CVE-2020-21573 in image-processing
Summary
by MITRE • 11/02/2021
An issue was discoverered in in abhijitnathwani image-processing v0.1.0, allows local attackers to cause a denial of service via a crafted image file.
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Analysis
by VulDB Data Team • 11/06/2021
The vulnerability identified as CVE-2020-21573 represents a critical denial of service weakness within the abhijitnathwani image-processing library version 0.1.0. This flaw specifically targets local attackers who can exploit malformed image files to disrupt the normal operation of systems utilizing this image processing component. The vulnerability stems from inadequate input validation mechanisms within the library's image parsing routines, which fail to properly handle malformed or specially crafted image data structures.
The technical implementation of this vulnerability manifests through improper exception handling and memory management within the image processing pipeline. When the library encounters a crafted image file, it fails to gracefully handle the malformed data, leading to application crashes or resource exhaustion that effectively renders the system unavailable to legitimate users. This type of vulnerability falls under CWE-400, which specifically addresses unspecified denial of service conditions in software implementations. The flaw operates at the application level where the library processes image files without adequate defensive programming practices to prevent malformed inputs from causing system instability.
From an operational perspective, this vulnerability presents significant risk to systems that rely on the affected image-processing library for automated image handling tasks. Local attackers can exploit this weakness to repeatedly crash services or applications that depend on the library, potentially leading to extended downtime and service disruption. The impact extends beyond simple system unavailability as the denial of service can affect business continuity and user experience, particularly in environments where image processing is a core component of application functionality. The vulnerability's local attack vector reduces the complexity of exploitation, making it particularly concerning for environments where local access is prevalent.
The attack surface for this vulnerability encompasses any system or application that utilizes the abhijitnathwani image-processing library version 0.1.0 and processes user-supplied or untrusted image files. This includes web applications, content management systems, image processing pipelines, and automated workflows that handle image data. Security practitioners should consider this vulnerability in the context of the MITRE ATT&CK framework, particularly under the T1499 category for network denial of service, as the exploitation results in service unavailability that aligns with network-based disruption techniques. Organizations should implement immediate mitigation strategies including library version updates, input sanitization measures, and enhanced monitoring for abnormal application behavior that may indicate exploitation attempts.
Mitigation efforts should prioritize updating to patched versions of the abhijitnathwani image-processing library where available, as this represents the most direct solution to address the underlying flaw. Additionally, implementing robust input validation and sanitization measures can provide defense-in-depth protection against similar vulnerabilities in other libraries or components. System administrators should establish monitoring protocols to detect unusual application crashes or resource consumption patterns that may indicate exploitation attempts. The vulnerability also highlights the importance of comprehensive security testing including fuzzing and input validation testing during software development lifecycle phases to identify and remediate similar weaknesses before deployment in production environments.