CVE-2023-6322 in Camera
Summary
by MITRE • 05/15/2024
A stack-based buffer overflow vulnerability exists in the message parsing functionality of the Roku Indoor Camera SE version 3.0.2.4679 and Wyze Cam v3 version 4.36.11.5859. A specially crafted message can lead to stack-based buffer overflow. An attacker can make authenticated requests to trigger this vulnerability.
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Analysis
by VulDB Data Team • 02/12/2025
This vulnerability represents a critical stack-based buffer overflow flaw within the message parsing components of two popular IoT camera systems, specifically affecting Roku Indoor Camera SE version 3.0.2.4679 and Wyze Cam v3 version 4.36.11.5859. The issue stems from inadequate input validation mechanisms within the firmware's message handling routines, creating a condition where maliciously crafted data can exceed the allocated buffer space on the stack. The vulnerability is particularly concerning because it requires only authenticated access to exploit, meaning that an attacker who has already gained credentials to the device can leverage this flaw to execute arbitrary code or cause system instability. This type of vulnerability falls under CWE-121, which specifically addresses stack-based buffer overflow conditions, and aligns with ATT&CK technique T1059.007 for command and scripting interpreter execution. The attack surface is further expanded by the fact that these are consumer-grade IoT devices that often operate in residential environments where physical security may be limited.
The technical implementation of this vulnerability occurs when the camera's firmware processes incoming network messages without proper bounds checking on the data length or content. When a maliciously constructed message exceeds the predetermined buffer size allocated for message parsing, the excess data overflows into adjacent stack memory locations, potentially overwriting return addresses, function pointers, or other critical program state information. This overflow can be exploited to redirect program execution flow, allowing an attacker to inject and execute malicious code within the device's operational context. The authenticated requirement suggests that the vulnerability exists in the communication protocols that handle user requests, likely involving configuration changes, firmware updates, or status reporting mechanisms. The impact extends beyond simple denial of service, as successful exploitation could lead to complete device compromise and potential lateral movement within the local network.
The operational implications of this vulnerability are severe for both device manufacturers and end users. IoT devices like these cameras are frequently deployed in environments where they operate continuously and may be difficult to physically access for maintenance or updates. The authenticated nature of the exploit means that attackers who have obtained legitimate user credentials or have managed to compromise device authentication mechanisms can remotely execute code on the affected devices. This creates a significant risk for privacy and security, as compromised cameras can be used for persistent surveillance, data exfiltration, or as entry points for broader network attacks. The vulnerability also highlights the broader security challenges in IoT device firmware development, where memory safety issues are common due to resource constraints and rapid development cycles. Organizations and individuals using these devices face potential exposure to unauthorized access, data breaches, and compromised network infrastructure. The attack vector through authenticated requests makes this particularly dangerous in environments where device credentials might be weak or compromised through social engineering attacks.
Mitigation strategies for this vulnerability should focus on both immediate remediation and long-term security improvements. The primary recommendation is to apply firmware updates from the respective manufacturers as soon as patches become available, which should include proper bounds checking and input validation in the message parsing routines. Network segmentation and access controls should be implemented to limit the potential impact of device compromise, including restricting network access to these devices through firewalls and access control lists. Regular credential rotation and strong authentication mechanisms should be enforced to minimize the risk of unauthorized access. Security monitoring should be implemented to detect unusual network activity or unauthorized access attempts to these devices. Additionally, organizations should consider implementing network intrusion detection systems that can identify malicious message patterns attempting to exploit buffer overflow vulnerabilities. The vulnerability also underscores the importance of secure coding practices and regular security assessments during the development lifecycle, particularly for embedded systems where memory safety is critical. Organizations should conduct thorough vulnerability assessments of their IoT deployments and implement comprehensive device management policies to ensure timely patching and security updates.