CVE-2018-3859 in Canvas Draw
Summary
by MITRE
An exploitable out-of-bounds write exists in the TIFF parsing functionality of Canvas Draw version 4.0.0. A specially crafted TIFF image processed via the application can lead to an out-of-bounds write, overwriting arbitrary data. An attacker can deliver a TIFF image to trigger this vulnerability and gain code execution. A different vulnerability than CVE-2018-3860.
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Analysis
by VulDB Data Team • 04/18/2023
The vulnerability identified as CVE-2018-3859 represents a critical out-of-bounds write flaw within the TIFF parsing implementation of Canvas Draw version 4.0.0. This security defect manifests when the application processes specially crafted TIFF image files, creating a scenario where memory corruption occurs beyond the allocated buffer boundaries. The flaw exists in the raster image processing pipeline where the application fails to properly validate the dimensions and data structures within TIFF files before attempting to write pixel data into memory regions. Such inadequate input validation creates a pathway for attackers to manipulate the parsing process and execute arbitrary code on the target system.
This vulnerability falls under the CWE-787 category of out-of-bounds write conditions, which is classified as a severe memory safety issue within the Common Weakness Enumeration framework. The technical implementation flaw stems from insufficient bounds checking during the TIFF file interpretation phase, specifically when handling image metadata and pixel data arrays. The application's TIFF parser does not properly verify array indices against allocated memory boundaries, allowing attackers to craft malicious TIFF files that cause the program to write data beyond the intended memory locations. This memory corruption can overwrite critical program variables, function pointers, or return addresses, potentially enabling remote code execution.
The operational impact of CVE-2018-3859 extends beyond simple data corruption, as it provides attackers with a potential path to full system compromise. When a victim opens a maliciously crafted TIFF image within Canvas Draw, the application's TIFF parsing routine triggers the out-of-bounds write condition, which can be leveraged to execute arbitrary code with the privileges of the affected application. This vulnerability operates at the application layer and requires no special privileges to exploit, making it particularly dangerous in environments where users frequently open image files from untrusted sources. The attack vector is primarily through social engineering techniques, where users are tricked into opening malicious TIFF files, though automated exploitation methods may also be possible depending on the specific memory layout and protection mechanisms in place.
Security mitigations for CVE-2018-3859 should focus on implementing robust input validation and bounds checking within the TIFF parsing functionality. The most effective immediate solution involves updating to a patched version of Canvas Draw that addresses the memory corruption issue through proper buffer size validation and array index checking. Additionally, organizations should implement application whitelisting policies that restrict the execution of image processing applications on untrusted files, combined with regular security updates and vulnerability assessments. Network-level protections such as sandboxing image processing applications and implementing strict file type validation can further reduce the attack surface. From an ATT&CK framework perspective, this vulnerability maps to techniques involving malicious file execution and privilege escalation, emphasizing the need for layered defensive measures including user education, application hardening, and continuous monitoring for suspicious file handling activities.