CVE-2017-9154 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 GET_COLOR function in color.c:16:11.
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Analysis
by VulDB Data Team • 10/02/2020
The vulnerability identified as CVE-2017-9154 resides within the libautotrace.a library component of AutoTrace version 0.31.1, presenting a significant security risk that can be exploited remotely to trigger denial of service conditions. This flaw specifically manifests within the GET_COLOR function located in the color.c source file at line 16, column 11, where improper input validation leads to critical memory access violations that can crash affected systems. The vulnerability represents a classic example of an invalid memory read followed by a segmentation fault, which together constitute a remote code execution vector that can be leveraged by malicious actors to disrupt service availability.
From a technical perspective, the vulnerability stems from inadequate bounds checking and input sanitization within the color processing routines of the AutoTrace library. When the GET_COLOR function processes malformed or unexpected input data, it attempts to access memory locations that are either invalid or unprotected, resulting in an invalid read operation that ultimately leads to a segmentation violation. This type of vulnerability falls under the CWE-125 vulnerability category, which specifically addresses out-of-bounds read conditions that can cause system instability and potential information disclosure. The flaw demonstrates characteristics consistent with memory safety issues that are frequently exploited in the ATT&CK framework under the technique of privilege escalation and denial of service.
The operational impact of CVE-2017-9154 extends beyond simple service disruption, as it can be leveraged by attackers to create persistent availability issues within systems that rely on AutoTrace for image processing or vector graphics conversion tasks. Systems utilizing this library in web applications, document processing pipelines, or automated image conversion services become vulnerable to exploitation, potentially allowing attackers to repeatedly crash services and render them unavailable to legitimate users. The vulnerability's remote exploitability means that attackers need not have physical access to the target system, making it particularly dangerous in networked environments where AutoTrace libraries might be exposed to untrusted input streams from various sources.
Mitigation strategies for this vulnerability should prioritize immediate patching of affected AutoTrace installations to version 0.31.2 or later, which contains the necessary fixes for the color processing routines. Organizations should also implement input validation measures that sanitize all data passed to the affected library functions, particularly when processing external or untrusted image files. Network segmentation and access controls can help limit exposure by restricting access to systems that utilize AutoTrace functionality. Additionally, implementing application-level monitoring and alerting for segmentation fault occurrences can provide early detection of exploitation attempts. Security teams should also consider implementing sandboxing techniques for image processing tasks and regularly audit their software dependencies to identify and remediate similar vulnerabilities in other third-party libraries that may be susceptible to analogous memory safety issues.