CVE-2018-5819 in LibRaw
Summary
by MITRE
An error within the "parse_sinar_ia()" function (internal/dcraw_common.cpp) within LibRaw versions prior to 0.19.1 can be exploited to exhaust available CPU resources.
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Analysis
by VulDB Data Team • 07/11/2023
The vulnerability identified as CVE-2018-5819 resides within the LibRaw library, a widely used open-source software for processing raw image files from digital cameras and other imaging devices. This issue affects versions prior to 019.1 and specifically targets the parse_sinar_ia() function located in the internal/dcraw_common.cpp source file. The flaw represents a classic denial of service vulnerability that can be exploited by malicious actors to consume excessive CPU resources, potentially leading to system instability or complete service unavailability. The vulnerability is particularly concerning given LibRaw's extensive usage in image processing applications, photo editing software, and digital asset management systems across various platforms and operating systems.
The technical implementation of this vulnerability stems from inadequate input validation and processing within the parse_sinar_ia() function. When the library processes malformed or specially crafted Sinar image files, the function enters into an infinite loop or extremely resource-intensive processing pattern that consumes CPU cycles without proper bounds or termination conditions. This behavior can be triggered through a simple file upload or processing operation that invokes the affected library function. The flaw operates at the parsing layer where the software attempts to interpret proprietary Sinar camera file formats, and the lack of proper loop bounds checking or resource consumption limits allows an attacker to craft malicious input that causes the processing to continue indefinitely or consume disproportionate computational resources.
The operational impact of CVE-2018-5819 extends beyond simple resource exhaustion, potentially affecting critical image processing workflows and system availability. Applications that rely on LibRaw for image handling, including photo editing suites, digital asset management platforms, and web-based image processing services, could become unresponsive or crash when processing maliciously crafted files. This vulnerability directly maps to CWE-400, which categorizes "Uncontrolled Resource Consumption" as a fundamental weakness in software design. The attack vector is particularly dangerous because it requires minimal privileges and can be executed through normal file processing operations, making it difficult to detect and prevent. Systems running vulnerable versions of LibRaw may experience cascading failures if multiple concurrent processing operations are exploited simultaneously, leading to complete service disruption.
Mitigation strategies for this vulnerability center on immediate version updates to LibRaw 0.19.1 or later, which contain the necessary code fixes to prevent the excessive CPU consumption. Organizations should prioritize patching all systems and applications that utilize LibRaw, particularly those handling untrusted image inputs from external sources. Network administrators should implement file type validation and scanning mechanisms to detect potentially malicious image files before they reach the processing layer. The vulnerability also highlights the importance of input sanitization and resource monitoring within image processing pipelines. Security teams should establish baseline CPU usage monitoring for image processing tasks and implement automated alerts for unusual resource consumption patterns. From an ATT&CK framework perspective, this vulnerability aligns with techniques related to resource exhaustion and denial of service, specifically mapping to tactics involving privilege escalation and service availability disruption. Organizations should also consider implementing application whitelisting and sandboxing mechanisms to limit the impact of potential exploitation attempts.