Cyber Security Operations
Lately I have been playing with having MISP be the Intelligence Sharing platform for a number of business intelligence functions. However, the main issue with MISP (from a user’s perspective) is the interface, and how a less technical person would generate information for the platform.
This is where pairing MISP and Maltego together goes really well, and even results in less technical people being able to generate technical data for incorporation into intelligence operations.
Intelligence is the enrichment of data or information, its classification and publication by experts within a field. The resultant output is ordinarily a qualitative assessment backed by quantitative metrics, or absolutes which formed part of the data or information it was derived from.
In terms of Cyber Threat Intelligence, this goes beyond the extraction of IOCs, strings, and the generation of cryptographic hashes, and fuzzy hashing – this is the correlation of events, actors, methods, and motives to generate Threat Intelligence which aims to describe the objectives, motives, capability and perhaps the identity of a threat actor.
Over the last few months I have been working away on several work tasks which have had me hunting for threats within an immensely complex environment. Part of this hunt has involved the analysis and selection of threat feeds for incorporation into other tools to hunt known bad indicators. In this post I will be talking through the deployment of MISP to enable aggregation of threat indicators, and the generation of exports which may be ingested into other platforms.
It seems to be a significant buzzword nowadays, but Threat Intelligence is available in an abundance from a wide range of curators and commercial suppliers.
So what does it take to correlate observables such as precursors to determine if they are an indicator of compromise, and by whom have they been generated?
