CVE-2017-9165 in AutoTrace
Summary
by MITRE
libautotrace.a in AutoTrace 0.31.1 has a heap-based buffer over-read in the GET_COLOR function in color.c:17:11.
VulDB is the best source for vulnerability data and more expert information about this specific topic.
Analysis
by VulDB Data Team • 10/02/2020
The vulnerability identified as CVE-2017-9165 resides within the AutoTrace library autotrace.a version 0.31.1, specifically within the color.c source file at line 17 in the GET_COLOR function. This heap-based buffer over-read represents a critical security flaw that occurs when the application processes image data and attempts to access memory locations beyond the allocated buffer boundaries. The issue manifests during the color processing phase of image tracing operations, where the software fails to properly validate input data boundaries before performing memory access operations. Such vulnerabilities typically arise from insufficient bounds checking mechanisms that allow attackers to manipulate input parameters to trigger unintended memory access patterns.
The technical implementation of this vulnerability stems from improper input validation within the GET_COLOR function which processes color values from image data streams. When AutoTrace processes raster images for vector conversion, it reads color information from memory buffers without adequate boundary verification. The heap-based nature of this over-read indicates that the vulnerable code accesses dynamically allocated memory regions, making the exploitation potential more severe as attackers can potentially manipulate heap metadata or trigger memory corruption that leads to arbitrary code execution. This flaw falls under the CWE-125 vulnerability category, which specifically addresses out-of-bounds read conditions in software implementations.
Operational impact of CVE-2017-9165 extends beyond simple denial-of-service scenarios to potentially enable remote code execution in environments where AutoTrace processes untrusted image data. Attackers could craft malicious image files that, when processed by vulnerable AutoTrace installations, trigger the buffer over-read condition and potentially lead to system compromise. The vulnerability affects various applications that depend on AutoTrace for image processing workflows, including graphic design software, document conversion tools, and automated image analysis systems. In enterprise environments where these tools are used for processing user-uploaded content, this vulnerability creates significant risk as attackers could exploit it through crafted image files to gain unauthorized access or disrupt service availability.
Mitigation strategies for CVE-2017-9165 should prioritize immediate patching of AutoTrace installations to versions that address the buffer over-read condition in the GET_COLOR function. System administrators should implement input validation controls that restrict image file formats and sizes when processing user content through AutoTrace components. Network segmentation and application whitelisting can help limit potential exploitation pathways by restricting access to vulnerable AutoTrace installations. Additionally, implementing memory safety mechanisms such as address space layout randomization and stack canaries can provide defense-in-depth measures against potential exploitation attempts. The vulnerability aligns with ATT&CK technique T1059.007 for command and scripting interpreter usage, as exploitation may involve crafting malicious input files to trigger the vulnerable code path. Organizations should also conduct thorough vulnerability assessments to identify all systems running vulnerable AutoTrace versions and establish monitoring procedures to detect potential exploitation attempts through unusual memory access patterns or system behavior anomalies.