Microsoft Defender ATP

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Forrester names Microsoft a Leader in 2019 Endpoint Security Suites Wave

Credit to Author: Eric Avena| Date: Tue, 01 Oct 2019 17:30:05 +0000

Microsoft is positioned as a leader in The Forrester Wave™: Endpoint Security Suites, Q3 2019, receiving among the second highest scores in both the strategy and market presence categories.

The post Forrester names Microsoft a Leader in 2019 Endpoint Security Suites Wave appeared first on Microsoft Security.

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Deep learning rises: New methods for detecting malicious PowerShell

Credit to Author: Eric Avena| Date: Tue, 03 Sep 2019 16:00:03 +0000

We adopted a deep learning technique that was initially developed for natural language processing and applied to expand Microsoft Defender ATP’s coverage of detecting malicious PowerShell scripts, which continue to be a critical attack vector.

The post Deep learning rises: New methods for detecting malicious PowerShell appeared first on Microsoft Security.

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Dismantling a fileless campaign: Microsoft Defender ATP’s Antivirus exposes Astaroth attack

Credit to Author: Eric Avena| Date: Mon, 08 Jul 2019 16:00:51 +0000

Advanced technologies in Microsoft Defender ATP’s Antivirus exposed and defeated a widespread fileless campaign that completely “lived off the land” throughout a complex attack chain that run the info-stealing backdoor Astaroth directly in memory

The post Dismantling a fileless campaign: Microsoft Defender ATP’s Antivirus exposes Astaroth attack appeared first on Microsoft Security.

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New machine learning model sifts through the good to unearth the bad in evasive malware

Credit to Author: Eric Avena| Date: Thu, 25 Jul 2019 16:30:55 +0000

Most machine learning models are trained on a mix of malicious and clean features. Attackers routinely try to throw these models off balance by stuffing clean features into malware. Monotonic models are resistant against adversarial attacks because they are trained differently: they only look for malicious features. The magic is this: Attackers can’t evade a monotonic model by adding clean features. To evade a monotonic model, an attacker would have to remove malicious features.

The post New machine learning model sifts through the good to unearth the bad in evasive malware appeared first on Microsoft Security.

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