Abstract: A system for machine learning data generation and visualization comprises a processor configured to generate a queue module that receives a data file pertaining to a problem to be addressed using a machine learning model, a feature selector module configured to select features extracted from the data file, a vectorizing module configured to generate vectorized feature data from the features, a feature generation module configured to generate data features with reduced dimensionality from the vectorized data using autoencoding techniques, a model handler module configured to select a machine learning model to analyze the data features with reduced dimensionality, to transmit the model for execution, and to receive the results of the execution, a visualizer module configured to parse a dimensionality of the results and select a visualization approach based on the dimensionality, and an output module configured to provide the results for rendering the visualization approach.

Abstract: A system for identifying and classifying malicious URLs comprising one or more processors having access to program instructions that when executed generate a queue module configured to receive a file including a potentially malicious URL from a source, a feature selector module configured to select features of interest to identifying URLs extracted from the file, a vectorizing module configured to generate vectorized feature data from the features, a feature generation module configured to generate URL data features with reduced dimensionality from the vectorized data using autoencoding techniques, a model handler module configured to select an artificial intelligence/machine learning (AI/ML) model to analyze the URL data features with reduced dimensionality, to transmit the model for execution, and to receive the results of the execution of the selected AI/ML model, and a visualizer module configured to provide a rendering of results of the execution of the selected AI/ML model.

Abstract: A non-transitory computer-readable medium comprising instructions which cause a computer system to carry out a method for artifact metadata extraction and analysis.

Abstract: A non-transitory computer-readable medium comprising instructions which cause a computer system to carry out a method for artifact metadata extraction and analysis.

Abstract: A non-transitory computer-readable medium comprising instructions which, when executed by a computer system, cause the computer system to carry out a method of forensic artifact analysis including steps of receiving from an end user a request to analyze for potential maliciousness an artifact which is included with the request, identifying a type of the received artifact, delivering the artifact to an analyzer adapted to analyze the identified artifact type, wherein the analyzer produces an analysis output, generating a query to a central intelligence database based on the analysis output, analyzing the artifact and results of the query using a plurality of analysis modules to provide information regarding maliciousness of the artifact, and providing a visualization of results of the analysis by the plurality of analysis modules to the end user.