Cloud Security Podcast by Google

Anton Chuvakin

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. read less
TechnologyTechnology

Episodes

EP181 Detection Engineering Deep Dive: From Career Paths to Scaling SOC Teams
Yesterday
EP181 Detection Engineering Deep Dive: From Career Paths to Scaling SOC Teams
Guest: Zack Allen, Senior Director of Detection & Research @ Datadog, creator of Detection Engineering Weekly Topics: What are the biggest challenges facing detection engineers today? What do you tell people who want to consume detections and not engineer them? What advice would you give to someone who is interested in becoming a detection engineer at her organization? So, what IS a detection engineer? Do you need software skills to be one? How much breadth and depth do you need? What should a SOC leader whose team totally lacks such skills do? You created Detection Engineering Weekly. What motivated you to start this publication, and what are your goals for it? What are the learnings so far? You work for a vendor, so how should customers think of vendor-made vs customer-made detections and their balance?  What goes into a backlog for detections and how do you inform it? Resources: Video (LinkedIn, YouTube) Zacks’s newsletter: https://detectionengineering.net  EP75 How We Scale Detection and Response at Google: Automation, Metrics, Toil EP117 Can a Small Team Adopt an Engineering-Centric Approach to Cybersecurity? The SRE book “Detection Spectrum” blog “Delivering Security at Scale: From Artisanal to Industrial” blog (and this too) “Detection Engineering is Painful — and It Shouldn’t Be (Part 1)” blog series “Detection as Code? No, Detection as COOKING!” blog “Practical Threat Detection Engineering: A hands-on guide to planning, developing, and validating detection capabilities” book SpecterOps blog
EP180 SOC Crossroads: Optimization vs Transformation - Two Paths for Security Operations Center
Jul 8 2024
EP180 SOC Crossroads: Optimization vs Transformation - Two Paths for Security Operations Center
Guests: Mitchell Rudoll, Specialist Master, Deloitte Alex Glowacki, Senior Consultant, Deloitte Topics: The paper outlines two paths for SOCs: optimization or transformation. Can you elaborate on the key differences between these two approaches and the factors that should influence an organization's decision on which path to pursue?  The paper also mentions that alert overload is still a major challenge for SOCs. What are some of the practices that work in 2024 for reducing alert fatigue and improving the signal-to-noise ratio in security signals? You also discuss the importance of automation for SOCs. What are some of the key areas where automation can be most beneficial, and what are some of the challenges of implementing automation in SOCs? Automation is often easier said than done… What specific skills and knowledge will be most important for SOC analysts in the future that people didn’t think of 5-10 years ago? Looking ahead, what are your predictions for the future of SOCs? What emerging technologies do you see having the biggest impact on how SOCs operate?  Resources: “Future of the SOC: Evolution or Optimization —Choose Your Path” paper and highlights blog “Meet the Ghost of SecOps Future” video based on the paper EP58 SOC is Not Dead: How to Grow and Develop Your SOC for Cloud and Beyond The original Autonomic Security Operations (ASO) paper (2021) “New Paper: “Future of the SOC: Forces shaping modern security operations” (Paper 1 of 4)” “New Paper: “Future of the SOC: SOC People — Skills, Not Tiers” (Paper 2 of 4)” “New Paper: “Future Of The SOC: Process Consistency and Creativity: a Delicate Balance” (Paper 3 of 4)”
EP178 Meet Brandon Wood: The Human Side of Threat Intelligence: From Bad IP to Trafficking Busts
Jun 24 2024
EP178 Meet Brandon Wood: The Human Side of Threat Intelligence: From Bad IP to Trafficking Busts
Guest: Brandon Wood, Product Manager for Google Threat Intelligence Topics: Threat intelligence is one of those terms that means different things to everyone–can you tell us what this term has meant in the different contexts of your career?  What do you tell people who assume that “TI = lists of bad IPs”? We heard while prepping for this show that you were involved in breaking up a human trafficking ring: tell us about that! In Anton’s experience, a lot  of cyber TI is stuck in “1. Get more TI 2. ??? 3. Profit!” How do you move past that? One aspect of threat intelligence that’s always struck me as goofy is the idea that we can “monitor the dark web” and provide something useful. Can you change my mind on this one? You told us your story of getting into sales, you recently did a successful rotation into the role of Product Manager,, can you tell us about what motivated you to do this and what the experience was like? Are there other parts of your background that inform the work you’re doing and how you see yourself at Google?  How does that impact our go to market for threat intelligence, and what’re we up to when it comes to keeping the Internet and broader world safe? Resources: Video EP175 Meet Crystal Lister: From Public Sector to Google Cloud Security and Threat Horizons EP128 Building Enterprise Threat Intelligence: The Who, What, Where, and Why EP112 Threat Horizons - How Google Does Threat Intelligence Introducing Google Threat Intelligence: Actionable threat intelligence at Google scale A Requirements-Driven Approach to Cyber Threat Intelligence
EP174 How to Measure and Improve Your Cloud Incident Response Readiness: A New Framework
May 27 2024
EP174 How to Measure and Improve Your Cloud Incident Response Readiness: A New Framework
