Brain
Intelligent Decision-Making At Scale
The planner is a multi-level finite state machine which determines the TTP order when a chain is deployed. The
procedures inside a chain are naturally unordered. Once deployed, it looks at the planner for a decision every time a decision is needed. The finite state algorithm organizes all TTPs into a kill-chain based by ATT&CK tactic and then again by technique. Then, it executes one tactic at a time until it exhausts all TTP files in a given chain.
Always learning
When a chain executes, it collects information which Operator can learn from. As this info is processed, it is fed back into the planner, often opening up a previously closed state. For example, say the planner is currently busy executing decisions for a chain, which has completed the first two tactical states above, and it is executing procedures under Discovery. If the planner learns something which can unlock a "defense evasion" procedure, it will instruct the chain to drop out of the discovery state and into the defense evasion one in order to do the newly discovered action.
Updated about 1 year ago