CVE-2017-9202 in ImageWorsener
Summary
by MITRE
imagew-cmd.c:854:45 in libimageworsener.a in ImageWorsener 1.3.1 allows remote attackers to cause a denial of service (divide-by-zero error) via a crafted image, related to imagew-api.c.
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Analysis
by VulDB Data Team • 12/07/2022
The vulnerability identified as CVE-2017-9202 represents a critical divide-by-zero error within the ImageWorsener library version 1.3.1, specifically manifesting in the imagew-cmd.c file at line 854. This flaw occurs during image processing operations when the software encounters a malformed input image that triggers an arithmetic exception. The vulnerability is classified under CWE-369, which denotes a divide-by-zero condition that can lead to system instability and denial of service. The issue stems from inadequate input validation within the image processing pipeline, where the software fails to properly sanitize or verify image metadata before attempting mathematical operations. Attackers can exploit this weakness by crafting malicious image files that contain malformed parameters or headers designed to trigger the division operation with a zero operand. The vulnerability is particularly concerning as it exists in the core image processing functionality, making it accessible through any application that utilizes the affected library. This type of flaw falls under the ATT&CK technique T1499.004, specifically targeting network infrastructure by causing denial of service conditions that can impact availability.
The technical implementation of this vulnerability involves a mathematical operation within the imagew-api.c component that is called by imagew-cmd.c, where the software attempts to perform division operations on image parameters without proper validation of divisor values. When processing crafted images, the software encounters image data that contains zero values in critical mathematical operands, leading to the division-by-zero exception. This exception typically results in program termination or system crash, thereby enabling a remote attacker to perform a denial of service attack against systems processing images through the vulnerable library. The flaw demonstrates poor error handling practices and insufficient defensive programming measures that should be implemented when dealing with external input data. The vulnerability affects systems where ImageWorsener is integrated as a library component, particularly web applications, image processing servers, and content management systems that handle user-uploaded media files. The attack surface is broad since any application utilizing this library for image manipulation or conversion becomes susceptible to this specific denial of service condition.
The operational impact of CVE-2017-9202 extends beyond simple service interruption to potentially compromise system availability and reliability in environments where image processing is critical. Systems that rely on ImageWorsener for automated image handling, such as social media platforms, e-commerce websites, or content delivery networks, could experience widespread service degradation when malicious image files are processed. The vulnerability is particularly dangerous in automated processing environments where batch operations might be initiated, as a single malicious file could cause cascading failures throughout the processing pipeline. This type of vulnerability aligns with ATT&CK tactic TA0040, which covers resource exploitation, where attackers target system resources to prevent legitimate users from accessing services. Organizations using vulnerable versions of ImageWorsener should consider the potential for extended downtime, increased operational overhead, and possible reputational damage from service unavailability. The vulnerability also highlights the importance of input sanitization and defensive programming practices, as similar flaws may exist in other mathematical operations within the codebase. Proper patch management and version updates are essential to mitigate this risk, as the vulnerability has been addressed in subsequent releases of the ImageWorsener library.
Organizations should implement immediate mitigations including updating to patched versions of ImageWorsener, implementing input validation measures, and deploying network segmentation to limit exposure. The vulnerability demonstrates the necessity of robust error handling and input validation in image processing libraries, as similar divide-by-zero conditions could exist in other mathematical operations. Security teams should also consider implementing monitoring for unusual processing patterns that might indicate exploitation attempts, as well as establishing secure image handling protocols that include proper sanitization before any processing occurs. The flaw serves as a reminder of the critical importance of defensive programming techniques and comprehensive testing of external input handling in security-sensitive applications. This vulnerability reinforces the principle that image processing libraries, due to their exposure to potentially malicious user input, require rigorous security testing and validation to prevent exploitation. The ATT&CK framework categorizes this vulnerability as a system resource compromise, emphasizing the need for organizations to maintain updated software components and implement proper access controls to prevent exploitation.