CVE-2024-24254 in Autopilot
Summary
by MITRE • 02/07/2024
PX4 Autopilot 1.14 and earlier, due to the lack of synchronization mechanism for loading geofence data, has a Race Condition vulnerability in the geofence.cpp and mission_feasibility_checker.cpp. This will result in the drone uploading overlapping geofences and mission routes.
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Analysis
by VulDB Data Team • 06/06/2025
The CVE-2024-24254 vulnerability affects PX4 Autopilot versions 1.14 and earlier, presenting a critical race condition flaw in the geofence management system. This vulnerability stems from insufficient synchronization mechanisms when loading geofence data, creating a scenario where multiple processes or threads can simultaneously access and modify geofence configuration files without proper coordination. The underlying technical flaw exists within the geofence.cpp and mission_feasibility_checker.cpp components, which are responsible for validating and processing geofence boundaries and mission route planning. When concurrent access occurs during geofence loading operations, the system fails to maintain data consistency, leading to unpredictable behavior in geofence processing.
The operational impact of this race condition is particularly severe for autonomous drone operations and unmanned aerial vehicle systems. The vulnerability allows for the unintentional uploading of overlapping geofences and mission routes, which can result in catastrophic consequences for flight operations. When geofence data becomes corrupted or inconsistently loaded, drones may inadvertently fly into restricted airspace, violate regulatory boundaries, or execute mission plans that conflict with safety parameters. This creates significant safety risks for both the unmanned aircraft and people or property in the surrounding area. The vulnerability essentially undermines the fundamental safety mechanisms designed to prevent unauthorized or dangerous flight operations, potentially leading to collisions, regulatory violations, or loss of aircraft.
The root cause of this vulnerability aligns with CWE-362, which describes a race condition flaw where multiple threads or processes access shared resources without proper synchronization. This weakness creates a window of opportunity where data integrity is compromised during concurrent operations. From an operational security perspective, this vulnerability falls under ATT&CK technique T1499.001, which involves the manipulation of physical systems through software modifications that can affect system behavior and safety parameters. The lack of proper mutex or semaphore controls in the geofence loading process creates an environment where concurrent access can result in data corruption, leading to mission planning failures and potential safety hazards. Organizations deploying PX4 Autopilot systems must recognize that this vulnerability can be exploited to compromise flight safety protocols and regulatory compliance measures.
Mitigation strategies for CVE-2024-24254 should prioritize immediate software updates to versions beyond 1.14 where synchronization mechanisms have been implemented. System administrators should implement monitoring protocols to detect anomalous geofence loading patterns or overlapping boundary configurations that could indicate the vulnerability's exploitation. Additionally, operational procedures should include redundant validation checks for geofence data integrity before mission deployment, ensuring that any corrupted or inconsistent geofence information is identified and corrected. The implementation of proper locking mechanisms and atomic operations during geofence data loading will address the root cause of this race condition, preventing concurrent access issues that lead to overlapping geofences and mission route conflicts. Organizations should also consider implementing automated testing procedures that verify geofence data consistency and integrity to prevent exploitation of this vulnerability in operational environments.