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  • EP199 Your Cloud IAM Top Pet Peeves (and How to Fix Them)
    2024/11/18

    Guests:

    • Michele Chubirka, Staff Cloud Security Advocate, Google Cloud
    • Sita Lakshmi Sangameswaran, Senior Developer Relations Engineer, Google Cloud

    Topics:

    • What is your reaction to “in the cloud you are one IAM mistake away from a breach”? Do you like it or do you hate it? Or do you "it depends" it? :-)
    • Everyone's talking about how "identity is the new perimeter" in the cloud. Can you break that down in simple terms?
    • A lot of people say “in the cloud, you must do IAM ‘right’”. What do you think that means? What is the first or the main idea that comes to your mind when you hear it?
    • What’s this stuff about least-privilege and separation-of-duties being less relevant? Why do they matter in the cloud that changes rapidly?
    • What are your IAM Top Pet Peeves?

    Resources:

    • Video (LinkedIn, YouTube)
    • EP127 Is IAM Really Fun and How to Stay Ahead of the Curve in Cloud IAM?
    • EP162 IAM in the Cloud: What it Means to Do It 'Right' with Kat Traxler
    • IAM: There and back again using resource hierarchies
    • IAM so lost: A guide to identity in Google Cloud
    • I Hate IAM: but I need it desperately
    • EP33 Cloud Migrations: Security Perspectives from The Field
    • EP176 Google on Google Cloud: How Google Secures Its Own Cloud Use
    • EP177 Cloud Incident Confessions: Top 5 Mistakes Leading to Breaches from Mandiant
    • EP188 Beyond the Buzzwords: Identity's True Role in Cloud and SaaS Security
    • “Identity Crisis: The Biggest Prize in Security” paper
    • “Learn to love IAM: The most important step in securing your cloud infrastructure“ Next presentation
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    29 分
  • EP198 GenAI Security: Unseen Attack Surfaces & AI Pentesting Lessons
    2024/11/11

    Guests:

    • Ante Gojsalic, Co-Founder & CTO at SplxAI

    Topics:

    • What are some of the unique challenges in securing GenAI applications compared to traditional apps?
    • What current attack surfaces are most concerning for GenAI apps, and how do you see these evolving in the future?
    • Do you have your very own list of top 5 GenAI threats? Everybody seem to!
    • What are the most common security mistakes you see clients make with GenAI?
    • Can you explain the main goals when trying to add automation to pentesting for next-gen GenAI apps?
    • What are your AI testing lessons from clients so far?

    Resources:

    • EP171 GenAI in the Wrong Hands: Unmasking the Threat of Malicious AI and Defending Against the Dark Side
    • EP135 AI and Security: The Good, the Bad, and the Magical
    • EP185 SAIF-powered Collaboration to Secure AI: CoSAI and Why It Matters to You
    • SAIF.google
    • Next SAIF presentation with top 5 AI security issues
    • Our Security of AI Papers and Blogs Explained

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    27 分
  • EP197 SIEM (Decoupled or Not), and Security Data Lakes: A Google SecOps Perspective
    2024/11/04

    Guest:

    • Travis Lanham, Uber Tech Lead (UTL) for Security Operations Engineering, Google Cloud

    Topics:

    • There’s been a ton of discussion in the wake of the three SIEM week about the future of SIEM-like products. We saw a lot of takes on how this augurs the future of disassembled or decoupled SIEMs. Can you explain what these disassembled SIEMs are all about?
    • What are the expected upsides of detaching your SIEM interface and security capabilities from your data backend?
    • Tell us about the early days of SecOps (nee Chronicle) and why we didn’t go with this approach?
    • What are the upsides of a tightly coupled datastore + security experience for a SIEM?
    • Are there more risks or negatives of the decoupled/decentralized approach? Complexity and the need to assemble “at home” are on the list, right?
    • One of the 50 things Google knew to be true back in the day was that product innovation comes from technical innovation, what’s the technical innovation driving decoupled SIEMs?
    • So what about those security data lakes? Any insights?

