Detecting Compromised Credentials in a Credential Stuffing Attack

Patent №

US 11,044,261

Granted

2021-06-22

Filed 2018

Owner

SHAPE SECURITY, INC.

Lab

AI components

4

nlp · vision · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

16024691

Techniques are provided for detecting compromised credentials in a credential stuffing attack. A set model is trained based on a first set of spilled credentials. The set model does not comprise any credential of the first set of spilled credentials. A first request is received from a client computer with a first candidate credential to login to a server computer. The first candidate credential is tested for membership in the first set of spilled credentials using the set model. In response to determining the first set of spilled credentials includes the first candidate credential using the set model, one or more negative actions is performed.

Natural languageVisionPlanningAI hardwareH04L 63/1416H04L 63/1425H04L 67/02G06N 20/00H04L 63/083

AI classification

AI hardware1.00
Planning0.95
Natural language0.79
Vision0.77
Machine learning0.40
Knowledge representation0.10
Evolutionary computation0.02
Speech0.00

Ownership

SHAPE SECURITY, INC.

assignment · 462470287

Assignors

MOEN, DANIEL G, SCHROEDER, CARL

On an employer assignment, the assignors are typically the inventors.

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