US 11,777,981 B1
Risk scoring based on compliance verification test results in a local network
James B. Hoscheit, Gallatin, TN (US); Peyton T. Ball, Smyrna, TN (US); E. Egon Rinderer, Rossville, TN (US); and John Phillip Ham, Lee's Summit, MO (US)
Assigned to TANIUM INC., Kirkland, WA (US)
Filed by Tanium Inc., Emeryville, CA (US)
Filed on Jan. 20, 2023, as Appl. No. 18/99,854.
Application 18/099,854 is a continuation of application No. 17/001,586, filed on Aug. 24, 2020, granted, now 11,563,764.
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 15/16 (2006.01); H04L 9/40 (2022.01); H04L 43/50 (2022.01)
CPC H04L 63/1433 (2013.01) [H04L 43/50 (2013.01); H04L 63/20 (2013.01)] 24 Claims
OG exemplary drawing
 
1. A method, including:
at a server system in a computer network that has a plurality of nodes, wherein each node of the plurality of nodes comprises a computational machine and has a defined location in a linearly ordered communication orbit comprising said plurality of nodes:
transmitting, via the linearly ordered communication orbit, one or more requests to a plurality of recipient nodes in a first subset of the plurality of nodes; wherein the one or more requests cause the computational machine at each recipient node of the plurality of recipient nodes to:
locally evaluate a set of local environment verification tests to produce test results for the computational machine at the recipient node; and
locally map the test results into risk scores for the computational machine at the recipient node;
transmitting, via the linearly ordered communication orbit, one or more queries to the plurality of recipient nodes;
receiving in response to the one or more queries, via the linearly ordered communication orbit, from the plurality of recipient nodes, test results and risk scores locally generated by and sent by the computational machines at the plurality of recipient nodes in response to the one or queries; and
identifying, based on the received test results and risk scores, computational machines and/or control categories having risk scores satisfying predefined criteria.