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Model-Assisted Threat Hunting (M-ATH) with the PEAK Framework
Welcome to the third entry in our introduction to the PEAK Threat Hunting Framework! Taking our detective theme to the next level, imagine a tough case where you need to call in a specialized investigator. For these unique cases, we can use algorithmically-driven approaches called Model-Assisted Threat Hunting (M-ATH).

Trust Unearned? Evaluating CA Trustworthiness Across 5 Billion Certificates
In this blog post, we dive into our recent research project, in which the Splunk SURGe team analyzed more than five billion TLS certificates to find out if the CAs we rely on are really worthy of our trust.

Splunk Field Hashing & Masking Capabilities for Compliance
Satisfy internal and external compliance requirements using Splunk standard components.

Security Content from the Splunk Threat Research Team
The blog explains how STRT develops Splunk Security Content, aiding detection engineering and threat research teams to efficiently detect and respond to potential threats, using ESCU App amidst growing security incidents and system complexity.

Hypothesis-Driven Hunting with the PEAK Framework
Details on hypothesis-driven threat hunting with the PEAK framework.

Planning for Success with Risk-Based Alerting
In our last RBA blog post, we talked about some of the problems RBA can help solve. In this post, we explain the methodology we use with Splunk customers as their security teams start working with RBA.

Machine Learning in Security: Detect Suspicious TXT Records Using Deep Learning
The Splunk Machine Learning for Security (SMLS) team introduces a new detection to detect DNS Tunneling using DNS TXT payloads.

7 questions all CxOs should ask to increase cyber resilience before buying more software
Here are 7 questions you should always ask to help your organisation to make the best possible purchase and increase its cyber resilience at the same time.

Paws in the Pickle Jar: Risk & Vulnerability in the Model-sharing Ecosystem
As AI / Machine Learning (ML) systems now support millions of daily users, has our understanding of the relevant security risks kept pace with this wild rate of adoption?