CVE-2017-11166 in ImageMagick
Summary
by MITRE
The ReadXWDImage function in coders\xwd.c in ImageMagick 7.0.5-6 has a memory leak vulnerability that can cause memory exhaustion via a crafted length (number of color-map entries) field in the header of an XWD file.
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Analysis
by VulDB Data Team • 12/12/2022
The vulnerability identified as CVE-2017-11166 resides within the ImageMagick image processing library, specifically in the ReadXWDImage function located in the coders\xwd.c file. This flaw manifests as a memory leak that occurs when processing X Window Dump format files, which are commonly used for screen captures and window snapshots in X11 environments. The vulnerability is particularly concerning because it can be exploited through crafted input files that manipulate the length field in the XWD file header, specifically the number of color-map entries field that dictates how many color palette entries should be allocated in memory. When an attacker crafts an XWD file with an inflated length value, the application allocates memory based on this malformed parameter without proper validation, leading to excessive memory consumption that can eventually result in system resource exhaustion and potential denial of service conditions. The vulnerability represents a classic case of insufficient input validation where the application fails to properly sanitize or limit the memory allocation based on user-supplied data.
The technical nature of this flaw aligns with CWE-401, which describes improper handling of memory allocation failures or insufficient checks for resource exhaustion conditions. The vulnerability operates at the boundary between user input validation and resource management, where the XWD file header parsing logic does not adequately verify that the specified number of color-map entries remains within reasonable bounds. When the ReadXWDImage function processes a malformed XWD file, it allocates memory based on the attacker-controlled length field without implementing proper bounds checking or maximum limits on the allocation size. This creates a scenario where a single malicious file can cause the application to consume excessive memory resources, potentially leading to system instability or complete application crash. The flaw demonstrates how seemingly innocuous header fields in image formats can be weaponized to exploit memory management vulnerabilities in image processing libraries that handle multiple file formats.
The operational impact of CVE-2017-11166 extends beyond simple denial of service conditions, as it can be leveraged in broader attack scenarios within environments where ImageMagick is used for image processing. Systems that automatically process user-uploaded images, such as web applications, content management systems, or file sharing platforms, become vulnerable to memory exhaustion attacks that can degrade service availability or potentially crash critical processes. The vulnerability is particularly dangerous in server environments where ImageMagick is integrated into automated workflows, as a single malicious XWD file could cause cascading failures across multiple processes or services. From an attacker perspective, this vulnerability maps to ATT&CK technique T1059.007 for execution through image processing libraries and T1499.004 for denial of service attacks. The memory leak aspect of this vulnerability can also contribute to long-term system instability, as repeated exploitation can gradually consume available memory resources and potentially cause system crashes or performance degradation.
Mitigation strategies for CVE-2017-11166 should focus on both immediate patching and defensive programming practices. The primary solution involves updating to ImageMagick versions that contain the appropriate fixes for this memory leak, as the vulnerability was addressed in subsequent releases through proper bounds checking and memory allocation limits. Organizations should implement input validation at multiple levels, including file format validation and size restriction for image processing operations, to prevent malformed files from reaching the vulnerable parsing functions. Network-based defenses can include implementing file type detection and limiting the maximum file sizes for image uploads, while application-level protections should enforce strict resource limits and memory monitoring. Additionally, implementing sandboxing techniques for image processing operations and using alternative image libraries with more robust memory management can provide defense in depth. The vulnerability underscores the importance of proper input validation and resource management in image processing libraries, as it demonstrates how header field manipulation can lead to critical memory exhaustion conditions that affect system stability and availability.