CVE-2017-7594 in LibTIFF
Summary
by MITRE
The OJPEGReadHeaderInfoSecTablesDcTable function in tif_ojpeg.c in LibTIFF 4.0.7 allows remote attackers to cause a denial of service (memory leak) via a crafted image.
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Analysis
by VulDB Data Team • 11/27/2022
The vulnerability identified as CVE-2017-7594 resides within the LibTIFF library version 4.0.7, specifically within the OJPEGReadHeaderInfoSecTablesDcTable function located in the tif_ojpeg.c file. This flaw represents a memory leak condition that can be exploited by remote attackers through the careful crafting of image files. The issue manifests when the library processes specially constructed image data that triggers improper memory management during the decompression of OJPEG (Old JPEG) formatted image sections. The vulnerability is classified as a denial of service condition, where the attacker can cause the application using LibTIFF to consume excessive memory resources without proper cleanup, ultimately leading to system instability or resource exhaustion.
The technical implementation of this vulnerability stems from inadequate memory management within the OJPEG decoding process. When the OJPEGReadHeaderInfoSecTablesDcTable function encounters malformed or crafted image data, it fails to properly release allocated memory blocks that were allocated during the parsing of the image header information. This memory leak occurs because the function does not implement proper error handling or cleanup routines when processing invalid data structures within the DC (Difference Coding) table section of the OJPEG format. The flaw operates at the intersection of image parsing and memory management, where the library's failure to validate data integrity during the decoding process leads to accumulation of unreleased memory segments. This behavior aligns with CWE-401, which specifically addresses improper release of memory, and demonstrates how inadequate resource management in image processing libraries can create persistent memory consumption issues.
The operational impact of CVE-2017-7594 extends beyond simple resource exhaustion, as it can affect any application that relies on LibTIFF for image processing, particularly those handling untrusted image data from external sources. Web applications, image servers, content management systems, and any software that processes user-uploaded images become vulnerable to this attack vector. The vulnerability is particularly concerning because it can be exploited remotely without requiring authentication or specialized privileges, making it an attractive target for attackers seeking to disrupt services. Applications using LibTIFF in server environments may experience gradual memory degradation over time, potentially leading to application crashes, service unavailability, or even system-wide performance degradation. The memory leak can compound over time, especially in applications that process multiple images or are subject to continuous image processing requests, creating a persistent DoS condition that is difficult to detect and remediate.
Mitigation strategies for CVE-2017-7594 should focus on both immediate patching and defensive programming practices. The most effective solution involves upgrading to LibTIFF version 4.0.8 or later, where the memory leak has been addressed through proper memory management and cleanup routines. Organizations should also implement input validation and sanitization measures, particularly for image files received from untrusted sources, to prevent malformed data from reaching the vulnerable parsing functions. Network-level protections such as image validation proxies or content filtering systems can provide additional defense in depth. From a security monitoring perspective, system administrators should establish memory usage monitoring for applications that process images, as abnormal memory consumption patterns may indicate exploitation attempts. The vulnerability demonstrates the importance of proper resource management in security-critical libraries and highlights how seemingly minor memory handling issues can create significant operational risks. Security practitioners should also consider implementing application sandboxing or containerization for image processing services to limit the potential impact of such vulnerabilities. The ATT&CK framework categorizes this type of vulnerability under privilege escalation and resource exhaustion techniques, emphasizing the need for comprehensive memory management practices in image processing libraries and the importance of regular security updates to prevent exploitation of such memory-related flaws.