AI Security Podcast

Kaizenteq Team

The #1 source for AI Security insights for CISOs and cybersecurity leaders. Hosted by two former CISOs, the AI Security Podcast provides expert, no-fluff discussions on the security of AI systems and the use of AI in Cybersecurity. Whether you're a CISO, security architect, engineer, or cyber leader, you'll find practical strategies, emerging risk analysis, and real-world implementations without the marketing noise. These conversations are helping cybersecurity leaders make informed decisions and lead with confidence in the age of AI.

  1. 9 SEPT.

    The Future of AI Security is Scaffolding, Agents & The Browser

    Welcome to the 2025 State of AI Security. This year, the conversation has moved beyond simple prompt injection to a far more complex threat: attacking the entire ecosystem surrounding the LLM. In this deep-dive discussion, offensive security experts Jason Haddix (Arcanum Information Security) and Daniel Miessler (Unsupervised Learning) break down the real-world attack vectors they're seeing in the wild. The conversation explores why prompt injection remains an unsolved problem and how the LLM is now being used as a delivery system to attack internal developers and connected applications. We also tackle the critical challenge of incident response, questioning how you can detect or investigate a malicious prompt when privacy regulations in some regions prevent logging and observability. This episode is a must-listen for anyone looking to understand the true offensive and defensive landscape of AI security, from the DARPA Cyber Challenge to the race for AI to control the browser. Questions asked: (00:00) Introduction(02:22) Who are Jason Haddix & Daniel Miessler?(03:40) The State of AI Security in 2025(06:20) It's All About the "Scaffolding", Not Just the Model(08:30) Why Prompt Injection is a Fundamental, Unsolved Problem(10:45) "Attacking the Ecosystem": Using the LLM as a Delivery System(12:45) The New Enterprise Protocol: Prompts in English(15:10) The Incident Response Dilemma: How Do You Detect Malicious Prompts?(16:50) The Challenge of Logging: When Privacy Laws Block Observability(21:30) Has Data Poisoning Become a Major Threat?(27:20) How Far Can Autonomous AI Go in Hacking Today?(28:30) An Inside Look at the DARPA AI Cyber Challenge (AIxCC)(40:45) Are Attackers Actually Using AI in the Wild?(47:30) The Evolution of the "Script Kitty" in the Age of AI(51:00) Would AGI Solve Security? The Problem of Politics & Context(59:15) Context is King: Why Prompt Engineering is a Critical Skill(01:03:30) What are the Best LLMs for Security & Productivity?(01:05:40) The Next Frontier: Why AI is Racing to Own the Browser(01:20:20) Does Using AI to Write Content Erode Trust?

    1 h 25 min

  2. 22 AOÛT

    A CISO's Blueprint for AI Security (From ML to GenAI)

    Is the current AI hype cycle different from the ones that failed before? How do you build a security program for technology that can't give the same answer twice? This episode features a deep-dive conversation with Damian Hasse, CISO of Moveworks and a security veteran from Amazon's Alexa team, VMware, and Microsoft. Damian provides a practical blueprint for securing both traditional Machine Learning (ML) and modern Generative AI (GenAI). We discuss the common pitfalls of newly formed AI Councils, where members may lack the necessary ML background to make informed decisions. He shares his framework for assessing AI risk by focusing on the specific use case, the data involved, and building a multi-layered defense against threats like prompt injection and data leakage. This is an essential guide for any security leader or practitioner tasked with navigating the complexities of AI security, from protecting intellectual property in AI-assisted coding to implementing safeguards for enterprise chatbots. Questions asked: (00:00) Introduction(02:31) Who is Damian Hasse? CISO at Moveworks(04:00) AI Security: The Difference Between the Pre-GPT and Post-GPT Eras(06:00) The Problem with New AI Councils Lacking ML Expertise(07:50) A History of AI: The Hype Cycles and Winters Since the 1950s(16:20) Is This AI Hype Cycle Different? The Power of Accessibility(20:25) Securing AI-Assisted Coding: IP Risks, Data Leakage, and Poisoned Models(23:30) The Threat of Indirect Prompt Injection in Open Source Packages(26:20) Are You Asking Your AI the Right Questions? The Power of "What Am I Missing?"(40:20) A CISO's Framework for Securing New AI Features(44:30) Building Practical Safeguards for Enterprise Chatbots(47:25) The Biggest Challenge in Real-Time AI Security: Performance(50:00) Why Access Control in AI is a Deterministic Problem Resources spoken about during the interview Tracing the thoughts of a large language model