Guest: Angelika Rohrer, Sr. Technical Program Manager , Cyber Security Response at Alphabet Topics: Incident response (IR) is by definition “reactive”, but ultimately incident prep determines your IR success. What are the broad areas where one needs to prepare? You have created a new framework for measuring how ready you are for an incident, what is the approach you took to create it? Can you elaborate on the core principles behind the Continuous Improvement (CI) Framework for incident response? Why is continuous improvement crucial for effective incident response, especially in cloud environments? Can’t you just make a playbook and use it? How to overcome the desire to focus on the easy metrics and go to more valuable ones? What do you think Google does best in this area? Can you share examples of how the CI Framework could have helped prevent or mitigate a real-world cloud security incident? How can other organizations practically implement the CI Framework to enhance their incident response capabilities after they read the paper? Resources: “How do you know you are "Ready  to Respond"? paper EP75 How We Scale Detection and Response at Google: Automation, Metrics, Toil EP103 Security Incident Response and Public Cloud - Exploring with Mandiant EP158 Ghostbusters for the Cloud: Who You Gonna Call for Cloud Forensics EP98 How to Cloud IR or Why Attackers Become Cloud Native Faster?
EP171 GenAI in the Wrong Hands: Unmasking the Threat of Malicious AI and Defending Against the Dark Side
May 6 2024
EP171 GenAI in the Wrong Hands: Unmasking the Threat of Malicious AI and Defending Against the Dark Side
Guest: Elie Bursztein, Google DeepMind Cybersecurity Research Lead, Google  Topics: Given your experience, how afraid or nervous are you about the use of GenAI by the criminals (PoisonGPT, WormGPT and such)? What can a top-tier state-sponsored threat actor do better with LLM? Are there “extra scary” examples, real or hypothetical? Do we really have to care about this “dangerous capabilities” stuff (CBRN)? Really really? Why do you think that AI favors the defenders? Is this a long term or a short term view? What about vulnerability discovery? Some people are freaking out that LLM will discover new zero days, is this a real risk?  Resources: “How Large Language Models Are Reshaping the Cybersecurity Landscape” RSA 2024 presentation by Elie (May 6 at 9:40AM) “Lessons Learned from Developing Secure AI Workflows” RSA 2024 presentation by Elie (May 8, 2:25PM) EP50 The Epic Battle: Machine Learning vs Millions of Malicious Documents EP40 2021: Phishing is Solved? EP135 AI and Security: The Good, the Bad, and the Magical EP170 Redefining Security Operations: Practical Applications of GenAI in the SOC EP168 Beyond Regular LLMs: How SecLM Enhances Security and What Teams Can Do With It PyRIT LLM red-teaming tool Accelerating incident response using generative AI Threat Actors are Interested in Generative AI, but Use Remains Limited OpenAI’s Approach to Frontier Risk
EP168 Beyond Regular LLMs: How SecLM Enhances Security and What Teams Can Do With It
Apr 15 2024
EP168 Beyond Regular LLMs: How SecLM Enhances Security and What Teams Can Do With It
Guests:  Umesh Shankar, Distinguished Engineer, Chief Technologist for Google Cloud Security Scott Coull, Head of Data Science Research, Google Cloud Security Topics: What does it mean to “teach AI security”? How did we make SecLM? And also: why did we make SecLM? What can “security trained LLM” do better vs regular LLM? Does making it better at security make it worse at other things that we care about? What can a security team do with it today?  What are the “starter use cases” for SecLM? What has been the feedback so far in terms of impact - both from practitioners but also from team leaders? Are we seeing the limits of LLMs for our use cases? Is the “LLM is not magic” finally dawning? Resources: “How to tackle security tasks and workflows with generative AI” (Google Cloud Next 2024 session on SecLM) EP136 Next 2023 Special: Building AI-powered Security Tools - How Do We Do It? EP144 LLMs: A Double-Edged Sword for Cloud Security? Weighing the Benefits and Risks of Large Language Models Supercharging security with generative AI  Secure, Empower, Advance: How AI Can Reverse the Defender’s Dilemma? Considerations for Evaluating Large Language Models for Cybersecurity Tasks Introducing Google’s Secure AI Framework Deep Learning Security and Privacy Workshop  Security Architectures for Generative AI Systems ACM Workshop on Artificial Intelligence and Security Conference on Applied Machine Learning in Information Security
EP164 Quantum Computing: Understanding the (very serious) Threat and Post-Quantum Cryptography
Mar 18 2024
EP164 Quantum Computing: Understanding the (very serious) Threat and Post-Quantum Cryptography
Guest: Jennifer Fernick, Senor Staff Security Engineer and UTL, Google Topics: Since one of us (!) doesn't have a PhD in quantum mechanics, could you explain what a quantum computer is and how do we know they are on a credible path towards being real threats to cryptography? How soon do we need to worry about this one? We’ve heard that quantum computers are more of a threat to asymmetric/public key crypto than symmetric crypto. First off, why? And second, what does this difference mean for defenders? Why (how) are we sure this is coming? Are we mitigating a threat that is perennially 10 years ahead and then vanishes due to some other broad technology change? What is a post-quantum algorithm anyway? If we’re baking new key exchange crypto into our systems, how confident are we that we are going to be resistant to both quantum and traditional cryptanalysis?  Why does NIST think it's time to be doing the PQC thing now? Where is the rest of the industry on this evolution? How can a person tell the difference here between reality and snakeoil? I think Anton and I both responded to your initial email with a heavy dose of skepticism, and probably more skepticism than it deserved, so you get the rare on-air apology from both of us! Resources: Securing tomorrow today: Why Google now protects its internal communications from quantum threats How Google is preparing for a post-quantum world NIST PQC standards PQ Crypto conferences “Quantum Computation & Quantum Information” by Nielsen & Chuang book “Quantum Computing Since Democritus” by Scott Aaronson book EP154 Mike Schiffman: from Blueboxing to LLMs via Network Security at Google