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Unsecured JupyterLab and Jupyter Notebooks servers abused for illegal streaming of Sports events

Threat actors exploit misconfigured JupyterLab and Jupyter Notebooks servers to rip sports streams and illegally redistribute them. Researchers from security firm Aqua observed threat actors exploiting misconfigured JupyterLab and Jupyter Notebook servers to hijack environments, deploy streaming tools, and duplicate live sports broadcasts on illegal platforms. “threat actors using misconfigured servers to hijack environments for […] Threat actors exploit misconfigured JupyterLab and Jupyter Notebooks servers to rip sports streams and illegally redistribute them. Researchers from security firm Aqua observed threat actors exploiting misconfigured JupyterLab and Jupyter Notebook servers to hijack environments, deploy streaming tools, and duplicate live sports broadcasts on illegal platforms. “threat actors using misconfigured servers to hijack environments for streaming sports events. By exploiting misconfigured JupyterLab and Jupyter Notebook applications, attackers drop live streaming capture tools and duplicate the broadcast on their illegal server, thus conducting stream ripping” reads the report published by Aqua. JupyterLab and Jupyter Notebook are widely used interactive tools for data science. While essential for data operations, improper security configurations can expose organizations to risks, making secure deployment critical. Aqua Nautilus researchers uncovered the attacks after deploying honeypots that mimic real-world development environments. A recent threat hunting operation conducted by Aqua researchers analyzed outbound network traffic and executed binaries in containerized environments. Using honeypots and a data warehouse for cross-referencing suspicious binaries and network events, researchers detected anomalies tied to illicit activity. One finding involved the open-source tool ffmpeg, commonly used for multimedia processing. Though typically benign, its use in these events suggests a potential shift toward malicious exploitation The Jupyter Lab and Jupyter Notebook honeypots set up by the company reveal were affetced by vulnerabilities and used weak passwords. The threat actors exploited unauthenticated access to Jupyter Lab and Jupyter Notebook to establish initial access and achieve remote code execution. The attack chain starts with threat actors updating the server, then downloaded the tool ffmpeg. Then attackers executed ffmpeg to capture live streams of sports events and redirected them to their server. “While the immediate impact on organizations might appear minimal (though it significantly affects the entertainment industry), it could be dismissed as merely a nuisance.” cotinues the report. “However, it’s crucial to remember that the attackers gained access to a server intended for data analysis, which could have serious consequences for any organization’s operations. Potential risks include denial of service, data manipulation, data theft, corruption of AI and ML processes, lateral movement to more critical environments and, in the worst-case scenario, substantial financial and reputational damage.” In the attack analyzed by Aqua, threat actors downloaded FFmpeg from MediaFire and use the tool to record live sports events feeds from the Qatari beIN Sports network. The output is re-directed to ustream.tv. The attackers used an IP address from an Algerian AS (41.200.191[.]23), suggesting a possible Arab origin for the threat actors. “Traditional security tools often miss subtle indicators, especially in complex environments like JupyterLab and Jupyter Notebook, where legitimate tools can be used for unauthorized purposes. By using behavioral analysis to spot anomalies such as the unusual deployment and execution of ffmpeg for live-stream capture our team uncovered covert sports piracy operations that bypassed standard alerts.” concludes the report. Follow me on Twitter: @securityaffairs and Facebook and Mastodon Pierluigi Paganini (SecurityAffairs hacking, piracy)

Published: 2024-11-20T07:32:57











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