    52 min

  3. 31 JUILL.

    Gen AI Threat Modeling vs. AI-Powered Defense:

    Is generative AI a security team's greatest new weapon or its biggest new vulnerability? This episode dives headfirst into the debate with two leading experts on opposite sides of the AI dragon. We 1st published this episode on Cloud Security Podcast and because of the feedback we received from those diving into all things AI Security, we wanted to bring it to those who haven't probably had the chance to hear it yet on this podcast. On one side, discover how to leverage and "tame" AI for your defense. Jackie Bow explains how Anthropic uses its own powerful LLM, Claude, to revolutionize threat detection and response. Learn how AI can be used to: Build investigation and triage tools with incredible speed. Break free from the "black box" of traditional security tools, offering more visibility and control. Creatively "hallucinate" within set boundaries to uncover investigative paths a human might miss. Lower the barrier to entry for security professionals, enabling them to build prototypes and tools without deep coding expertise. On the other side, Kane Narraway provides a masterclass in threat modeling the new landscape of AI systems. He argues that while AI introduces new challenges, many are amplifications of existing SaaS risks. This conversation covers the critical aspects of securing AI, including: Why access, integrations, and authorization are the biggest risk factors in enterprise AI. How to approach threat modeling for both in-house and third-party AI tools. The security challenges of emerging standards like MCP (Meta-Controller Protocol) and the importance of securing the data AI tools can access. The critical need for security teams to adopt AI to keep pace with modern engineering departments. Questions asked: (00:00) Intro: Slaying or Training the AI Dragon at BSidesSF?(02:22) Meet Jackie Bow (Anthropic): Training AI for Security Defense(02:51) Meet Kane Narraway (Canva): Securing AI Systems & Facing Risks(03:49) Was Traditional Security Ops "Hot Garbage"? Setting the Scene(05:57) The Real Risks: What AI Brings to Your Organisation(06:53) AI in Action: Leveraging AI for Threat Detection & Response(07:46) AI Hallucinations: Bug, Feature, or Security Blind Spot?(08:55) Threat Modeling AI: The Core Challenges & Learnings(12:26) Getting Started: Practical AI Threat Detection First Steps(16:42) AI & Cloud: Integrating AI into Your Existing Environments(25:21) AI vs. Traditional: Is Threat Modeling Different Now?(28:34) Your First Step: Where to Begin with AI Threat Modeling?(31:59) Fun Questions & Final Thoughts on the Future of AI Security Resources BSidesSF 2025 - AI's Bitter Lesson for SOCs: Let Machines Be MachinesBSidesSF 2025 - One Search To Rule Them All: Threat Modelling AI Search

