CVE-2020-35530 in LibRaw
Summary
by MITRE • 09/01/2022
In LibRaw, there is an out-of-bounds write vulnerability within the "new_node()" function (libraw\src\x3f\x3f_utils_patched.cpp) that can be triggered via a crafted X3F file.
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Analysis
by VulDB Data Team • 04/30/2025
The vulnerability identified as CVE-2020-35530 represents a critical out-of-bounds write flaw in LibRaw, a widely-used library for processing raw image files from digital cameras. This vulnerability specifically resides within the "new_node()" function located in the libraw\src??_utils_patched.cpp source file, making it a fundamental issue within the library's memory management and data parsing capabilities. The flaw manifests when processing specially crafted X3F files, which are the native raw image format used by Fujifilm cameras, indicating that the vulnerability affects a significant portion of digital photography workflows that rely on raw file processing.
The technical nature of this vulnerability stems from improper bounds checking during the allocation and manipulation of memory structures within the LibRaw library's internal data handling mechanisms. When a maliciously constructed X3F file is processed, the "new_node()" function fails to validate array indices or buffer boundaries before writing data, allowing an attacker to overwrite adjacent memory locations. This type of vulnerability falls under CWE-787, which specifically addresses out-of-bounds write conditions, and represents a classic example of memory safety issues that can lead to arbitrary code execution or system instability. The vulnerability's exploitation potential is heightened by the fact that X3F files are legitimate image formats that users might encounter in normal workflow scenarios, making this an attractive target for attackers seeking to compromise systems through image processing applications.
The operational impact of CVE-2020-35530 extends beyond simple denial of service, as it creates potential pathways for remote code execution and system compromise. Applications that utilize LibRaw for image processing, including photo editing software, digital asset management systems, and content management platforms, become vulnerable to attacks when processing untrusted X3F files. This vulnerability affects the broader digital imaging ecosystem since LibRaw is integrated into numerous software packages and frameworks, meaning that a single exploit could potentially impact multiple applications across different platforms and operating systems. The attack surface is particularly concerning given that X3F files are commonly shared through various digital channels, making them a plausible vector for supply chain attacks or social engineering campaigns targeting photographers and imaging professionals.
Mitigation strategies for CVE-2020-35530 should focus on immediate patch application and defensive programming practices. The primary solution involves updating to the latest version of LibRaw where the out-of-bounds write issue has been resolved through proper bounds checking and memory validation mechanisms. Organizations should implement comprehensive vulnerability management processes that include regular updates to image processing libraries and dependencies, particularly those handling untrusted input data. Additionally, defensive programming techniques such as implementing input sanitization, using memory-safe programming languages where possible, and deploying runtime protections like address space layout randomization and stack canaries can help reduce the exploitation risk. From an ATT&CK framework perspective, this vulnerability aligns with techniques involving process injection and privilege escalation, making it a critical target for defensive measures that include network segmentation, application whitelisting, and monitoring for unusual image processing activities that might indicate exploitation attempts.