    Resources:

    • EP139 What is Chronicle? Beyond XDR and into the Next Generation of Security Operations
    • EP190 Unraveling the Security Data Fabric: Need, Benefits, and Futures
    • EP184 One Week SIEM Migration: Fact or Fiction?
    • Hacking Google video series
    • Decoupled SIEM: Brilliant or …. Not :-)
    • UNC5537 Targets Snowflake Customer Instances for Data Theft and Extortion
    • So, Why Did I Join Chronicle Security? (2019)
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    30 分
  • EP196 AI+TI: What Happens When Two Intelligences Meet?
    2024/10/28

    Guest:

    • Vijay Ganti, Director of Product Management, Google Cloud Security

    Topics:

    • What have been the biggest pain points for organizations trying to use threat intelligence (TI)?
    • Why has it been so difficult to convert threat knowledge into effective security measures in the past?
    • In the realm of AI, there's often hype (and people who assume “it’s all hype”). What's genuinely different about AI now, particularly in the context of threat intelligence?
    • Can you explain the concept of "AI-driven operationalization" in Google TI? How does it work in practice?
    • What's the balance between human expertise and AI in the TI process? Are there specific areas where you see the balance between human and AI involvement shifting in a few years?
    • Google Threat Intelligence aims to be different. Why are we better from client PoV?

    Resources:

    • Google Threat Intel website
    • “Future of Brain” book by Gary Marcus et al
    • Detection engineering blog (Part 9) and the series
    • Detect engineering blogs by David French
    • The pyramid of pain blog, the classic
    • “Scaling Up Malware Analysis with Gemini 1.5 Flash” and “From Assistant to Analyst: The Power of Gemini 1.5 Pro for Malware Analysis” blogs on Gemini for security
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    28 分
  • EP195 Containers vs. VMs: The Security Showdown!
    2024/10/21

    Cross-over hosts:

    • Kaslin Fields, co-host at Kubernetes Podcast

    • Abdel Sghiouar, co-host at Kubernetes Podcast

    Guest:

    • Michele Chubirka, Cloud Security Advocate, Google Cloud

    Topics:

    • How would you approach answering the question ”what is more secure, container or a virtual machine (VM)?”
    • Could you elaborate on the real-world implications of this for security, and perhaps provide some examples of when one might be a more suitable choice than the other?
    • While containers boast a smaller attack surface (what about the orchestrator though?), VMs present a full operating system. How should organizations weigh these factors against each other?
    • The speed of patching and updates is a clear advantage of containers. How significant is this in the context of today's rapidly evolving threat landscape? Are there any strategies organizations can employ to mitigate the slower update cycles associated with VMs?
    • Both containers and VMs can be susceptible to misconfigurations, but container orchestration systems introduce another layer of complexity. How can organizations address this complexity and minimize the risk of misconfigurations leading to security vulnerabilities?
    • What about combining containers and VMs. Can you provide some concrete examples of how this might be implemented? What benefits can organizations expect from such an approach, and what challenges might they face?
    • How do you envision the security landscape for containers and VMs evolving in the coming years? Are there any emerging trends or technologies that could significantly impact the way we approach security for these two technologies?

    Resources:

    • Container Security, with Michele Chubrika (the same episode - with extras! - at our peer podcast, “Kubernetes Podcast from Google”)
    • EP105 Security Architect View: Cloud Migration Successes, Failures and Lessons
    • EP54 Container Security: The Past or The Future?
    • DORA 2024 report
    • Container Security: It’s All About the Supply Chain - Michele Chubirka
    • Software composition analysis (SCA)
    • DevSecOps Decisioning Principles
    • Kubernetes CIS Benchmark
    • Cloud-Native Consumption Principles
    • State of WebAssembly outside the Browser - Abdel Sghiouar
    • Why Perfect Compliance Is the Enemy of Good Kubernetes Security - Michele Chubirka - KubeCon NA 2024

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    41 分
  • EP194 Deep Dive into ADR - Application Detection and Response
    2024/10/14

