerable OpenExif library, including web applications, image processing servers, and content management systems, become susceptible to denial of service attacks. Attackers can remotely trigger these vulnerabilities by uploading or accessing malicious jpeg files, making this particularly dangerous in web-facing applications where users can upload content. The vulnerability affects systems that rely on Exif metadata parsing for image processing workflows, potentially disrupting legitimate image handling operations. In environments where automated image processing is critical, such as social media platforms, e-commerce sites, or digital asset management systems, this vulnerability could result in significant service degradation or complete system unavailability. The impact is amplified when considering that many applications use OpenExif as a dependency for handling image metadata, making the attack surface much broader than initially apparent.
Mitigation strategies for CVE-2017-11116 should focus on immediate patching and application-level defenses. The most effective solution involves upgrading to a patched version of OpenExif that addresses the buffer over-read condition in the ExifImageFile::readDQT function. Organizations should also implement input validation measures at application boundaries, including sanitizing jpeg file inputs before processing and implementing strict file format validation. Network-level defenses such as web application firewalls can help detect and block malicious jpeg files, though these are less effective than proper code-level fixes. Additionally, implementing proper memory protection mechanisms, including stack canaries and address space layout randomization, can make exploitation more difficult. Security teams should also consider implementing monitoring for unusual application crash patterns or resource consumption spikes that might indicate exploitation attempts. The remediation process should include thorough testing of patched libraries in development environments to ensure compatibility and prevent regressions in legitimate image processing functionality. Organizations should also review their dependency management practices to identify and remediate similar vulnerabilities in other third-party libraries that might be susceptible to similar buffer over-read conditions.