CVE-2024-48855 in QNX Software Development Platform
Summary
by MITRE • 01/14/2025
Out-of-bounds read in the TIFF image codec in QNX SDP versions 8.0, 7.1 and 7.0 could allow an unauthenticated attacker to cause an information disclosure in the context of the process using the image codec.
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Analysis
by VulDB Data Team • 01/14/2025
The vulnerability identified as CVE-2024-48855 represents a critical out-of-bounds read flaw within the TIFF image codec implementation in QNX Software Development Platform versions 8.0, 7.1, and 7.0. This issue resides in the fundamental image processing capabilities of the operating system, potentially affecting any application or service that utilizes TIFF file handling within these QNX environments. The vulnerability is classified as an information disclosure risk, where an attacker can extract sensitive data from memory locations beyond the intended buffer boundaries, potentially exposing confidential information that could be leveraged for further exploitation.
The technical implementation of this flaw occurs within the TIFF image codec parser, which processes image files to extract and interpret metadata and pixel data. When processing malformed or specially crafted TIFF files, the codec fails to properly validate array indices or buffer boundaries, leading to memory access violations that result in out-of-bounds reads. This behavior aligns with CWE-129, which specifically addresses insufficient validation of length of input buffers, and CWE-125, which covers out-of-bounds read conditions in software implementations. The vulnerability is particularly concerning because it operates without requiring authentication, making it accessible to any unauthenticated attacker who can influence the processing of TIFF files through the affected QNX system.
The operational impact of CVE-2024-48855 extends beyond simple information disclosure, as it could enable attackers to extract sensitive data such as cryptographic keys, system credentials, or proprietary information stored in adjacent memory regions. This vulnerability is particularly dangerous in embedded systems or automotive environments where QNX SDP is commonly deployed, as these systems often handle critical functions and may contain sensitive operational data. The vulnerability could be exploited through various attack vectors including email attachments, web downloads, or file transfers, making it a significant risk for organizations relying on QNX-based systems for their operations. According to ATT&CK framework, this vulnerability could be categorized under T1566 for initial access through malicious file delivery and T1005 for data from local system storage.
Organizations using QNX SDP versions 8.0, 7.1, and 7.0 should immediately implement mitigations to address this vulnerability, including applying the latest security patches provided by QNX, implementing strict file validation for TIFF inputs, and deploying network segmentation to limit potential attack surfaces. Additionally, system administrators should consider implementing memory protection mechanisms such as address space layout randomization and stack canaries to reduce the effectiveness of potential exploitation attempts. Regular security assessments should be conducted to identify any other similar vulnerabilities within the image processing pipelines and ensure that all system components are regularly updated to maintain security posture against evolving threats. The vulnerability demonstrates the critical importance of proper input validation in image processing libraries and highlights the need for comprehensive security testing of all system components that handle external data inputs.