The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 06, 2025

Filed:

Oct. 11, 2022
Applicant:

Rapid7, Inc., Boston, MA (US);

Inventors:

Wah-Kwan Lin, Melrose, MA (US);

Leonardo Varela Guevara, Austin, TX (US);

Cody Pierce, Austin, TX (US);

Assignee:

Rapid7, Inc., Boston, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 9/40 (2021.12); G06F 3/0481 (2021.12); G06F 3/0484 (2021.12); G06F 8/65 (2017.12); G06N 5/04 (2022.12); G06N 7/01 (2022.12); G06N 20/00 (2018.12); G06Q 10/0635 (2022.12); G06Q 10/0637 (2022.12); G06Q 10/10 (2022.12);
U.S. Cl.
CPC ...
H04L 63/1433 (2012.12); G06F 8/65 (2012.12); G06N 5/04 (2012.12); G06N 7/01 (2022.12); G06N 20/00 (2018.12); G06Q 10/0635 (2012.12); G06Q 10/0637 (2012.12); G06Q 10/10 (2012.12); H04L 63/102 (2012.12); H04L 63/20 (2012.12); G06F 3/0481 (2012.12); G06F 3/0484 (2012.12);
Abstract

Systems and methods are provided to build a machine learned exploitability risk model that predicts, based on the characteristics of a set of machines, a normalized risk score quantifying the risk that the machines are exploitable by a set of attacks. To build the model, a training dataset is constructed by labeling characteristic data of a population of machines with exploitation test results obtained by simulating a set of attacks on the population. The model is trained using the training data to accurately predict a probability that a given set of machines is exploitable by the set of attacks. In embodiments, the model may be used to make quick assessments about how vulnerable a set of machines are to the set of attacks. In embodiments, the model may be used to compare the effectiveness of different remediation actions to protect against the set of attacks.


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