CVE-2017-6890 in LibRaw-demosaic-pack-GPL2
Summary
by MITRE
A boundary error within the "foveon_load_camf()" function (dcraw_foveon.c) when initializing a huffman table in LibRaw-demosaic-pack-GPL2 before 0.18.2 can be exploited to cause a stack-based buffer overflow.
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Analysis
by VulDB Data Team • 12/06/2022
The vulnerability identified as CVE-2017-6890 represents a critical stack-based buffer overflow condition within the LibRaw-demosaic-pack-GPL2 library version 0.18.1 and earlier. This flaw exists in the foveon_load_camf() function located in the dcraw_foveon.c source file, where improper boundary checking during huffman table initialization creates an exploitable condition that can lead to arbitrary code execution. The issue stems from insufficient validation of input data lengths when processing camera metadata files, specifically those containing foveon sensor information used in certain digital cameras. The vulnerability affects systems that utilize this library for image processing and demosaicing operations, particularly in applications that handle raw camera data without proper input sanitization.
The technical implementation of this vulnerability occurs when the foveon_load_camf() function attempts to initialize a huffman table structure without adequate bounds checking on the incoming data buffer. When processing malformed or specially crafted camera metadata files, the function fails to validate the size of expected data structures, allowing an attacker to provide input that exceeds the allocated buffer space on the stack. This boundary error directly maps to CWE-121 Stack-based Buffer Overflow, which is classified under the Common Weakness Enumeration framework as a fundamental flaw in memory management where data written to a buffer extends beyond its allocated boundaries. The overflow can overwrite adjacent stack memory locations including return addresses and local variables, potentially enabling attackers to redirect program execution flow.
The operational impact of this vulnerability extends beyond simple denial of service scenarios to encompass full system compromise when exploited effectively. Systems utilizing vulnerable versions of LibRaw-demosaic-pack-GPL2 in applications such as photo editing software, digital asset management systems, or camera raw processing pipelines become susceptible to remote code execution attacks. Attackers can craft malicious camera metadata files that, when processed by vulnerable applications, trigger the buffer overflow condition and potentially execute arbitrary code with the privileges of the affected application. This vulnerability is particularly concerning in web-based applications or services that accept user-uploaded image files, as it can be exploited through file upload mechanisms without requiring user interaction beyond the initial file delivery. The exploitability of this condition aligns with ATT&CK technique T1203 Exploitation for Client Execution, where adversaries leverage application vulnerabilities to execute malicious code on target systems.
Mitigation strategies for CVE-2017-6890 primarily focus on immediate version updates to LibRaw-demosaic-pack-GPL2 0.18.2 or later, which incorporates proper boundary checking and input validation within the foveon_load_camf() function. Organizations should conduct comprehensive vulnerability assessments to identify all systems utilizing affected library versions and implement patch management procedures to ensure timely deployment of security updates. Additional defensive measures include input validation at application layers, sandboxing of image processing operations, and implementation of strict file format validation before processing raw camera data. Network-based mitigations such as content filtering and web application firewalls can help prevent exploitation through malicious file uploads, while runtime protections including stack canaries and address space layout randomization may provide additional defense in depth. The vulnerability demonstrates the importance of proper input validation and boundary checking in cryptographic and image processing libraries, as highlighted in industry best practices for secure coding and the OWASP Top Ten security risks that emphasize injection flaws as critical application vulnerabilities requiring systematic remediation approaches.