Software Engineering Institute | Carnegie Mellon University
Software Engineering Institute | Carnegie Mellon University

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Distributed Sensor Data Contextualization at Scale for Threat Intelligence Analysis

  • Abstract

    As organizations operationalize diverse network sensors of various types, from passive sensors to DNS sinkholes to honeypots, there are many opportunities to combine this data for increased contextual awareness for network defense and threat intelligence analysis. In this presentation, we discuss our experiences by analyzing data collected from distributed honeypot sensors, p0f, snort/suricata, and botnet sinkholes as well as enrichments from PDNS and malware sandboxing. We talk through how we can answer the following questions in an automated fashion:  What is the profile of the attacking system? Is the host scanning/attacking my network an infected workstation, an ephemeral scanning/exploitation box, or a compromised web server? If it is a compromised server, what are some possible vulnerabilities exploited by the attacker? What vulnerabilities (CVEs) has this attacker been seen exploiting in the wild and what tools do they drop?  Is this attack part of a distributed campaign or is it limited to my network?

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FloCon 2016 Presentations