CVE-2017-9155 in AutoTrace
Summary
by MITRE
libautotrace.a in AutoTrace 0.31.1 allows remote attackers to cause a denial of service (invalid read and SEGV), related to the input_pnm_reader function in input-pnm.c:243:3.
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Analysis
by VulDB Data Team • 10/02/2020
The vulnerability identified as CVE-2017-9155 affects AutoTrace version 0.31.1 through a flaw in the libautotrace.a library component. This issue manifests as a remote denial of service condition that can be triggered by malicious input data, specifically within the input_pnm_reader function located in the input-pnm.c source file at line 243. The vulnerability represents a critical security flaw that can be exploited by remote attackers to disrupt service availability and potentially crash the affected system.
The technical root cause of this vulnerability stems from insufficient input validation within the PNM (Portable AnyMap) file parsing functionality of AutoTrace. When the input_pnm_reader function processes malformed or specially crafted PNM image files, it fails to properly validate the input data structure, leading to an invalid memory read operation followed by a segmentation fault. This type of vulnerability falls under the category of improper input validation and memory handling issues, which are commonly classified under CWE-125 for out-of-bounds read conditions and CWE-119 for improper restriction of operations within a memory buffer. The function's failure to properly handle edge cases in the input data causes the program to attempt accessing memory locations that are either invalid or unauthorized, resulting in the segmentation fault that terminates the application.
The operational impact of CVE-2017-9155 extends beyond simple service disruption to potentially enable more sophisticated attack vectors. Remote attackers can leverage this vulnerability to perform denial of service attacks against systems that utilize AutoTrace for image processing or conversion tasks. This vulnerability is particularly concerning in environments where AutoTrace is used as a backend service or integrated into larger applications, as it can be exploited to continuously disrupt operations without requiring authentication or elevated privileges. The vulnerability can be triggered through various attack vectors including web applications that accept image uploads, automated processing pipelines, or any system that processes PNM formatted images through the affected AutoTrace library. From an adversary perspective, this vulnerability aligns with ATT&CK technique T1499.004 for network denial of service, where attackers can leverage software weaknesses to cause service unavailability.
The mitigation strategies for CVE-2017-9155 primarily focus on immediate remediation through software updates and patches provided by the AutoTrace maintainers. Organizations should prioritize upgrading to AutoTrace versions that have addressed this vulnerability, as the original 0.31.1 release contains known issues that have been resolved in subsequent releases. Additionally, implementing proper input validation mechanisms at the application level can provide defense-in-depth protection, where applications using AutoTrace can validate image file formats and content before passing them to the library functions. Network-level protections such as input sanitization proxies or web application firewalls can also help detect and block malicious input patterns that may trigger this vulnerability. System administrators should also consider implementing monitoring and alerting mechanisms to detect potential exploitation attempts, as the segmentation fault behavior may generate specific system logs or crash reports that can indicate attempted exploitation of this vulnerability.