CVE-2018-20337 in LibRaw
Summary
by MITRE
There is a stack-based buffer overflow in the parse_makernote function of dcraw_common.cpp in LibRaw 0.19.1. Crafted input will lead to a denial of service or possibly unspecified other impact.
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Analysis
by VulDB Data Team • 06/20/2023
The vulnerability identified as CVE-2018-20337 represents a critical stack-based buffer overflow flaw within the LibRaw library version 0.19.1. This issue manifests specifically within the parse_makernote function located in the dcraw_common.cpp source file, making it a significant concern for any system or application that relies on this library for raw image processing. The vulnerability arises from insufficient input validation and bounds checking during the parsing of maker note metadata within digital camera raw image files, creating an exploitable condition that can be triggered by malformed input data.
The technical implementation of this vulnerability stems from improper handling of buffer boundaries when processing maker note data structures in raw image files. When the parse_makernote function encounters crafted input that exceeds expected buffer dimensions, it fails to properly validate the input length before copying data into stack-allocated buffers. This classic buffer overflow condition allows an attacker to overwrite adjacent stack memory locations, potentially leading to arbitrary code execution or system instability. The flaw operates under CWE-121, which classifies stack-based buffer overflow conditions, and represents a direct violation of secure coding practices that mandate proper input validation and boundary checking.
The operational impact of this vulnerability extends beyond simple denial of service scenarios, as the nature of stack corruption can potentially lead to more severe consequences including arbitrary code execution. Systems utilizing LibRaw for image processing, particularly those handling untrusted input from web applications, email attachments, or file upload functionalities, face significant risk exposure. The vulnerability affects any application that processes raw camera images without proper input sanitization, including photo editing software, digital asset management systems, and web-based image processing services. Attackers can craft specially formatted raw image files that trigger the buffer overflow when processed by vulnerable applications, potentially enabling remote code execution or system compromise depending on the execution environment.
Mitigation strategies for CVE-2018-20337 should prioritize immediate patching of LibRaw to version 0.19.2 or later, which contains the necessary fixes for the buffer overflow condition. Organizations should implement input validation measures that sanitize all raw image file inputs before processing, including length verification and format checking before invoking LibRaw functions. Additional defensive measures include deploying application sandboxing techniques, implementing strict file type validation, and using memory protection mechanisms such as stack canaries or address space layout randomization. From an ATT&CK framework perspective, this vulnerability maps to T1059.007 for execution through compromised applications and T1203 for exploitation of software vulnerabilities, emphasizing the need for comprehensive defensive strategies including network segmentation and regular security assessments to identify systems running vulnerable versions of the library.