    36 min

  4. 27 JUIN

    Vibe Coding for CISOs: Managing Risk & Opportunity in AI Development

    What happens when your product, sales, and marketing teams can build and deploy their own applications in a matter of hours? This is the new reality of "Vibe Coding," and for CISOs, it represents both a massive opportunity for innovation and a significant governance challenge. In this episode, join Ashish Rajan and Caleb Sima as they move beyond the hype to provide a strategic playbook for security leaders navigating the world of AI-assisted development. Learn how Vibe Coding empowers non-engineers to solve business problems and how you can leverage it to rapidly prototype security solutions yourself. Get strategies to handle the inevitable influx of AI-generated applications from across the business without overwhelming your engineering and security teams. Understanding the Core OpportunityAssessing the Real-World OutputManaging the "Shadow Prototype" RiskBuilding Proactive GuardrailsArchitecting for Safety For more episodes like this go to www.aisecuritypodcast.com Questions asked: (00:00) Why Vibe Coding is a C-Suite Issue (02:34) The Strategic Advantage of Hands-On AI (04:20) Your AI Development Toolkit: Where to Start (12:08 Choosing Your First Project: A Framework for Success (16:46) The CISO as an AI Engineering Manager: A Step-by-Step Workflow (31:32) A Surprising Security Finding: AI and Least Privilege (36:47) Augmenting AI with Agents and Live Data (38:50) Beyond Code: AI Agents for Business Automation (Zapier, etc.) (43:30) The "Production Ready" Problem: Who Owns the Code? (53:25) A CISO's Playbook for Governing AI Development Resources spoken about during the episode: AI Native Landscape - Tools Cline Roo-Code Visual Studio Code Windsurf Bolt.new Aider v0 - Vercel Lovable Claude Code ChatGPT

    1 h

  5. 12 JUIN

    Vibe Coding, Slopsquatting, and the Future of AI in Software Development

    In this episode, we welcome back Guy Podjarny, founder of Snyk and Tessl, to explore the evolution of AI-assisted coding. We dive deep into the three chapters of AI's impact on software development, from coding assistants to the rise of "vibe coding" and agentic development. Guy explains what "vibe coding" truly is, a term coined by Andrej Karpathy where developers delegate more control to AI, sometimes without even reviewing the code. We discuss how this opens the door for non-coders to create real applications but also introduces significant risks. Caleb, Ashish and Guy discuss: The Three Chapters of AI-Assisted Coding: The journey from simple code completion to full AI agent-driven development.Vibe Coding Explained: What is it, who is using it, and why it's best for "disposable apps" like prototypes or weekend projects.A New Security Threat - Slopsquatting: Discover how LLMs can invent fake library names that attackers can exploit, a risk potentially greater than typosquatting.The Future of Development: Why the focus is shifting from the code itself—which may become disposable—to the importance of detailed requirements and rigorous testing.The Developer as a Manager: How the role of an engineer is evolving into managing AI labor, defining specifications, and overseeing workflows Questions asked: (00:00) The Evolution of AI Coding Assistants(05:55) What is Vibe Coding?(08:45) The Dangers & Opportunities of Vibe Coding(11:50) From Vibe Coding to Enterprise-Ready AI Agents(16:25) Security Risk: What is "Slopsquatting"?(22:20) Are Old Security Problems Just Getting Bigger?(25:45) Cloud Sprawl vs. App Sprawl: The New Enterprise Challenge(33:50) The Future: Disposable Code, Permanent Requirements(40:20) Why AI Models Are Getting So Good at Understanding Your Codebase(44:50) The New Role of the AI-Native Developer: Spec & Workflow Manager(46:55) Final Thoughts & Favorite Coding Tools Resources spoken about during the episode: AI Native Dev Community Tessl Cursor Bolt BASE44 Vercel

    49 min

  6. 6 JUIN

    AI in Cybersecurity: Phil Venables (Formerly Google Cloud CISO) on Agentic AI & CISO Strategy

