CVE-2019-16865 in Pillow
Summary
by MITRE
An issue was discovered in Pillow before 6.2.0. When reading specially crafted invalid image files, the library can either allocate very large amounts of memory or take an extremely long period of time to process the image.
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Analysis
by VulDB Data Team • 05/18/2025
The vulnerability identified as CVE-2019-16865 represents a critical resource exhaustion flaw within the Pillow library, a widely used Python imaging library that serves as the de facto standard for image processing in numerous applications and web services. This vulnerability stems from inadequate input validation and memory management when processing malformed image files, creating a potential attack vector that can be exploited to disrupt service availability or cause system instability. The issue affects versions prior to 6.2.0, making it a significant concern for systems that have not yet been updated to address this weakness.
The technical flaw manifests when the Pillow library encounters specially crafted invalid image files that trigger abnormal memory allocation patterns or extended processing times during image parsing operations. This behavior can be attributed to insufficient bounds checking and memory allocation controls within the library's image decoding routines, particularly when handling malformed data structures that do not conform to standard image format specifications. The vulnerability allows attackers to manipulate the library's memory consumption to extremely high levels or force it to engage in computationally intensive operations that can cause denial of service conditions. This type of vulnerability aligns with CWE-400, which categorizes resource exhaustion issues, and specifically relates to improper handling of input data that leads to uncontrolled resource consumption.
The operational impact of this vulnerability extends beyond simple denial of service scenarios, as it can affect a broad spectrum of applications that rely on Pillow for image processing tasks. Web applications, content management systems, and image hosting services that utilize Pillow for image validation, resizing, or conversion operations become vulnerable to attacks that can consume excessive system resources or cause application crashes. Attackers can exploit this vulnerability by uploading malicious image files that trigger the resource exhaustion behavior, potentially leading to system instability, service unavailability, or even system compromise if the affected applications do not implement proper input sanitization measures. The vulnerability can be particularly dangerous in environments where multiple image processing operations occur simultaneously, as the cumulative effect of resource exhaustion can severely impact overall system performance and availability.
Mitigation strategies for CVE-2019-16865 primarily focus on immediate remediation through library updates to version 6.2.0 or later, which includes patches addressing the memory allocation and processing time issues. Organizations should implement comprehensive patch management procedures to ensure all affected systems are updated promptly. Additionally, implementing input validation measures such as image file size limits, format verification, and timeout mechanisms can provide additional defense-in-depth layers. The ATT&CK framework categorizes this type of vulnerability under T1499.004, which covers resource exhaustion attacks, making it important for security teams to monitor for unusual memory consumption patterns or processing delays that could indicate exploitation attempts. Regular security assessments and vulnerability scanning should be conducted to identify systems that may still be running vulnerable versions of the Pillow library, while application-level defenses including sandboxing image processing operations and implementing proper error handling can further reduce the risk of exploitation.