Russians at it again, Microsoft and Adobe updates, PoS breaches, US-CERT throws TLS shade, epilepsy tweet stalking, Tesla's billion, lip-reading AI, autonomous BMWs, Fiber Lasers, taxing robots, Green Zones and Red Zones, AI disruption of healthcare, discovery, recommendations, and aphorisms, and more…

Russians at it again, Microsoft and Adobe updates, PoS breaches, US-CERT throws TLS shade, epilepsy tweet stalking, Tesla's billion, lip-reading AI, autonomous BMWs, Fiber Lasers, taxing robots, Green Zones and Red Zones, AI disruption of&nbsp;healthcare, discovery, recommendations, and&nbsp;aphorisms, and more&hellip;

Unsupervised Learning is a Security, AI, and Meaning-focused podcast that looks at how best to thrive as humans in a post-AI world. It combines original ideas, analysis, and mental models to bring not just the news, but why it matters and how to respond.

Unsupervised Learning is a Security, AI, and Meaning-focused podcast that looks at how best to thrive as humans in a post-AI world. It combines original ideas, analysis, and mental models to bring not just the news, but why it matters and how to respond.

Exploring the fascinating intersection of security, technology, and humans.

Unsupervised Learning

Unsupervised Learning: No. 70

In this conversation, I speak with Rob Allen, Chief Product Officer at ThreatLocker.

We talk about:

ThreatLocker’s Unique Zero Trust Approach to Cybersecurity:
How ThreatLocker’s "deny by default, permit by exception" methodology, along with automated application learning and built-in definitions for over 4,000 applications, simplifies allowlisting and enhances endpoint security.

Innovations in ThreatLocker’s Control Features:
How ThreatLocker’s ringfencing prevents unauthorized application interactions and data access, and dynamic firewalls mitigate risks like lateral movement and ransomware attacks through endpoint-level network segmentation.

Recent Developments and Cloud Expansion:
How ThreatLocker Detect and Cloud Detect provide advanced detection capabilities for endpoint and cloud environments, including Office 365, enabling anomaly detection, centralized alerts, and proactive threat management.

And more.

Into (00:00:00)
ThreatLocker's Zero Trust Cybersecurity Approach (00:00:31)
Understanding Allow Listing in Cybersecurity (00:01:49)
Managing Software Updates with ThreatLocker (00:02:13)
Automated Application Updates for Over 4000 Programs (00:04:11)
Vendor Collaboration for Early Software Updates (00:05:40)
Challenges and Risks of Immediate Software Updates (00:06:53)
Assuming Breach: A Core Cybersecurity Principle (00:08:10)
Implementing Zero Trust Strategies with Ring Fencing (00:09:30)
Controlling Application Interactions to Prevent Threats (00:09:50)
Advanced Data Protection with Storage Control (00:13:17)
Dynamic ACLs for Smarter Network Control (00:15:48)
Ransomware Risks from Open Ports (00:16:50)
Using Shodan to Identify Open Port Vulnerabilities (00:17:19)
Building Application Allow Lists with Contextual Data (00:18:43)
Learning Mode for Application and Traffic Visibility (00:19:36)
Balancing User Behavior Control and Workflow (00:20:44)
Integrating Detection and Control with ThreatLocker Detect (00:21:44)
Why Detection is Critical in Cybersecurity Layers (00:22:41)
Response Mechanisms and Automated Remediation (00:24:02)
Lockdown Mode: Ultimate Isolation from Threats (00:25:38)
Streamlined Application Approvals with Cyber Hero (00:26:36)
Breaking Down Ransomware Attack Stages (00:27:46)
Introducing Cloud Detect for Cloud Security (00:29:39)
How to Learn More About ThreatLocker Solutions (00:30:47)

