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The Truth Behind AI Agents: Hype vs. Reality
AI is evolving fast, and AI agents are the latest buzzword. But what exactly are they? Are they truly intelligent, or just automation in disguise? In this episode, Caleb Sima and Ashish Rajan spoke to Daniel Miessler—a cybersecurity veteran who is now deep into AI security research.🎙️ In this episode, we cover:✅ What AI agents really are (and what they’re NOT)✅ How AI is shifting from searching to making decisions✅ The biggest myths and misconceptions about AI automation✅ Why most companies calling their tools “AI agents” are misleading you✅ How AI agents will impact cybersecurity, business, and the future of work✅ The security risks and opportunities no one is talking aboutQuestions asked:(00:00) Introduction(03:50) What are AI Agents?(06:53) Use case for AI Agents(14:39) Can AI Agents be used for security today?(22:06) AI Agent’s impact on Attackers and Defenders in Cybersecurity(37:05) AI Agents and Non Human Identities(45:22) The big picture with AI Agents(48:28) Transparency and Ethics for AI Agents(58:36) Whats exciting about future of AI Agents?(01:08:00) Would there still be value for foundational knowledge
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1:19:06
How AI is changing Detection Engineering & SOC Operations?
AI is revolutionizing many things, but how does it impact detection engineering and SOC teams? In this episode, we sit down withDylan Williams, a cybersecurity practitioner with nearly a decade of experience in blue team operations and detection engineering. We speak about how AI is reshaping threat detection and response, the future role of detection engineers in an AI-driven world, can AI reduce false positives and speed up investigations, the difference between automation vs. agentic AI in security and practical AI tools you can use right now in detection & responseQuestions asked:(00:00) Introduction(02:01) A bit about Dylan Williams(04:05) Keeping with up AI advancements(06:24) Detection with and without AI(08:11) Would AI reduce the number of false positives?(10:28) Does AI help identity what is a signal?(14:18) The maturity of the current detection landscape(17:01) Agentic AI vs Automation in Detection Engineering(19:35) How prompt engineering is evolving with newer models?(25:52) How AI is imapcting Detection Engineering today?(36:23) LLM Models become the detector(42:03) What will be the future of detection?(47:58) What can detection engineers practically do with AI today?(52:57) Favourite AI Tool and Final thoughts on Detection EngineeringResources spoken about during the episode:exa.ai - The search engine for AIBuilding effective agents (Athropic’s blog different architecture and design patterns for agents)-https://www.anthropic.com/research/building-effective-agents -Introducing Ambient Agents (LangChain’s blog on Ambient Agents) -https://blog.langchain.dev/introducing-ambient-agents/ -Jared Atkinson’s Blog on Capability Abstraction -https://posts.specterops.io/capability-abstraction-fbeaeeb26384LangGraph Studio -https://studio.langchain.com/n8n -https://n8n.io/Flowise -https://flowiseai.com/CrewAI -https://www.crewai.com/
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57:43
What does your AI cybersecurity plan look like for 2025?
Welcome to 2025! In this episode our hosts Ashish Rajan and Caleb Sima, tackle the pressing question: What should your AI cybersecurity game plan look like this year? The rapid evolution of agentic AI—where AI agents can perform tasks autonomously—is set to transform businesses, but it comes with unprecedented security challenges. From the resurgence of Identity and Access Management (IAM) to the urgent need for least privilege strategies, this episode captures actionable insights for CISOs and security leaders. What is agentic AI and how it may impact businesses? Top 3 priorities for building an effective AI security plan. The critical role of IAM and least privilege in managing AI agents. Real-world examples of how agentic AI will impact operations and security. Practical advice on incident response, monitoring, and preparing for AI-driven challenges. Questions asked: (00:00) Introduction (01:59) The current state of AI in Enterprise (10:22) Different Levels of Agentic AI (12:05) CISO AI Cybersecurity Game plan for 2025 (15:57) IAM’s fire comeback (23:11) Top 3 things for AI Cybersecurity Plan
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38:25
AI Cybersecurity Predictions 2025: Revolution or Reality?
In this episode, to kick of 2025, we dive deep into AI and cybersecurity predictions for 2025 exploring the opportunities, challenges, and trends shaping the future of the industry. Our hosts, Ashish Rajan and Caleb Sima sat down to discuss the evolution of SOC automation and its real-world impact on cybersecurity, the practical use cases for AI-enhanced security tools in organizations, why data security might be the real winner in 2025, the potential of agentic AI and its role in transforming security operations and predictions for AI-powered startups and their production-ready innovations in 2025. Questions asked: (00:00) Introduction (06:32) Current AI Innovation in Cybersecurity (21:57) AI Security Predictions for 2025 (25:02) Data Security and AI in 2025 (30:56) The rise of Agentic AI (35:40) Planning for AI Skills in the team (42:53) What to ditch from 2024? (48:00) AI Making Security Predictions for 2025
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56:53
AI Red Teaming in 2024 and Beyond
Host Caleb Sima and Ashish Rajan caught up with experts Daniel Miessler (Unsupervised Learning), Joseph Thacker (Principal AI Engineer, AppOmni) to talk about the true vulnerabilities of AI applications, how prompt injection is evolving, new attack vectors through images, audio, and video and predictions for AI-powered hacking and its implications for enterprise security. Whether you're a red teamer, a blue teamer, or simply curious about AI's impact on cybersecurity, this episode is packed with expert insights, practical advice, and future forecasts. Don’t miss out on understanding how attackers leverage AI to exploit vulnerabilities—and how defenders can stay ahead. Questions asked: (00:00) Introduction (02:11) A bit about Daniel Miessler (02:22) A bit about Rez0 (03:02) Intersection of Red Team and AI (07:06) Is red teaming AI different? (09:42) Humans or AI: Better at Prompt Injection? (13:32) What is a security vulnerability for a LLM? (14:55) Jailbreaking vs Prompt Injecting LLMs (24:17) Whats new for Red Teaming with AI? (25:58) Prompt injection in Multimodal Models (27:50) How Vulnerable are AI Models? (29:07) Is Prompt Injection the only real threat? (31:01) Predictions on how prompt injection will be stored or used (32:45) What’s changed in the Bug Bounty Toolkit? (35:35) How would internal red teams change? (36:53) What can enterprises do to protect themselves? (41:43) Where to start in this space? (47:53) What are our guests most excited about in AI? Resources Daniel's Webpage - Unsupervised Learning Joseph's Website
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51:24