Cloud Security Podcast by Google

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**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.

Latest Episodes:

EP253 The Craft of Cloud Bug Hunting: Writing Winning Reports and Secrets from a VRP Champion Nov 24, 2025

Show notes

Guests:

Sivanesh Ashok, bug bounty hunter
Sreeram KL, bug bounty hunter

Topics:

We hear from the Cloud VRP team that you write excellent bugbounty reports - is there any advice you'd give to other researchers when they write reports?
You are one of Cloud VRP's top researchers and won the MVH (most valuable hacker) award at their event in June - what do you think makes you so successful at finding issues?
What is a Bugswat?
What do you find most enjoyable and least enjoyable about the VRP?
What is the single best piece of advice you'd give an aspiring cloud bug hunter today?

Resources:

EP252 The Agentic SOC Reality: Governing AI Agents, Data Fidelity, and Measuring Success Nov 17, 2025

Show notes

Guests:

Alexander Pabst, Deputy Group CISO, Allianz
Lars Koenig, Global Head of D&R, Allianz

Topics:

Moving from traditional SIEM to an agentic SOC model, especially in a heavily regulated insurer, is a massive undertaking. What did the collaboration model with your vendor look like?
Agentic AI introduces a new layer of risk - that of unconstrained or unintended autonomous action. In the context of Allianz, how did you establish the governance framework for the SOC alert triage agents?
Where did you draw the line between fully automated action and the mandatory "human-in-the-loop" for investigation or response?
Agentic triage is only as good as the data it analyzes. From your perspective, what were the biggest challenges - and wins - in ensuring the data fidelity, freshness, and completeness in your SIEM to fuel reliable agent decisions?
We've been talking about SOC automation for years, but this agentic wave feels different. As a deputy CISO, what was your primary, non-negotiable goal for the agent? Was it purely Mean Time to Respond (MTTR) reduction, or was the bigger strategic prize to fundamentally re-skill and uplevel your Tier 2/3 analysts by removing the low-value alert noise?
As you built this out, were there any surprises along the way that left you shaking your head or laughing at the unexpected AI behaviors?
We felt a major lack of proof - Anton kept asking for pudding - that any of the agentic SOC vendors we saw at RSA had actually achieved anything beyond hype! When it comes to your org, how are you measuring agent success? What are the key metrics you are using right now?

Resources:

EP251 Beyond Fancy Scripts: Can AI Red Teaming Find Truly Novel Attacks? Nov 10, 2025

Show notes

Guest:

Ari Herbert-Voss, CEO at RunSybil

Topics:

The market already has Breach and Attack Simulation (BAS), for testing known TTPs. You're calling this 'AI-powered' red teaming. Is this just a fancy LLM stringing together known attacks, or is there a genuine agent here that can discover a truly novel attack path that a human hasn't scripted for it?
Let's talk about the 'so what?' problem. Pentest reports are famous for becoming shelf-ware. How do you turn a complex AI finding into an actionable ticket for a developer, and more importantly, how do you help a CISO decide which of the thousand 'criticals' to actually fix first?
You're asking customers to unleash a 'hacker AI' in their production environment. That's terrifying. What are the 'do no harm' guardrails? How do you guarantee your AI won't accidentally rm -rf a critical server or cause a denial of service while it's 'exploring'?
You mentioned the AI is particularly good at finding authentication bugs. Why that specific category? What's the secret sauce there, and what's the reaction from customers when you show them those types of flaws?
Is this AI meant to replace a human red teamer, or make them better? Does it automate the boring stuff so experts can focus on creative business logic attacks, or is the ultimate goal to automate the entire red team function away?
So, is this just about finding holes, or are you closing the loop for the blue team? Can the attack paths your AI finds be automatically translated into high-fidelity detection rules? Is the end goal a continuous purple team engine that's constantly training our defenses?
Also, what about fixing? What makes your findings more fixable?
What will happen to red team testing in 2-3 years if this technology gets better?

Resource:

EP250 The End of "Collect Everything"? Moving from Centralization to Data Access? Nov 03, 2025

Show notes

Guest:

Balazs Scheidler, CEO at Axoflow, original founder of syslog-ng

Topics:

Are we really coming to "access to security data" and away from "centralizing the data"?
How to detect without the same storage for all logs?
Is data pipeline a part of SIEM or is it standalone? Will this just collapse into SIEM soon?
Tell us about the issues with log pipelines in the past?
What about enrichment? Why do it in a pipeline, and not in a SIEM?
We are unable to share enough practices between security teams. How are we fixing it? Is pipelines part of the answer?
Do you have a piece of advice for people who want to do more than save on their SIEM costs?