In this conversation, I speak with Rob Allen, Chief Product Officer at ThreatLocker.
We talk about:
ThreatLocker’s Unique Zero Trust Approach to Cybersecurity: How ThreatLocker’s "deny by default, permit by exception" methodology, along with automated application learning and built-in definitions for over 4,000 applications, simplifies allowlisting and enhances endpoint security.
Innovations in ThreatLocker’s Control Features: How ThreatLocker’s ringfencing prevents unauthorized application interactions and data access, and dynamic firewalls mitigate risks like lateral movement and ransomware attacks through endpoint-level network segmentation.
Recent Developments and Cloud Expansion: How ThreatLocker Detect and Cloud Detect provide advanced detection capabilities for endpoint and cloud environments, including Office 365, enabling anomaly detection, centralized alerts, and proactive threat management.
And more.
Into (00:00:00) ThreatLocker's Zero Trust Cybersecurity Approach (00:00:31) Understanding Allow Listing in Cybersecurity (00:01:49) Managing Software Updates with ThreatLocker (00:02:13) Automated Application Updates for Over 4000 Programs (00:04:11) Vendor Collaboration for Early Software Updates (00:05:40) Challenges and Risks of Immediate Software Updates (00:06:53) Assuming Breach: A Core Cybersecurity Principle (00:08:10) Implementing Zero Trust Strategies with Ring Fencing (00:09:30) Controlling Application Interactions to Prevent Threats (00:09:50) Advanced Data Protection with Storage Control (00:13:17) Dynamic ACLs for Smarter Network Control (00:15:48) Ransomware Risks from Open Ports (00:16:50) Using Shodan to Identify Open Port Vulnerabilities (00:17:19) Building Application Allow Lists with Contextual Data (00:18:43) Learning Mode for Application and Traffic Visibility (00:19:36) Balancing User Behavior Control and Workflow (00:20:44) Integrating Detection and Control with ThreatLocker Detect (00:21:44) Why Detection is Critical in Cybersecurity Layers (00:22:41) Response Mechanisms and Automated Remediation (00:24:02) Lockdown Mode: Ultimate Isolation from Threats (00:25:38) Streamlined Application Approvals with Cyber Hero (00:26:36) Breaking Down Ransomware Attack Stages (00:27:46) Introducing Cloud Detect for Cloud Security (00:29:39) How to Learn More About ThreatLocker Solutions (00:30:47)

A Conversation with Rob Allen from ThreatLocker

https://api.omny.fm/orgs/070af456-729b-4a0f-9c09-a6c100397b59/clips/6584c3d5-d44d-4a37-82f7-b22c005a6109/transcript

My conversation with Jason Haddix from Flare, Google finds a Zero-Day with AI, Robot Dogs Protecting Mar-a-Lago, and more...

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https://danielmiessler.com/subscribe

Join the UL community at:
https://danielmiessler.com/upgrade

Follow on X:
https://twitter.com/danielmiessler

Follow on LinkedIn:
https://www.linkedin.com/in/danielmiessler

See you in the next one!

My conversation with Jason Haddix from Flare, Google finds a Zero-Day with AI, Robot Dogs Protecting Mar-a-Lago, and more...
Subscribe to the newsletter at:  <a href="https://danielmiessler.com/subscribe">https://danielmiessler.com/subscribe</a>
Join the UL community at: <a href="https://danielmiessler.com/upgrade">https://danielmiessler.com/upgrade</a>
Follow on X: <a href="https://twitter.com/danielmiessler">https://twitter.com/danielmiessler</a>
Follow on LinkedIn: <a href="https://www.linkedin.com/in/danielmiessler">https://www.linkedin.com/in/danielmiessler</a>
See you in the next one!

UL NO. 458: Ollama Vulnerabilities, Rating AI Using AI, The Mantis Hack-back Framework

https://api.omny.fm/orgs/070af456-729b-4a0f-9c09-a6c100397b59/clips/094a744c-9e33-4175-957d-b22b013da1d7/transcript

Streamline Your Cybersecurity with Flare Here:
https://try.flare.io/unsupervised-learning/

In this conversation, I speak with Jason Haddix, founder of Arcanum Security and CISO at Flare.

We talk about:

Flare's Unique Approach to Threat Intelligence:
How Flare's capability to uncover compromised credentials and cookies from the dark web and private forums has been crucial in red team engagements.

Challenges of Credential Theft and Advanced Malware Techniques:
How adversaries utilize tools like the RedLine Stealer malware to gather credentials, cookies, and other sensitive information, and this stolen data enables attackers to bypass authentication protocols, emphasizing the need for comprehensive exposure management.

Jason's Journey To Founding Arcanum & Arcanum's Security Training Programs:
How Jason now advises on product development and threat intelligence as Flare's CISO and his journey to fund Arcanum, a company focused on red teaming and cybersecurity, and Arcanum's specialized training programs focusing on offensive security and using AI in security roles. 

