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Cloud Security Podcast by Google

Anton Chuvakin
Cloud Security Podcast by Google
Latest episode

265 episodes

  • Cloud Security Podcast by Google

    EP263 SOC Refurbishing: Why New Tools Won't Fix Broken Processes (Even With AI)

    16/2/2026 | 32 mins.
    Guest:
    Daniel Lyman, VP of Threat Detection and Response, Fiserv
    Topics:
    What is the right way for people to bridge the gap and translate executive dreams and board goals into the reality of life on the ground?
    How do we talk to people who think they have "transformed" their SOC simply by buying a better, shinier product (like a modern SIEM) while leaving their old processes intact?
    What are the specific challenges and advantages you've seen with a federated SOC versus a centralized one? What does a "federated" or "sub-SOC" model actually mean in practice?
    Why is the message that "EDR doesn't cover everything" so hard for some people to hear? Is this obsession with EDR a business decision or technology debt?
    How do you expect AI to change the calculus around data centralization versus data federation?
    What is your favorite example of telemetry that is useful, but usually excluded from a SIEM?
    What are the Detection and Response organizational metrics that you think are most valuable?
    Is the continued use of Excel an issue of tooling, laziness, or just because it is a fundamentally good way to interact with a small database?
    Resources:
    Video version
    "In My Time of Dying" book
    EP258 Why Your Security Strategy Needs an Immune System, Not a Fortress with Royal Hansen
    EP197 SIEM (Decoupled or Not), and Security Data Lakes: A Google SecOps Perspective
    The Gravity of Process: Why New Tech Never Fixes Broken Process and Can AI Change It? blog
  • Cloud Security Podcast by Google

    EP262 Freedom, Responsibility, and the Federated Guardrails: A New Model for Modern Security

    09/2/2026 | 28 mins.
    Guest:
    Alex Shulman-Peleg, Global CISO at Kraken
     Topics:
    You mentioned that centralized security can't work anymore. Can you elaborate on the key changes—driven by cloud, SaaS, and AI—that have made this traditional model unsustainable for a modern organization?
    Why do some persist at centralized, top down approach to security, despite that?
    What do you mean by "Freedom, Responsibility and distributed security"? 
    Can you explain the difference between "centralized security" and what you define as "security with distributed ownership"?  Is this the same "federated"?
    In our conversation you mentioned "cloud and AI- native", what do you mean by this (especially "AI-native") and how is this changing your approach to security? 
    You introduce the concept of "Security as quality" suggesting that a security-unaware developer is essentially a bad software developer. How do you shift the culture and internal metrics to make security an inherent quality standard, rather than a separate, compliance-driven checklist?
    You likened the central security team's new role to a "911 emergency service." Beyond incident response, what stays central no matter what, and how does the central team successfully influence the security posture of the entire organization without being directly responsible for the day-to-day work.
    Resources:
    Video version
    EP129 How CISO Cloud Dreams and Realities Collide
    EP258 Why Your Security Strategy Needs an Immune System, Not a Fortress with Royal Hansen
    EP212 Securing the Cloud at Scale: Modern Bank CISO on Metrics, Challenges, and SecOps
  • Cloud Security Podcast by Google

    EP261 No More Aspiration: Scaling a Modern SOC with Real AI Agents

    02/2/2026 | 28 mins.
    Guest:
    Dennis Chow, Director of Detection Engineering at UKG

     Topics:
    We ended our season talking about the AI apocalypse. In your opinion, are we living in the world that the guests describe in their apocalypse paper? 
    Do you think AI-powered attacks are really here, and if so, what is your plan to respond? Is it faster patching? Better D&R? Something else altogether? 
    Your team has a hybrid agent workflow: could you tell us what that means?  Also, define "AI agent" please.
    What are your production use cases for AI and AI agents in your SOC?
    What are your overall SOC metrics and how does the agentic AI part play into that?
    It's one thing to ask a team "hey what did y'all do last week" and get a good report - how are you measuring the agentic parts of your SOC?
    How are you thinking about what comes next once AI is automatically writing good (!) rules for your team out of research blog posts and TI papers? 
    Resources:
    Video version
    Agentic AI in the SOC: Build vs Buy Lessons
    EP255 Separating Hype from Hazard: The Truth About Autonomous AI Hacking
    EP256 Rewiring Democracy & Hacking Trust: Bruce Schneier on the AI Offense-Defense Balance
    EP252 The Agentic SOC Reality: Governing AI Agents, Data Fidelity, and Measuring Success
    EP236 Accelerated SIEM Journey: A SOC Leader's Playbook for Modernization and AI
    EP242 The AI SOC: Is This The Automation We've Been Waiting For?
    Google Cloud Skill Boost
  • Cloud Security Podcast by Google

    EP260 The Agentic IAM Trainwreck: Why Your Bots Need Better Permissions Than Your Admins

    26/1/2026 | 30 mins.
    Guest:
    Vishwas Manral, CEO at Precize.ai
    Topic:
    Why is agent security so different from "just" LLM security?
    Why now? Agents are coming, sure, but they are - to put it mildly - not in wide use. Why create a top 10 list now and not wait for people to make the mistakes?
    It sounds like "agents + IAM" is a disaster waiting to happen. What should be our approach for solving this? Do we have one?
    Which one agentic AI risk keeps you up at night? 
    Is there an interesting AI shared responsibility angle here? Agent developer, operator, downstream system operator?
    We are having a lot of experimentation, but sometimes little value from Agents. What are the biggest challenges of secure agentic AI and AI agents adoption in enterprises?
    Resources:
    Top 10 threats and mitigation for AI Agents
    Past podcast AI episodes
    Cloud CISO Perspectives: How Google secures AI Agents (and paper)
    Top AI Risks from SAIF
    CoSAI
    From turnkey to custom: Tailor your AI risk governance to help build confidence
  • Cloud Security Podcast by Google

    EP259 Why DeepMind Built a Security LLM Sec-Gemini and How It Beats the Generalists

    19/1/2026 | 33 mins.
    Guest:
    Elie Burstein,  Distinguished Scientist, Google Deepmind
    Topics: 
    What is Sec-Gemini, why are we building it?
    How does DeepMind decide when to create something like Sec-Gemini? 
    What motivates a decision to focus on something like this vs anything else we might build as a dedicated set of regular Gemini capabilities? 
    What is Sec-Gemini good at? How do we know it's good at those things? 
    Where and how is it better than a general LLM?
    Are we using Sec-Gemini internally?
     Resources:
    Video version
    EP238 Google Lessons for Using AI Agents for Securing Our Enterprise
    EP255 Separating Hype from Hazard: The Truth About Autonomous AI Hacking
    EP168 Beyond Regular LLMs: How SecLM Enhances Security and What Teams Can Do With It
    EP171 GenAI in the Wrong Hands: Unmasking the Threat of Malicious AI and Defending Against the Dark Side
    Big Sleep, CodeMender blogs

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About Cloud Security Podcast by Google

Cloud Security Podcast by Google focuses on security in the cloud, delivering security from the cloud, and all things at the intersection of security and cloud. Of course, we will also cover what we are doing in Google Cloud to help keep our users' data safe and workloads secure. We're going to do our best to avoid security theater, and cut to the heart of real security questions and issues. Expect us to question threat models and ask if something is done for the data subject's benefit or just for organizational benefit. We hope you'll join us if you're interested in where technology overlaps with process and bumps up against organizational design. We're hoping to attract listeners who are happy to hear conventional wisdom questioned, and who are curious about what lessons we can and can't keep as the world moves from on-premises computing to cloud computing.
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