CVE-2018-5804 in LibRaw
Summary
by MITRE
A type confusion error within the "identify()" function (internal/dcraw_common.cpp) in LibRaw versions prior to 0.18.8 can be exploited to trigger a division by zero.
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Analysis
by VulDB Data Team • 06/13/2023
The vulnerability identified as CVE-2018-5804 represents a critical type confusion flaw within the LibRaw library's internal dcraw_common.cpp file that affects versions prior to 0.18.8. This issue manifests specifically within the "identify()" function where improper type handling creates conditions that can lead to a division by zero error during image processing operations. The vulnerability stems from insufficient input validation and type checking mechanisms that fail to properly distinguish between different data types when processing raw image files from various camera manufacturers.
The technical exploitation of this vulnerability occurs when malformed or specially crafted image files are processed by applications leveraging the affected LibRaw library. The type confusion aspect arises from the library's inability to properly validate the expected data types during the identification phase of raw image processing, allowing an attacker to manipulate the data flow in a way that causes the division by zero condition. This particular error condition is classified under CWE-471, which specifically addresses the issue of "Incorrectly Handling of Data Type" where a program does not properly handle data type conversions or validations, leading to unpredictable behavior.
From an operational perspective, this vulnerability poses significant risks to applications that depend on LibRaw for image processing, including digital photography software, image viewers, and professional photo editing tools. The division by zero condition can result in application crashes, denial of service conditions, and potentially provide attackers with opportunities for further exploitation through controlled application termination. The impact extends beyond simple service disruption as the vulnerability can be leveraged in automated attack scenarios where malicious image files are used to target vulnerable applications in batch processing environments.
The exploitation of CVE-2018-5804 aligns with ATT&CK technique T1203, which involves the use of malicious files to cause system instability or denial of service. This vulnerability specifically targets the input validation and error handling mechanisms within image processing pipelines, making it particularly dangerous in environments where large volumes of user-uploaded images are processed. The vulnerability demonstrates the importance of proper input sanitization and type checking in multimedia processing libraries, as these components often handle untrusted data from diverse sources.
Organizations should prioritize updating their LibRaw dependencies to version 0.18.8 or later, which contains the necessary patches to address the type confusion error. Additionally, implementing input validation measures at the application level can provide defense-in-depth protection against potential exploitation attempts. Security monitoring should focus on detecting unusual application termination patterns or error conditions that might indicate exploitation attempts. The vulnerability serves as a reminder of the critical importance of maintaining up-to-date third-party libraries and implementing robust error handling mechanisms in multimedia processing applications that handle untrusted input data.