Posted on 2021-04-29Steve Esling
Making a good machine learning model involves more than just good data and well-selected features. Each model also has its own set of hyperparameters, variables which are set before training begins to influence how a given model learns. In this article, we go over grid search, a technique used to select the best hyperparameters for a model quickly and efficiently!
Posted on 2021-04-16Dmitry Melikov
It's no secret that today, targeted attacks and phishing attacks are the primary means of spreading malware. The purpose of which is to collect user data, theft banking data, and espionage. Threat Actors are constantly working to improve the tools they use. In this article, I will try to show you how the Hanictor group is improving their toolbox.
Posted on 2021-03-31William MacArthur
What we all need now and again is some exciting news, and since we have some, we wanted to make an article to share it! Earlier this month, our friends at Abuse.ch officially announced in a tweet that their MalwareBazaar project has integrated with InQuest’s Deep File Inspection (DFI) analysis stack.
Posted on 2021-03-29Josiah Smith
At InQuest, we're fanatical about malware analysis and ingest real-world samples at-scale, dissecting millions of files daily. We leverage a combination of our Deep File Inspection (DFI™) analysis engine and a proprietary machine-learning apparatus to distill a daily volume of millions of samples down to a harvest consisting of dozens of "interesting" samples.
Posted on 2021-02-26Deandre Hall
The staff at InQuest have been busy running a variety of different research experiments in the realm of bleeding-edge maldoc discovery to ensure the efficacy of detection for our customers and generate threat intelligence. One such experiment is our Twitter bot that tweets about malicious stage-2 RTFs referenced from documents found within the InQuest Labs Corpus. Another additional research project includes the mass curation and password cracking attempts of encrypted files.