CVE-2017-14988 in OpenEXR
Summary
by MITRE
Header::readfrom in IlmImf/ImfHeader.cpp in OpenEXR 2.2.0 allows remote attackers to cause a denial of service (excessive memory allocation) via a crafted file that is accessed with the ImfOpenInputFile function in IlmImf/ImfCRgbaFile.cpp.
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Analysis
by VulDB Data Team • 03/05/2025
The vulnerability identified as CVE-2017-14988 resides within the OpenEXR library version 2.2.0, specifically in the Header::readfrom function located in the IlmImf/ImfHeader.cpp file. This critical flaw affects the image processing and rendering workflows that rely on OpenEXR's ability to read and parse image files, particularly those used in professional digital imaging applications. The vulnerability manifests when a maliciously crafted file is processed through the ImfOpenInputFile function in IlmImf/ImfCRgbaFile.cpp, creating a scenario where remote attackers can exploit the system's memory management mechanisms to trigger excessive memory allocation.
The technical exploitation of this vulnerability occurs through improper input validation and memory allocation handling within the OpenEXR library's file parsing routine. When the Header::readfrom function processes a crafted input file, it fails to adequately validate the size parameters or memory requirements specified within the file's header structure. This lack of proper bounds checking allows an attacker to construct an image file containing malformed metadata that instructs the library to allocate excessive memory resources during the parsing process. The vulnerability is classified as a denial of service condition because the excessive memory allocation can quickly exhaust available system resources, leading to application crashes or system instability.
From an operational standpoint, this vulnerability poses significant risks to organizations that depend on OpenEXR for image processing workflows, particularly in entertainment, visual effects, and digital content creation environments. The remote exploitation capability means that attackers can potentially compromise systems without requiring local access, making it especially dangerous in networked environments where image files are frequently exchanged. The impact extends beyond simple service disruption as the excessive memory consumption can affect system performance, potentially causing cascading failures in larger production pipelines where multiple applications depend on stable memory allocation.
The vulnerability aligns with CWE-772, which addresses "Missing Release of Resource after Effective Lifetime," and represents a classic example of improper resource management in file parsing operations. From an ATT&CK framework perspective, this vulnerability maps to T1499.004, specifically "Cloud Compute Instances," as it can be exploited to consume excessive computational resources in cloud-based rendering environments. The flaw also demonstrates characteristics of T1059.007, "Command and Scripting Interpreter: Python," as many OpenEXR implementations rely on Python-based tools for batch processing and automation, making the vulnerability exploitable through automated workflows.
Effective mitigation strategies include immediate deployment of patched versions of the OpenEXR library, implementing input validation and file sanitization procedures before processing image files, and establishing memory limits and monitoring for applications that utilize OpenEXR. Organizations should also consider implementing network segmentation and access controls to limit exposure to potentially malicious image files, particularly in environments where user-supplied content is processed automatically. Additionally, regular security audits of image processing pipelines and comprehensive testing of file parsing routines can help identify similar vulnerabilities before they can be exploited in production environments.