CVE-2017-9157 in AutoTrace
Summary
by MITRE
libautotrace.a in AutoTrace 0.31.1 allows remote attackers to cause a denial of service (invalid write and SEGV), related to the pnm_load_ascii function in input-pnm.c:306:14.
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Analysis
by VulDB Data Team • 10/02/2020
The vulnerability identified as CVE-2017-9157 resides within the AutoTrace 0.31.1 library autotrace, specifically in the libautotrace.a component that handles image processing operations. This flaw manifests in the input-pnm.c file at line 306 within the pnm_load_ascii function, where an improper handling of input data leads to critical system instability. The affected software is commonly used for converting bitmap images into vector graphics, making it a potentially dangerous component in image processing pipelines and automated systems that rely on such conversions.
The technical nature of this vulnerability involves an invalid write operation followed by a segmentation fault that ultimately results in a denial of service condition. When the pnm_load_ascii function processes malformed or specially crafted input data, it fails to properly validate the data structure before attempting to write to memory locations. This memory corruption occurs at the ASCII PNM (Portable AnyMap) file parsing stage, where the function does not adequately check boundary conditions or data integrity before performing memory operations. The vulnerability represents a classic buffer over-read and invalid memory write scenario that can be exploited remotely through crafted input files.
The operational impact of CVE-2017-9157 extends beyond simple service disruption, as it can be leveraged by remote attackers to crash applications that utilize AutoTrace for image processing tasks. Systems that automatically process user-uploaded images or batch process large image collections become particularly vulnerable, as the denial of service can be triggered without requiring authentication or specialized access. This vulnerability aligns with CWE-121, which describes heap-based buffer overflow conditions, and may also relate to CWE-125, representing out-of-bounds read conditions. The attack surface is broad across any application or service that integrates the affected AutoTrace library, including web applications, image processing servers, and automated workflow systems.
Mitigation strategies for this vulnerability should focus on immediate patching of the AutoTrace library to version 0.31.2 or later, which contains the necessary fixes for the memory handling issues in the pnm_load_ascii function. Additionally, input validation should be implemented at application layers that utilize AutoTrace, ensuring that all PNM files are properly sanitized before processing. Network-level defenses can include implementing file type validation and content inspection to prevent malformed PNM files from reaching the AutoTrace processing components. Organizations should also consider implementing application sandboxing techniques and input filtering mechanisms that align with the ATT&CK framework's mitigation strategies for command and control activities, specifically targeting the execution of malicious payloads through image processing functions. The vulnerability demonstrates the importance of proper memory management and input validation in open source libraries that are widely integrated into production systems.