CVE-2018-4023 in A1 Dashcam
Summary
by MITRE
An exploitable code execution vulnerability exists in the XML_UploadFile Wi-Fi command of the NT9665X Chipset firmware, running on the Anker Roav A1 Dashcam, version RoavA1SWV1.9. A specially crafted packet can cause a stack-based buffer overflow, resulting in code execution.
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Analysis
by VulDB Data Team • 09/17/2023
The vulnerability identified as CVE-2018-4023 represents a critical code execution flaw within the NT9665X Chipset firmware of the Anker Roav A1 Dashcam device. This issue manifests in the XML_UploadFile Wi-Fi command implementation, where the firmware fails to properly validate input data before processing. The vulnerability stems from inadequate bounds checking mechanisms that allow maliciously crafted packets to exceed allocated buffer space during command execution. The affected firmware version RoavA1SWV1.9 demonstrates a fundamental flaw in memory management practices, creating an opportunity for attackers to exploit the device's wireless communication capabilities for unauthorized system compromise. This vulnerability directly impacts the device's security posture by enabling remote code execution without requiring physical access or authentication credentials.
The technical implementation of this vulnerability follows a classic stack-based buffer overflow pattern where input data exceeds the allocated memory buffer size, causing adjacent memory locations to be overwritten. The XML_UploadFile command processes wireless packets containing XML formatted data, but fails to implement proper input length validation or sanitization routines. When an attacker crafts a malicious packet with oversized XML content, the firmware's parsing routine writes data beyond the intended buffer boundaries, potentially overwriting critical program execution elements such as return addresses or function pointers. This overflow condition creates a predictable attack surface that can be leveraged to redirect program execution flow to attacker-controlled code. The vulnerability's classification aligns with CWE-121 Stack-based Buffer Overflow, which specifically addresses buffer overflows occurring in stack memory regions. The attack vector operates entirely over the wireless network interface, making it particularly concerning for IoT devices that lack robust network segmentation controls.
The operational impact of CVE-2018-4023 extends beyond simple device compromise, as it enables attackers to gain full control over the dashcam's functionality and potentially access sensitive data stored locally or transmitted over networks. Once exploited, the attacker can execute arbitrary code with the privileges of the affected firmware process, potentially leading to persistent backdoor installation, data exfiltration, or further network reconnaissance. The dashcam's wireless capabilities provide an accessible attack surface that could be exploited by remote adversaries, while the device's deployment in vehicles creates additional security implications related to personal data protection and vehicle network security. The vulnerability's exploitation requires minimal skill level and can be automated, making it particularly dangerous for widespread deployment scenarios. From an adversarial perspective, this vulnerability aligns with ATT&CK technique T1059.007 Command and Scripting Interpreter: JavaScript, as the exploitation may involve crafting malicious XML payloads that trigger JavaScript execution within the firmware context, though the actual implementation likely involves direct memory corruption techniques.
Mitigation strategies for CVE-2018-4023 should prioritize immediate firmware updates from the vendor to address the identified buffer overflow condition. Network segmentation practices should be implemented to isolate the dashcam device from critical network segments, reducing the attack surface for potential exploitation. Device administrators should consider disabling unnecessary wireless services and implementing strict access controls for any remaining network interfaces. The vulnerability's nature suggests that input validation should be strengthened at multiple layers including network protocol parsing, XML schema validation, and memory allocation boundaries. Security monitoring should be enhanced to detect unusual network traffic patterns that might indicate exploitation attempts. Organizations should implement vulnerability management processes that include regular firmware assessment and patch deployment for IoT devices. The implementation of defensive measures should follow industry standards such as NIST SP 800-125 for IoT security guidelines and ISO/IEC 27030 for supply chain security practices. Regular penetration testing and security assessments should be conducted to identify similar vulnerabilities in other firmware components and network services.