CVE-2017-9173 in AutoTrace
Summary
by MITRE
libautotrace.a in AutoTrace 0.31.1 has a heap-based buffer overflow in the ReadImage function in input-bmp.c:497:29.
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Analysis
by VulDB Data Team • 10/02/2020
The vulnerability identified as CVE-2017-9173 represents a critical heap-based buffer overflow within the AutoTrace 0.31.1 software library known as libautotrace.a. This flaw specifically manifests within the ReadImage function located in the input-bmp.c source file at line 497, where a buffer overflow occurs at column 29. AutoTrace is a graphics conversion tool that transforms bitmap images into vector graphics, commonly used in graphic design and digital illustration workflows. The vulnerability arises when processing specially crafted bitmap image files that trigger an improper memory allocation during the image reading process. The heap-based nature of this overflow indicates that malicious input can cause memory corruption in the program's heap memory space, potentially allowing attackers to execute arbitrary code or cause application crashes.
The technical exploitation of this vulnerability stems from insufficient bounds checking within the image parsing logic. When AutoTrace processes a malformed bmp file, the ReadImage function fails to properly validate the size of data being read into a buffer, leading to memory overwrite conditions. This type of vulnerability falls under CWE-121, which categorizes heap-based buffer overflow conditions where insufficient memory bounds checking allows attackers to overwrite adjacent heap memory locations. The vulnerability is particularly concerning because it occurs during normal file processing operations, meaning that simply opening a maliciously crafted bmp file could trigger the exploit. The specific location at input-bmp.c:497:29 suggests that the issue involves a memcpy or similar memory copying operation where the source buffer size exceeds the destination buffer capacity.
From an operational perspective, this vulnerability creates significant security risks for systems that utilize AutoTrace for image processing tasks. Attackers could potentially craft malicious bitmap files that, when processed by AutoTrace, would cause the application to crash or execute unintended code. The impact extends beyond simple denial of service scenarios since heap overflows often provide opportunities for more sophisticated attacks including privilege escalation or remote code execution. Systems that automatically process user-uploaded images or batch process large numbers of bitmap files would be particularly vulnerable. The vulnerability affects not only direct users of AutoTrace but also applications that depend on the libautotrace library for vector graphics conversion. This type of flaw aligns with ATT&CK technique T1203, which covers exploitation of software vulnerabilities through buffer overflow conditions.
Mitigation strategies for CVE-2017-9173 should prioritize immediate software updates to versions that have patched the buffer overflow vulnerability. Organizations should implement input validation measures that restrict the types of bitmap files processed by AutoTrace installations, particularly those that are malformed or exceed expected size parameters. Network segmentation and access controls can help limit exposure by restricting which systems have access to AutoTrace functionality. Regular security assessments should include vulnerability scanning for outdated AutoTrace installations, and automated patch management systems should be deployed to ensure timely remediation. Additionally, implementing runtime protections such as address space layout randomization and stack canaries can provide defense-in-depth measures against exploitation attempts. The vulnerability demonstrates the importance of proper memory management practices in image processing libraries and highlights the need for comprehensive input validation in all file parsing operations.