CVE-2018-3973 in Canvas Draw
Summary
by MITRE
An exploitable out of bounds write exists in the CAL parsing functionality of Canvas Draw version 5.0.0. A specially crafted CAL image processed via the application can lead to an out of bounds write overwriting arbitrary data. An attacker can deliver a PCX image to trigger this vulnerability and gain code execution.
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Analysis
by VulDB Data Team • 07/06/2023
The vulnerability identified as CVE-2018-3973 represents a critical out of bounds write flaw within the CAL parsing component of Canvas Draw version 5.0.0. This type of vulnerability falls under the common weakness enumeration CWE-787 which specifically addresses out of bounds writes in memory operations. The flaw manifests when the application processes specially crafted CAL image files that contain malformed data structures, particularly within the PCX image format that serves as the attack vector. The vulnerability stems from inadequate bounds checking during the parsing of image metadata and pixel data structures, allowing an attacker to manipulate memory layout through crafted input files.
The technical exploitation of this vulnerability occurs through the manipulation of CAL image parsing routines that handle PCX file format processing. When Canvas Draw encounters a maliciously crafted PCX image, the parser fails to properly validate array indices and buffer boundaries during data extraction from the image headers and pixel data sections. This insufficient validation enables an attacker to write data beyond the allocated memory boundaries, potentially overwriting adjacent memory regions containing critical application data, function pointers, or control structures. The out of bounds write can be leveraged to corrupt program execution flow, leading to arbitrary code execution capabilities. The ATT&CK framework categorizes this as a memory corruption vulnerability under the technique of code injection, specifically targeting the application's parsing functionality.
The operational impact of CVE-2018-3973 extends beyond simple privilege escalation as it provides a complete code execution pathway that can be exploited remotely or through social engineering techniques. An attacker who successfully triggers this vulnerability gains the ability to execute arbitrary code within the context of the Canvas Draw application, potentially leading to full system compromise. The vulnerability affects users who process untrusted image files, making it particularly dangerous in environments where users may encounter malicious attachments or download images from unverified sources. The flaw exists in the application's image processing pipeline, meaning any user who opens or previews a maliciously crafted PCX image file could be compromised. The memory corruption affects the application's stability and can lead to denial of service conditions while simultaneously providing a persistent code execution vector.
Mitigation strategies for CVE-2018-3973 should focus on immediate patch deployment from the vendor, as the vulnerability requires no user interaction beyond opening a malicious image file. Organizations should implement strict file validation policies that filter or quarantine suspicious image file formats, particularly those with embedded CAL or PCX structures. Network-based intrusion detection systems should be configured to monitor for patterns associated with malicious image file delivery, while endpoint protection solutions should be updated to include signature-based detection for known malicious file samples. Additionally, user education programs should emphasize the importance of avoiding untrusted image file attachments and implementing least privilege access controls for applications that process image files. The vulnerability's classification as a memory corruption flaw aligns with ATT&CK technique T1059 which covers command and scripting interpreter usage, making it essential to monitor for suspicious process execution patterns that may indicate exploitation attempts.