CVE-2020-19498 in libheif
Summary
by MITRE • 07/22/2021
Floating point exception in function Fraction in libheif 1.4.0, allows attackers to cause a Denial of Service or possibly other unspecified impacts.
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Analysis
by VulDB Data Team • 07/26/2021
The vulnerability identified as CVE-2020-19498 represents a critical floating point exception within the Fraction function of libheif version 1.4.0, a library widely used for handling heif image format files. This issue arises from improper handling of floating point operations during mathematical computations within the library's core processing functions. The flaw specifically manifests when the library attempts to perform division operations or other arithmetic calculations that result in invalid floating point states, such as division by zero or overflow conditions. The vulnerability impacts applications that rely on libheif for image processing, particularly those handling user-supplied or untrusted heif files.
The technical implementation of this vulnerability stems from the library's failure to properly validate input parameters and mathematical operations within the Fraction function. When processing heif files containing malformed or specially crafted numerical values, the function executes floating point operations that trigger exceptions in the underlying processor or runtime environment. This behavior aligns with CWE-191, which describes integer underflow conditions, though specifically applies to floating point arithmetic in this case. The exception handling mechanism in libheif version 1.4.0 does not adequately protect against these scenarios, causing the application to terminate unexpectedly or enter an unstable state. Attackers can exploit this by crafting malicious heif files with invalid numerical parameters that force the Fraction function into problematic arithmetic states.
The operational impact of this vulnerability extends beyond simple denial of service, as it can potentially enable more sophisticated attacks depending on the environment where the vulnerable library is deployed. When applications using libheif encounter malformed files, they may crash or behave unpredictably, leading to service interruption for users and potential information exposure through crash dumps or error messages. The vulnerability affects web applications, mobile applications, and desktop software that process heif images, making it particularly dangerous in environments where user input is not properly sanitized. In a broader security context, this vulnerability could be leveraged as part of a larger attack chain, potentially enabling privilege escalation or information disclosure if the application does not properly handle exceptions or if the crash leads to memory corruption. The ATT&CK framework categorizes this under privilege escalation and denial of service techniques, as it can be used to disrupt services or potentially gain unauthorized access to system resources.
Mitigation strategies for CVE-2020-19498 require immediate attention from system administrators and software developers. The primary solution involves upgrading to libheif version 1.4.1 or later, where the floating point exception handling has been corrected. Organizations should conduct thorough vulnerability assessments to identify all systems and applications that depend on libheif, particularly those processing user-generated content. Implementing input validation and sanitization measures can provide additional defense in depth, ensuring that heif files are properly validated before processing. Network segmentation and application firewalls can help limit the potential impact of exploitation attempts. Additionally, monitoring systems should be configured to detect unusual application crashes or service disruptions that might indicate exploitation attempts. The vulnerability demonstrates the critical importance of proper exception handling in mathematical operations and highlights the need for comprehensive testing of numerical processing functions in security-sensitive libraries. Organizations should also consider implementing automated patch management processes to ensure timely deployment of security updates and maintain awareness of similar vulnerabilities in other image processing libraries that may be in use.