And more

Introduction to the Podcast (00:00:00)
Guest Excitement on Podcast (00:00:20)
Jason's New Business and Flare Role (00:00:24)
Career Shift from Ubisoft to Red Teaming (00:01:02)
Evolution of Adversary Tactics (00:02:04)
Flare's Credential Exposure Management (00:02:58)
Synergy Between Arcanum and Flare(00:03:55)
Dark Web Credential Compromise (00:04:45)
Challenges with Two-Factor Authentication (00:06:25)
Cookie Theft and Unauthorized Access (00:07:39)
Redline Malware and Its Impact (00:08:12)
Flare's Research Capabilities (00:09:50)
Potential for Advanced Malware Detection (00:11:40)
Expansion of Threat Intelligence Services (00:12:15)
Vision for a Unified Security Dashboard (00:13:25)
Integrating Threat Intelligence with Identity Management (00:14:00)
Credential Update Notifications via API (00:15:54)
Automated Credential Management Potential (00:17:28)
AI Features in Security Platforms (00:17:32)
Exploration of Automated Security Responses (00:18:38)
Introduction to Arcanum Security (00:19:25)
Overview of Arcanum Training Courses (00:20:25)
Necessity for Up-to-Date Training (00:22:15)
Guest Experts in Training Sessions (00:23:08)
Upcoming Features for Flare (00:25:11)
Integrating Vulnerability Management (00:28:08)
Accessing Flare's Free Trial (00:28:25)
Learning More About Arcanum (00:29:09)

Streamline Your Cybersecurity with Flare Here: <a href="https://try.flare.io/unsupervised-learning/">https://try.flare.io/unsupervised-learning/</a>
In this conversation, I speak with Jason Haddix, founder of Arcanum Security and CISO at Flare.
We talk about:
Flare's Unique Approach to Threat Intelligence: How Flare's capability to uncover compromised credentials and cookies from the dark web and private forums has been crucial in red team engagements.
Challenges of Credential Theft and Advanced Malware Techniques: How adversaries utilize tools like the RedLine Stealer malware to gather credentials, cookies, and other sensitive information, and this stolen data enables attackers to bypass authentication protocols, emphasizing the need for comprehensive exposure management.
Jason's Journey To Founding Arcanum &amp; Arcanum's Security Training Programs: How Jason now advises on product development and threat intelligence as Flare's CISO and his journey to fund Arcanum, a company focused on red teaming and cybersecurity, and Arcanum's specialized training programs focusing on offensive security and using AI in security roles. 
And more
Introduction to the Podcast (00:00:00) Guest Excitement on Podcast (00:00:20) Jason's New Business and Flare Role (00:00:24) Career Shift from Ubisoft to Red Teaming (00:01:02) Evolution of Adversary Tactics (00:02:04) Flare's Credential Exposure Management (00:02:58) Synergy Between Arcanum and Flare(00:03:55) Dark Web Credential Compromise (00:04:45) Challenges with Two-Factor Authentication (00:06:25) Cookie Theft and Unauthorized Access (00:07:39) Redline Malware and Its Impact (00:08:12) Flare's Research Capabilities (00:09:50) Potential for Advanced Malware Detection (00:11:40) Expansion of Threat Intelligence Services (00:12:15) Vision for a Unified Security Dashboard (00:13:25) Integrating Threat Intelligence with Identity Management (00:14:00) Credential Update Notifications via API (00:15:54) Automated Credential Management Potential (00:17:28) AI Features in Security Platforms (00:17:32) Exploration of Automated Security Responses (00:18:38) Introduction to Arcanum Security (00:19:25) Overview of Arcanum Training Courses (00:20:25) Necessity for Up-to-Date Training (00:22:15) Guest Experts in Training Sessions (00:23:08) Upcoming Features for Flare (00:25:11) Integrating Vulnerability Management (00:28:08) Accessing Flare's Free Trial (00:28:25) Learning More About Arcanum (00:29:09)

A Conversation with Jason Haddix from Flare

https://api.omny.fm/orgs/070af456-729b-4a0f-9c09-a6c100397b59/clips/7103eace-01f3-4545-a979-b225015b47c2/transcript

Unsupervised Learning: No. 70

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