    Guest:

    • Daniel Shechter, Co-Founder and CEO at Miggo Security

    Topics:

    • Why do we need Application Detection and Response (ADR)? BTW, how do you define it?
    • Isn’t ADR a subset of CDR (for cloud)? What is the key difference that sets ADR apart from traditional EDR and CDR tools?
    • Why can’t I just send my application data - or eBPF traces - to my SIEM and achieve the goals of ADR that way?
    • We had RASP and it failed due to instrumentation complexities. How does an ADR solution address these challenges and make it easier for security teams to adopt and implement?
    • What are the key inputs into an ADR tool?
    • Can you explain how your ADR correlates cloud, container, and application contexts to provide a better view of threats? Could you share real-world examples of types of badness solved for users?
    • How would ADR work with other application security technologies like DAST/SAST, WAF and ASPM?
    • What are your thoughts on the evolution of ADR?

    Resources:

    • EP157 Decoding CDR & CIRA: What Happens When SecOps Meets Cloud
    • EP143 Cloud Security Remediation: The Biggest Headache?
    • Miggo research re: vulnerability ALBeast
    • “WhatDR or What Detection Domain Needs Its Own Tools?” blog
    • “Making Sense of the Application Security Product Market” blog
    • “Effective Vulnerability Management: Managing Risk in the Vulnerable Digital Ecosystem“ book
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    31 分
  • EP193 Inherited a Cloud? Now What? How Do I Secure It?
    2024/10/07

    Guests:

    • Taylor Lehmann, Director at Office of the CISO, Google Cloud
    • Luis Urena, Cloud Security Architect, Google Cloud

    Topics

    • There is a common scenario where security teams are brought in after a cloud environment is already established. From your experience, how does this late involvement typically impact the organization's security posture and what are the immediate risks they face?
    • Upon hearing this, many experts suggest that “burn the environment with fire” or “nuke it from orbit” are the only feasible approaches? What is your take on that suggestion?
    • On the opposite side, what if business demands you don't touch anything but “make it secure” regardless?
    • Could you walk us through some of the first critical steps you do after “inheriting a cloud” and why they are prioritized in this way?
    • Why not just say “add MFA everywhere”? What may or will blow up?
    • We also say “address overly permissive users and roles” and this sounds valuable, but also tricky. How do we go about it?
    • What are the chances that the environment is in fact compromised already? When is Compromise Assessment the right call, it does cost money, right?
    • How do you balance your team’s current priorities when you’ve just adopted an insecure cloud environment. How do you make tradeoffs among your existing stack and this new one?

    Resources:

    • “Confetti cannons or fire extinguishers? Here’s how to secure cloud surprises”
    • EP179 Teamwork Under Stress: Expedition Behavior in Cybersecurity Incident Response
    • IAM Recommender
    • “TM" book by Adam Shostack
    • “Checklist Manifesto” book
    • “Moving shields into position: How you can organize security to boost digital transformation” (with a new paper!)
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    31 分
  • EP192 Confidential + AI: Can AI Keep a Secret?
    2024/09/30

    Guest:

    • Nelly Porter, Director of PM, Cloud Security at Google Cloud

    Topics:

    • Share your story and how you ended here doing confidential AI at Google?
    • What problem does confidential compute + AI solve and for what clients?
    • What are some specific real-world applications or use cases where you see the combination of AI and confidential computing making the most significant impact?
    • What about AI in confidential vs AI on prem? Should those people just do on-prem AI instead?
    • Which parts of the AI lifecycle need to be run in Confidential AI: Training? Data curation? Operational workloads?
    • What are the performance (and thus cost) implications of running AI workloads in a confidential computing environment?
    • Are there new risks that arise out of confidential AI?

    Resources:

    • Video
    • EP48 Confidentially Speaking 2: Cloudful of Secrets
    • EP1 Confidentially Speaking
    • “To securely build AI on Google Cloud, follow these best practices“ blog (paper)
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    33 分