CVE-2017-9194 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-tga.c:559:29.
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Analysis
by VulDB Data Team • 10/02/2020
The vulnerability identified as CVE-2017-9194 resides within the AutoTrace library autotrace.a version 0.31.1, specifically within the input-tga.c file at line 559 in the ReadImage function. This represents a heap-based buffer over-read condition that occurs when processing Targa image files, a common raster graphics format. The flaw manifests during the parsing of TGA file headers and pixel data, where insufficient bounds checking allows an attacker to manipulate the program's memory access patterns. Such vulnerabilities typically arise when developers fail to validate input data dimensions against allocated buffer sizes, creating opportunities for memory corruption that can be exploited by malicious actors.
The technical implementation of this vulnerability involves a classic buffer over-read scenario where the ReadImage function processes TGA file data without adequate validation of the expected data size against the allocated memory buffer. When the application encounters a malformed or specially crafted TGA file, the parsing logic attempts to read beyond the allocated heap memory boundaries, potentially exposing sensitive data or causing application instability. This type of vulnerability falls under the CWE-125 weakness category, which specifically addresses out-of-bounds read conditions in software applications. The heap-based nature of the vulnerability means that the memory corruption occurs in dynamically allocated memory regions rather than stack-based buffers, making the exploitation more complex but potentially more dangerous in terms of information disclosure.
The operational impact of CVE-2017-9194 extends beyond simple application crashes, as it creates potential entry points for more sophisticated attacks within the ATT&CK framework's initial access and execution phases. An attacker could leverage this vulnerability by providing a malicious TGA file to an application that utilizes AutoTrace for image processing, potentially leading to information disclosure through memory content exposure or application denial of service. The vulnerability is particularly concerning in environments where AutoTrace is integrated into larger applications or content processing pipelines, as it could be exploited through various attack vectors including email attachments, web uploads, or file sharing systems. The memory corruption could also potentially be chained with other vulnerabilities to achieve privilege escalation or remote code execution depending on the application context and system configuration.
Mitigation strategies for this vulnerability should focus on immediate patching of the AutoTrace library to version 0.31.2 or later, which contains the necessary fixes for the buffer over-read condition. Organizations should also implement input validation measures that restrict TGA file processing to known good formats and sizes, particularly in applications that handle untrusted user input. The implementation of address space layout randomization ASLR and stack canaries can provide additional defense-in-depth measures against exploitation attempts. Additionally, network segmentation and access controls should be enforced to limit exposure of systems that utilize AutoTrace to processing TGA files, while regular security assessments should verify that no other similar buffer over-read vulnerabilities exist in related image processing libraries. System monitoring should be enhanced to detect anomalous memory access patterns that could indicate exploitation attempts, and incident response procedures should be updated to address potential exploitation of this class of vulnerability.