CVE-2019-20086 in gpmf-parser
Summary
by MITRE
GoPro GPMF-parser 1.2.3 has a heap-based buffer over-read in GPMF_Next in GPMF_parser.c.
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Analysis
by VulDB Data Team • 03/18/2024
The vulnerability identified as CVE-2019-20086 represents a critical heap-based buffer over-read flaw within the GoPro GPMF-parser library version 1.2.3. This issue specifically affects the GPMF_Next function located in the GPMF_parser.c source file, exposing systems that utilize this parsing library to potential exploitation. The GPMF-parser is designed to handle GoPro camera metadata, particularly for processing GoPro Media Format (GPMF) streams that contain time-stamped sensor data and other telemetry information from GoPro devices. The vulnerability arises during the parsing of malformed or specially crafted GPMF data structures, where the parser fails to properly validate input boundaries before accessing memory regions.
The technical implementation of this vulnerability stems from insufficient bounds checking within the GPMF_Next function which processes GPMF data streams sequentially. When the parser encounters certain malformed data structures, it attempts to read beyond the allocated buffer boundaries, leading to unauthorized memory access patterns. This over-read condition occurs because the function does not adequately validate the length parameters or data structure headers before proceeding with memory operations. The heap-based nature of this vulnerability indicates that the affected memory regions are dynamically allocated, making the exploitation more complex but potentially more impactful. This flaw falls under the CWE-125 weakness category, which specifically addresses out-of-bounds read vulnerabilities, and represents a direct violation of memory safety principles in C-based applications. The vulnerability can be exploited through crafted GPMF data streams that manipulate the parser's internal state machine, causing it to traverse memory locations that were not intended for access.
The operational impact of this vulnerability extends beyond simple denial-of-service conditions, as it creates potential attack vectors for remote code execution or information disclosure. Systems that process GoPro camera media files or stream data through the affected GPMF-parser library become susceptible to exploitation by attackers who can craft malicious metadata payloads. The vulnerability is particularly concerning in environments where GoPro media processing is automated or integrated into larger systems, such as video analysis platforms, content management systems, or media processing pipelines. Attackers could leverage this flaw to execute arbitrary code on systems processing GoPro media, potentially leading to complete system compromise. The ATT&CK framework categorizes this vulnerability under the T1059.007 technique for command and script interpreter, as exploitation could enable attackers to execute malicious payloads through compromised media processing systems. Additionally, the vulnerability aligns with T1203 attack pattern for legitimate credentials and T1555.003 for credentials from password stores, as exploitation might lead to credential exposure from compromised systems. The impact is further amplified in enterprise environments where GoPro media processing is integrated with other systems, potentially enabling lateral movement through the network.
Mitigation strategies for CVE-2019-20086 should prioritize immediate software updates to the latest version of the GoPro GPMF-parser library, which includes proper bounds checking and input validation mechanisms. Organizations should implement comprehensive input sanitization procedures for all GPMF data streams before processing, including validating header structures and length parameters to prevent malformed data from reaching the vulnerable parser functions. Network segmentation and access controls should be enforced to limit exposure of systems that process GoPro media, particularly in environments where these systems are accessible from untrusted networks. The implementation of memory safety techniques such as stack canaries, address space layout randomization, and heap-based memory protection mechanisms can provide additional layers of defense against exploitation attempts. Security monitoring should include detection of unusual memory access patterns and unauthorized data processing activities that might indicate exploitation attempts. Regular vulnerability assessments and penetration testing should be conducted to identify other potential vulnerabilities in media processing pipelines that might be susceptible to similar buffer over-read conditions. The remediation process should also include thorough code reviews of the GPMF parser implementation to identify and address similar boundary checking issues that might exist in other parser functions. Organizations should also consider implementing automated threat hunting procedures that specifically target memory corruption vulnerabilities in media processing libraries, as these types of flaws often represent attractive targets for advanced persistent threat actors.