CVE-2017-7943 in ImageMagick
Summary
by MITRE
The ReadSVGImage function in svg.c in ImageMagick 7.0.5-4 allows remote attackers to consume an amount of available memory via a crafted file.
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Analysis
by VulDB Data Team • 11/29/2022
The vulnerability identified as CVE-2017-7943 represents a critical memory consumption flaw within ImageMagick's SVG processing capabilities, specifically affecting version 7.0.5-4. This issue manifests through the ReadSVGImage function in the svg.c component, where maliciously crafted SVG files can trigger excessive memory allocation behavior that ultimately leads to resource exhaustion. The vulnerability operates by exploiting the way ImageMagick handles SVG image parsing, particularly when processing malformed or specially constructed input files that cause the application to allocate disproportionately large amounts of memory during the rendering process. Such attacks can be executed remotely, making them particularly dangerous in web environments where users might unknowingly encounter malicious SVG content through various attack vectors including web browsers, email attachments, or file sharing platforms.
The technical exploitation of this vulnerability stems from insufficient input validation and memory management within the SVG parsing engine of ImageMagick. When the ReadSVGImage function processes a crafted SVG file, it fails to properly constrain memory allocation based on the actual size requirements of the parsed content, allowing attackers to craft input files that cause the application to allocate memory in a manner that grows exponentially or becomes unbounded. This type of vulnerability aligns with CWE-400, which specifically addresses unchecked resource consumption, and represents a classic example of a memory exhaustion attack that can lead to denial of service conditions. The flaw essentially allows an attacker to cause the target system to consume all available memory resources, potentially leading to system instability, application crashes, or complete system unresponsiveness.
The operational impact of CVE-2017-7943 extends far beyond simple denial of service scenarios, as it can be leveraged in broader attack chains within the MITRE ATT&CK framework under the T1499 category for network denial of service. Systems running vulnerable versions of ImageMagick become susceptible to remote exploitation through any application or service that processes SVG images, including web applications, content management systems, image processing pipelines, and file upload handlers. The vulnerability is particularly concerning in environments where automated image processing occurs, as it can be triggered through legitimate user interactions such as file uploads, image previews, or content rendering operations. Organizations may experience cascading failures across multiple systems if they have not properly secured their image processing workflows, potentially leading to service disruptions, data loss, or the need for emergency system shutdowns during attack mitigation.
Mitigation strategies for this vulnerability require immediate action including updating to ImageMagick versions that contain patches for this specific memory consumption flaw, typically those released after the vulnerability disclosure. System administrators should implement strict input validation measures and consider deploying application firewalls or web application firewalls that can detect and block suspicious SVG content before it reaches the ImageMagick processing engine. Additionally, organizations should consider implementing memory limits and resource constraints on image processing services to prevent complete system exhaustion even if an attack succeeds. The vulnerability also underscores the importance of proper sandboxing mechanisms and input sanitization practices, particularly in applications that handle untrusted image formats. Security teams should monitor for exploitation attempts through network traffic analysis and implement automated response mechanisms that can isolate affected systems or services when memory consumption patterns indicate potential exploitation of this vulnerability.