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Automating Malicious Infrastructure Discovery Using Graph Neural Networks

/ 1 min read

🕵️‍♂️ Automated Detection Enhances Cybersecurity Against Evolving Threats. Threat actors often leave traces of their infrastructure during large-scale cyberattacks, which defenders can exploit to uncover new indicators of compromise. This article discusses the benefits of automated pivoting using a graph neural network (GNN) to detect malicious domains, illustrated through three case studies: a postal service phishing campaign, a web skimmer campaign, and financial services phishing. By continuously monitoring and correlating known indicators, defenders can proactively identify and block new attack infrastructure before it is weaponized. Palo Alto Networks’ Advanced URL Filtering and DNS Security tools enhance protection against these threats, demonstrating the importance of automated detection in cybersecurity.

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