CVE-2017-9158 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_raw function in input-pnm.c:336:11.
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Analysis
by VulDB Data Team • 10/02/2020
The vulnerability identified as CVE-2017-9158 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 pnm_load_raw function located in the input-pnm.c file at line 336, where improper input validation leads to critical system instability. The vulnerability represents a classic buffer overflow condition that can be exploited through malformed input data, creating a dangerous scenario for systems that rely on this library for image conversion and tracing operations.
The technical implementation of this vulnerability stems from inadequate bounds checking within the pnm_load_raw function, which processes portable anymap (PNM) image formats. When the function encounters malformed PNM data, it fails to properly validate the input parameters before performing memory operations, resulting in an invalid write operation that subsequently triggers a segmentation fault. This type of flaw falls under CWE-121, which describes stack-based buffer overflow conditions, and represents a direct violation of secure coding practices that mandate proper input validation and memory boundary checks. The vulnerability's impact is particularly severe because it allows remote attackers to craft malicious PNM files that can be processed by applications using the AutoTrace library, leading to system crashes and potential service disruption.
The operational consequences of CVE-2017-9158 extend beyond simple denial of service, as it creates opportunities for more sophisticated attacks within the broader ATT&CK framework. When exploited, this vulnerability can be leveraged as an initial access vector for subsequent exploitation attempts, particularly in environments where AutoTrace is integrated into web applications or automated processing pipelines. The segmentation fault generated by the invalid write operation can cause applications to terminate unexpectedly, potentially leading to data loss or service unavailability. Systems that process untrusted image data, such as content management systems, image processing servers, or any application that utilizes AutoTrace for image conversion, become vulnerable to this attack vector, making it a significant concern for organizations managing digital media workflows.
Mitigation strategies for CVE-2017-9158 should focus on immediate patching of the AutoTrace library to version 0.31.2 or later, which includes the necessary fixes for the input validation issues. Organizations should also implement input sanitization measures that validate image file formats before processing, particularly for any system that accepts user-uploaded content. Network segmentation and access controls can help limit the potential impact of exploitation attempts, while application-level sandboxing can provide additional protection layers. The vulnerability demonstrates the critical importance of proper memory management and input validation in open source libraries, as highlighted by ATT&CK technique T1203 which covers the use of input validation to prevent exploitation. Regular security assessments of third-party libraries and maintaining updated software inventories are essential practices to prevent similar vulnerabilities from compromising system integrity and availability.