CVE-2016-10658 in native-opencv
Summary
by MITRE
native-opencv is the OpenCV library installed via npm native-opencv downloads binary resources over HTTP, which leaves it vulnerable to MITM attacks. It may be possible to cause remote code execution (RCE) by swapping out the requested resources with an attacker controlled copy if the attacker is on the network or positioned in between the user and the remote server.
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Analysis
by VulDB Data Team • 02/09/2020
The vulnerability identified as CVE-2016-10658 affects the native-opencv library, a Node.js package that provides OpenCV computer vision functionality through native bindings. This library operates by downloading binary resources from remote servers during installation, creating a critical security weakness in its implementation. The flaw stems from the use of unencrypted HTTP protocols for resource transfer, which exposes the installation process to man-in-the-middle attacks. When users install or update the native-opencv package, the system attempts to fetch pre-compiled binary files containing the actual OpenCV libraries, but these downloads occur over insecure HTTP connections that can be intercepted and manipulated by malicious actors positioned within the network traffic path.
The technical implementation of this vulnerability resides in the package's dependency resolution and resource fetching mechanism. The native-opencv library does not implement any form of integrity verification or secure transport mechanisms when downloading binary components, making it susceptible to attack vectors that leverage network position or compromised intermediaries. This represents a classic case of insecure download handling that directly violates security best practices for software distribution and dependency management. The vulnerability is classified under CWE-319 as "Cleartext Transmission of Sensitive Information" and specifically relates to the improper handling of network communications in client-side software components. Attackers with network access or positioning capabilities can exploit this weakness by intercepting the HTTP requests and replacing the legitimate binary files with malicious copies, potentially leading to remote code execution on systems where the vulnerable package is installed.
The operational impact of this vulnerability extends beyond simple data interception, as successful exploitation can result in complete system compromise through remote code execution. When an attacker successfully substitutes the legitimate binary resources with malicious payloads, any system executing code from the compromised package can become vulnerable to arbitrary command execution, privilege escalation, and persistent backdoor installation. The attack surface is particularly concerning because OpenCV libraries are commonly used in security-sensitive applications, including facial recognition systems, surveillance software, and automated security monitoring tools. Organizations using native-opencv in production environments face significant risk, as the vulnerability can be exploited without requiring user interaction or specific authentication, making it particularly dangerous in networked environments where attackers may have the ability to monitor traffic or position themselves between the client and remote servers.
Mitigation strategies for CVE-2016-10658 require immediate action to address the root cause of insecure resource downloads. The primary recommendation involves upgrading to a newer version of the native-opencv library that implements secure HTTPS transport for all binary downloads, along with cryptographic verification mechanisms such as checksums or digital signatures. Organizations should also implement network monitoring and intrusion detection systems to identify potential man-in-the-middle attacks targeting HTTP traffic. The ATT&CK framework categorizes this vulnerability under T1059.007 for "Command and Scripting Interpreter: JavaScript' and T1566.001 for 'Phishing: Spearphishing Attachment', as attackers may leverage this weakness to deliver malicious payloads through compromised package repositories or network interception. Additionally, security teams should consider implementing network segmentation and mandatory access controls to limit exposure, while ensuring that all software dependencies are verified through secure channels and that organizations maintain up-to-date vulnerability management processes to prevent similar issues in other third-party components.