    Dive deep into the evolving landscape of AI in Cybersecurity with Phil Venables, former Chief Information Security Officer at Google Cloud and a cybersecurity veteran with over 30 years of experience. Recorded at RSA, this episode explores the critical shifts and future trends shaping our industry. Caleb, Ashish and Phil speak about The journey from predictive AI to the forefront of Agentic AI in enterprise environments.How organizations are transitioning AI from experimental prototypes to impactful production applications.The three essential pillars of AI control for CISOs: software lifecycle risk, data governance, and operational risk management.Current adversarial uses of AI and the surprising realities versus the hype.Leveraging AI to combat workforce skill shortages and boost productivity within security teams.The rise of "Vibe Coding" and how AI is transforming software development and security.The expanding role of the CISO towards becoming a Chief Digital Risk Officer.Practical advice for security teams on adopting AI for security operations automation and beyond. Questions asked: (00:00) - Intro: AI's Future in Cybersecurity with Phil Venables (00:55) - Meet Phil Venables: Ex-Google Cloud CISO & Cyber Veteran (02:59) - AI Security Now: Navigating Predictive, Generative & Agentic AI (04:44) - AI: Beyond the Hype? Real Enterprise Adoption & Value (05:49) - Top CISO Concerns: Securing AI in Production Environments (07:02) - AI Security for All: Advice for Smaller Organizations (Hint: Platforms!) (09:04) - CISOs' AI Worries: Data Leakage, Prompt Injection & Deepfakes? (12:53) - AI Maturity: Beyond Terminator Fears to Practical Guardrails (14:45) - Agentic AI in Action: Real-World Enterprise Deployments & Use Cases (15:56) - Securing Agentic AI: Building Guardrails & Control Planes (Early Days) (22:57) - Future-Proof Your Security Program for AI: Key Considerations (25:13) - LLM Strategy: Single vs. Multiple Models for AI Applications (28:26) - "Vibe Coding": How AI is Revolutionizing Software Development for Leaders (32:21) - Security Implications of AI-Generated Code & "Shift Downward" (37:22) - Frontier Models & Shared Responsibility: Who Secures What? (39:07) - AI Adoption Hotbeds: Which Security Teams Are Leading the Way? (SecOps First!) (40:20) - AI App Sprawl: Managing Risk in a World of Custom, AI-Generated Apps

    45 min

  7. 29 MAI

    Is Your Browser the Biggest AI Security Risk?

    Are you overlooking the most critical piece of real estate in your enterprise security strategy, especially with the rise of AI? With 90% or more of employee work happening inside a browser, it's becoming the new operating system and the primary entry point for AI agents. In this episode, Ashish and Caleb dive deep into the world of Enterprise Browsers. They explore why this often-underestimated technology is set to disrupt how AI agents operate and why it should be top-of-mind for every security leader. Join us as we cover: What are Enterprise Browsers? Understanding these Chromium-based, standalone browsers.Who are the Key Players? A look at companies like Island Security and Talon Security (now Palo Alto).Why Now? How browsers became the de facto OS and the prime spot for AI integration.The Power of Control: Exploring benefits like built-in DLP (Data Loss Prevention), Zero Trust capabilities, policy enforcement, and BYOD enablement.Beyond Security: How enterprise browsers can inject features and modify permissions without backend dev work.AI Agents in Action: How AI will leverage browsers for automation and the security challenges this presents.The Future Outlook: Predictions for AI-enabled browsers and the coming wave of browser-focused AI security startups.Whether you're skeptical or already exploring browser security, this conversation offers valuable insights into managing AI agents and securing your organization in an increasingly browser-centric, AI-driven world. Questions asked: (00:00) Intro: Why Enterprise Browsers are Crucial for AI Agents(01:50) Why Discuss Enterprise Browsers on an AI Cybersecurity Podcast?(02:20) The Browser is the New OS: 99% of Time Spent (03:00) AI Agents' Easiest Entry Point: The Browser (03:30) Example: How an AI Agent Automates Tasks via Browser (04:30) The Scope: Intranet, SaaS, and 60% of Employee Activity (06:50) OpenAI's Operator Demo & Browser Emulation (07:45) Overview: What are Enterprise Browsers? (Vendors & Purpose) (08:50) Key Players: Talon (Palo Alto) & Island Security (09:30) Benefit 1: Built-in DLP & Visibility (10:10) Benefit 2: Zero Trust Capabilities (10:40) Benefit 3: Policy, Compliance & Password Management (11:00) Use Case: BYOD & Contractors (Replacing Virtual Desktops?) (13:10) Why Not Firefox or Edge? The Power of Chromium (16:00) Budgeting Challenge: Why Browser Security is Often Overlooked (17:00) The Rise of AI Browser Plugins & Startups (19:30) The Hidden Risk: Existing Chrome Plugin Dangers (23:45) Why Did OpenAI Want to Buy Chrome? (25:00) Devil's Advocate: Can Enterprise Browsers Stop OWASP Top 10? (27:06) Example: AI Agent Ordering Flowers via Browser Extension (29:00) How AI Agents Gain Power via Browser Extensions (30:15) Prediction: What AI Browser Security Startups will look like at RSA 2026? (31:30) Skepticism: Will Enterprises Really Fund Browser Security? (SSPM Lessons) (34:00) The #1 Benefit You Don't Know: Injecting Features Without Code! (34:45) Example: Masking PII & Adding 2FA via Enterprise Browser (38:15) Monitoring AI Agents: Browser as a "Man-in-the-Middle" (40:00) The "AI Version of Chrome": A Future Consumer Product? (42:15) Personal vs. Professional: The Blurring Lines in Browser Use (44:15) Final Predictions & The Cybersecurity Gap (45:00) Final Thoughts & Wrap Up