Resources:

EP249 Data First: What Really Makes Your SOC 'AI Ready'? Oct 27, 2025

Show notes

Guest:

Monzy Merza, co-founder and CEO at Crogl

Topics:

We often hear about the aspirational idea of an "IronMan suit" for the SOC—a system that empowers analysts to be faster and more effective. What does this ideal future of security operations look like from your perspective, and what are the primary obstacles preventing SOCs from achieving it today?
You've also raised a metaphor of AI in the SOC as a "Dr. Jekyll and Mr. Hyde" situation. Could you walk us through what you see as the "Jekyll"—the noble, beneficial promise of AI—and what are the factors that can turn it into the dangerous "Mr. Hyde"?
Let's drill down into the heart of the "Mr. Hyde" problem: the data. Many believe that AI can fix a team's messy data, but you've noted that "it's all about the data, duh." What's the story?
"AI ready SOC" - What is the foundational work a SOC needs to do to ensure their data is AI-ready, and what happens when they skip this step?
And is there anything we can do to use AI to help with this foundational problem?
How do we measure progress towards AI SOC? What gets better at what time? How would we know?
What SOC metrics will show improvement? Will anything get worse?

Resources:

EP248 Cloud IR Tabletop Wins: How to Stop Playing Security Theater and Start Practicing Oct 20, 2025

Show notes

Guest:

Jibran Ilyas, Director for Incident Response at Google Cloud

Topics:

What is this tabletop thing, please tell us about running a good security incident tabletop?
Why are tabletops for incident response preparedness so amazingly effective yet rarely done well?
This is cheap/easy/useful so why do so many fail to do it? Why are tabletops seen as kind of like elite pursuit?
What's your favorite Cloud-centric scenario for tabletop exercises? Ransomware? But there is little ransomware in the cloud, no?
What are other good cloud tabletop scenarios?

Resources:

EP247 The Evolving CISO: From Security Cop to Cloud & AI Champion Oct 13, 2025

Show notes

Guest:

David Gee, Board Risk Advisor, Non-Executive Director & Author, former CISO

Topics:

Drawing from the "Aspiring CIO and CISO" book's focus on continuous improvement, how have you seen the necessary skills, knowledge, experience, and behaviors for a CISO evolve, especially when guiding an organization through a transformation?
Could you share lessons learned about leadership and organizational resilience during such a critical period, and how does that experience reshape your approach to future transformations?
Many organizations are undergoing transformations, often heavily involving cloud technologies. From your perspective, what is the most crucial—and perhaps often overlooked—role a CISO plays in ensuring security is an enabler, not a roadblock, during such large-scale changes?
Have you ever seen a CISO who is a cloud champion for the organization?
Your best advice for a CISO meeting cloud for the first time?
What is your best advice for a CISO meeting AI for the first time?
How do you balance the continuous self-improvement and development with the day-to-day pressures and responsibilities?

Resources:

EP246 From Scanners to AI: 25 Years of Vulnerability Management with Qualys CEO Sumedh Thakar Oct 06, 2025

Show notes

Guest:

Sumedh Thakar, President and CEO, Qualys

Topics:

How did vulnerability management (VM) change since Qualys was founded in 1999? What is different about VM today?
Can we actually remediate vulnerabilities automatically at scale? Why did this work for you even though many expected it would not?
Where does cloud fit into modern vulnerability management?
How does AI help vulnerability management today? What is real?
What is this Risk Operations Center (ROC) concept and how it helps in vulnerability management?

Resources:

EP245 From Consumer Chatbots to Enterprise Guardrails: Securing Real AI Adoption Sep 29, 2025

Show notes

Guest:

Rick Caccia, CEO and Co-Founder, Witness AI

Topics:

In what ways is the current wave of enterprise AI adoption different from previous technology shifts? If we say "but it is different this time", then why?
What is your take on "consumer grade AI for business" vs enterprise AI?
A lot of this sounds a bit like the CASB era circa 2014. How is this different with AI?
The concept of "routing prompts for risk and cost management" is intriguing. Can you elaborate on the architecture and specific AI engines Witness AI uses to achieve this, especially for large global corporations?
What are you seeing in the identity space for AI access? Can you give us a rundown of the different tradeoffs teams are making when it comes to managing identities for agents?

Resources:

EP244 The Future of SOAPA: Jon Oltsik on Platform Consolidation vs. Best-of-Breed in the Age of Agentic AI Sep 22, 2025

Show notes

Guest:

Jon Oltsik, security researcher, ex-ESG analyst

Topics:

You invented the concept of SOAPA – Security Operations & Analytics Platform Architecture. As we look towards SOAPA 2025, how do you see the ongoing debate between consolidating security around a single platform versus a more disaggregated, best-of-breed approach playing out?
What are the key drivers for either strategy in today's complex environments? How can we have both "decoupling" and platformization going at the same time?
With all the buzz around Generative AI and Agentic AI, how do you envision these technologies changing the future of the Security Operations Center (and SOAPA of course)?
Where do you see AI really work today in the SOC and what is the proof of that actually happening? What does a realistic "AI SOC" look like in the next few years, and what are the practical implications for security teams?
"Integration" is always a hot topic in security - and it has been for decades. Within the context of SOAPA and the adoption of advanced analytics, where do you see the most critical integration challenges today – whether it's vendor-centric ecosystems, strategic partnerships, or the push for open standards?

Resources:

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