Machine Learning

Endgame Machine Learning Engine Featured in VirusTotal

Signature-Less Endpoint Prevention and Detection Proven to Anticipate Latest Attacker Innovations

Endgame Leapfrogs EDR Incumbents; Dramatically Expanding Preventions and Detections to Stop Zero Days, Malwareless Attacks, and Ransomware

Platform updates solve for industry failures by offering the only end-to-end EDR solution that instantly immobilizes attackers in time to prevent damage and loss 

January 20, 2017
Artemis: An Intelligent Assistant for Cyber Defense
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You’ve used them for directions, to order pizza, to ask about the weather. You’ve called them by their names Siri, Alexa, Cortana... You speak to them like you know them, like they can understand you. Why? Because they usually can. Intelligent assistants are on the rise and increasingly supporting our lives. In large part, this is driven by the user’s desire for ever more efficient querying and frictionless action. Instead of muddling through bloated interfaces, simply speaking or typing your queries or commands through a bot is often easier, faster, and seamless.

Endgame Announces Artemis: ‘Siri for Security’ to Transform SOC Operations

AI-powered chatbot bolsters security analysts to accelerate attack detection and response 

Endgame Joins Anti-Malware Testing Standards Organization (AMTSO)

By participating with AMTSO, Endgame works to advance testing standards for next-gen security technologies

Arlington, VA - January 13, 2017 - Endgame, a leading endpoint security platform closing the protection gap against advanced attackers, announced today that it joined the Anti-Malware Testing Standards Organization (AMTSO). Participation in AMTSO furthers Endgame’s mission to develop scientifically objective and statistically significant third-party testing methodologies for next-gen security products.

Endgame Machine Learning Engine Achieves 100% Independent Malware Certification

Signature-Less Endpoint Prevention and Detection Proven to Anticipate Latest Attacker Innovations

November 18, 2016
Using Deep Learning to Detect DGAs
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Long Short-Term Memory networks - a form of deep learning - are a basic yet powerful approach for detecting domain generation algorithms. We introduce this machine learning approach and how we implement it to detect DGAs at scale.

November 08, 2016
Endgame Research @ AISec: Deep DGA
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At this year's AISec conference, data scientist Bobby Filar presented co-authored work titled DeepDGA: Adversarially-Tuned Domain Generation and Detection. It was quickly evident that more conferences which focus on the intersection of machine learning and infosec are desperately needed.

August 14, 2016
Endpoint Malware Detection for the Hunt: Real-world Considerations

In this post, we'll address operationalizing a malware classifier on an endpoint in the context of a hunt paradigm.

July 31, 2016
It's a Bake-off!: Navigating the Evolving World of Machine Learning Models

In our previous blog, we reviewed some of the core fundamentals in machine learning with respect to malware classification.

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