    46 min

  8. 16 MAI

    AI Red Teaming & Securing Enterprise AI

    As AI systems become more integrated into enterprise operations, understanding how to test their security effectively is paramount. In this episode, we're joined by Leonard Tang, Co-founder and CEO of Haize Labs, to explore how AI red teaming is changing. Leonard discusses the fundamental shifts in red teaming methodologies brought about by AI, common vulnerabilities he's observing in enterprise AI applications, and the emerging risks associated with multimodal AI (like voice and image processing systems). We delve into the intricacies of achieving precise output control for crafting sophisticated AI exploits, the challenges enterprises face in ensuring AI safety and reliability, and practical mitigation strategies they can implement. Leonard shares his perspective on the future of AI red teaming, including the critical skills cybersecurity professionals will need to develop, the potential for fingerprinting AI models, and the ongoing discussion around protocols like MCP. Questions asked: 00:00 Intro: AI Red Teaming's Evolution01:50 Leonard Tang: Haize Labs & AI Expertise05:06 AI vs. Traditional Red Teaming (Enterprise View)06:18 AI Quality Assurance: The Haize Labs Perspective08:50 AI Red Teaming: Real-World Application Examples10:43 Major AI Risk: Multimodal Vulnerabilities Explained11:50 AI Exploit Example: Voice Injections via Background Noise15:41 AI Vulnerabilities & Early XSS: A Cybersecurity Analogy20:10 Expert AI Hacking: Precisely Controlling AI Output for Exploits21:45 The AI Fingerprinting Challenge: Identifying Chained Models25:48 Fingerprinting LLMs: The Reality & Detection Difficulty29:50 Top Enterprise AI Security Concerns: Reputation & Policy34:08 Enterprise AI: Model Choices (Frontier Labs vs. Open Source)34:55 Future of LLMs: Specialized Models & "Hot Swap" AI37:43 MCP for AI: Enterprise Ready or Still Too Early?44:50 AI Security: Mitigation with Precise Input/Output Classifiers49:50 Future Skills for AI Red Teamers: Discrete Optimization Resources discussed during the episode: Baselines for Watermarking Large Language Models Haize Labs

    53 min
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À propos

The #1 source for AI Security insights for CISOs and cybersecurity leaders. Hosted by two former CISOs, the AI Security Podcast provides expert, no-fluff discussions on the security of AI systems and the use of AI in Cybersecurity. Whether you're a CISO, security architect, engineer, or cyber leader, you'll find practical strategies, emerging risk analysis, and real-world implementations without the marketing noise. These conversations are helping cybersecurity leaders make informed decisions and lead with confidence in the age of AI.

Informations

  • Créateur
    Kaizenteq Team
  • Années d’activité
    2023 - 2025
  • Épisodes
    35
  • Classement
    Tout public
  • Copyright
    © Kaizenteq Team
  • Site Web de l’émission
    AI Security Podcast

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