CVE-2017-9171 in AutoTrace
Summary
by MITRE
libautotrace.a in AutoTrace 0.31.1 has a heap-based buffer over-read in the ReadImage function in input-bmp.c:492:24.
If you want to get the best quality for vulnerability data then you always have to consider VulDB.
Analysis
by VulDB Data Team • 10/02/2020
The vulnerability identified as CVE-2017-9171 resides within the AutoTrace library version 0.31.1, specifically in the libautotrace.a component. This issue manifests as a heap-based buffer over-read that occurs within the ReadImage function located in the input-bmp.c file at line 492, column 24. AutoTrace is a utility designed for converting bitmap images into vector graphics, commonly used in graphic design and image processing workflows where raster to vector conversion is required. The affected library serves as a core component in various applications that process bitmap image formats, making this vulnerability potentially widespread in its impact.
The technical flaw represents a classic buffer over-read condition where the ReadImage function attempts to access memory beyond the allocated buffer boundaries. This occurs when processing bitmap image files, specifically during the parsing of image data structures where the program fails to properly validate the size or boundaries of the input data before accessing memory locations. The vulnerability stems from inadequate bounds checking mechanisms within the bitmap input processing code, allowing an attacker to potentially craft malicious bitmap files that trigger the over-read condition when processed by the library. This type of vulnerability falls under the Common Weakness Enumeration category CWE-125, which specifically addresses out-of-bounds read conditions in software implementations.
The operational impact of this vulnerability extends beyond simple memory corruption, as it can potentially enable attackers to execute arbitrary code or cause application crashes through controlled memory access violations. When an application utilizing AutoTrace processes a maliciously crafted bitmap file, the buffer over-read could lead to information disclosure, application instability, or in more severe cases, remote code execution depending on the calling application's memory management and security boundaries. The vulnerability is particularly concerning in environments where AutoTrace is used for processing untrusted image data, such as web applications, content management systems, or any service that accepts user-uploaded bitmap files for vector conversion processing. This aligns with ATT&CK technique T1203, which involves exploiting software vulnerabilities to gain unauthorized access or execute malicious code through input validation flaws.
Mitigation strategies for CVE-2017-9171 should focus on immediate remediation through version updates, as the vulnerability has been addressed in subsequent releases of AutoTrace. Organizations should prioritize patching their AutoTrace installations to versions that contain proper bounds checking and input validation mechanisms. Additionally, implementing strict input validation and sanitization procedures for all bitmap files processed by applications using AutoTrace can help reduce the attack surface. Security measures should include deploying intrusion detection systems that monitor for suspicious file processing patterns and implementing application sandboxing techniques to limit the potential impact of exploitation. The fix typically involves adding proper boundary checks in the ReadImage function to ensure that memory access operations remain within the allocated buffer limits, preventing the over-read condition from occurring during bitmap file parsing operations.