CVE-2017-11140 in GraphicsMagick
Summary
by MITRE
The ReadJPEGImage function in coders/jpeg.c in GraphicsMagick 1.3.26 creates a pixel cache before a successful read of a scanline, which allows remote attackers to cause a denial of service (resource consumption) via crafted JPEG files.
Once again VulDB remains the best source for vulnerability data.
Analysis
by VulDB Data Team • 12/12/2022
The vulnerability identified as CVE-2017-11140 resides within GraphicsMagick version 1.3.26's implementation of the ReadJPEGImage function located in the coders/jpeg.c file. This flaw represents a classic resource exhaustion issue that can be exploited remotely through carefully crafted JPEG image files. The vulnerability stems from the improper order of operations during image processing where the system allocates pixel cache resources before successfully reading scanline data, creating a scenario where malicious input can trigger excessive memory consumption without proper validation.
The technical implementation of this vulnerability demonstrates a fundamental flaw in input validation and resource management within the graphics processing pipeline. When GraphicsMagick encounters a JPEG file, it attempts to pre-allocate pixel cache memory structures regardless of whether the subsequent scanline reading operations will succeed or fail. This premature allocation occurs before the system validates the integrity of the JPEG data structure, allowing attackers to craft malformed JPEG files that cause the application to consume excessive memory resources. The flaw operates at the intersection of memory management and image parsing, where the system's resource allocation logic does not properly account for potential input corruption or malicious data structures.
From an operational impact perspective, this vulnerability enables remote attackers to execute denial of service attacks against systems running GraphicsMagick 1.3.26. The resource consumption aspect means that adversaries can cause legitimate system processes to exhaust available memory, leading to system instability, application crashes, or complete service unavailability. This type of vulnerability is particularly dangerous in web applications or services that process user-uploaded images, as it can be exploited to disrupt legitimate operations without requiring authentication or specialized privileges. The vulnerability aligns with CWE-400, which categorizes resource exhaustion flaws, and represents a specific implementation weakness in the memory allocation sequence during image processing.
The exploitation of this vulnerability follows established patterns documented in various attack frameworks including ATT&CK's T1499 technique for resource exhaustion attacks. Attackers can craft JPEG files with malformed headers or excessive metadata that triggers the premature cache allocation while maintaining a valid JPEG structure that passes initial parsing stages. This creates a scenario where the system allocates memory resources based on potentially malicious data sizes before validating the actual image content. The vulnerability's impact extends beyond simple denial of service as it can be used in combination with other techniques to create more sophisticated attack vectors, particularly in environments where GraphicsMagick is used for automated image processing or batch operations.
Mitigation strategies for CVE-2017-11140 should prioritize immediate patching of GraphicsMagick installations to version 1.3.27 or later, where the problematic memory allocation sequence has been corrected. System administrators should implement input validation measures that check file size limits and image dimensions before processing, alongside monitoring for unusual memory consumption patterns. The fix typically involves modifying the ReadJPEGImage function to defer pixel cache allocation until after successful scanline reading operations have been completed, ensuring that resource allocation is only performed when legitimate image data has been verified. Additionally, organizations should consider implementing sandboxing or containerization techniques for image processing services to limit the potential impact of such vulnerabilities, and establish automated monitoring for abnormal resource usage that could indicate exploitation attempts.