
Advertise on podcast: Cloud Security Podcast
Rating
5from
This podcast has
346 episodes
Language
EnglishPublisher
TechRiot.ioExplicit
No
Date created
2019/11/29
Latest episode
2026/04/21
Average duration
44 min.
Release period
11 days
Description
Learn Cloud Security in Public Cloud and for AI systems, the unbiased way from CyberSecurity Experts solving challenges at Cloud Scale. We are honest because we are not owned by Cloud Service Provider like AWS, Azure or Google Cloud. We aim to make the community learn Cloud Security through community stories from small - Large organisations solving multi-cloud challenges to diving into specific topics of Cloud Security. We STREAM interviews on Cloud Security Topics every week on Linkedin, YouTube and Twitter with over 150K people tuning in.
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Check latest episodes from Cloud Security Podcast podcast
The Rise of Agentic Cloud Security: Code-to-Cloud Shrinks to 3 Days
2026/04/21
Is your cloud security strategy ready for the "messy middle" of AI adoption? With developers pushing code from inception to production in under three days using "vibe coding," and adversaries capable of exfiltrating data in just 25 minutes, human-led security is no longer fast enough .In this episode, Ashish sits down with Elad Koren from Palo Alto Networks (Cortex Cloud) to discuss the shift toward Agentic Cloud Security. Elad spoke to us about why bolting an AI chatbot onto legacy security tools doesn't work, and why you must run AI directly where your data lies . Elad shared a real-world case study: an organization that rapidly spun up an "internal" AI workload to test the market, only to have a red team discover it was exposed to the public internet with zero authentication .If you want to know how the role of cloud security practitioners will evolve from manual analysts to AI orchestrators within the next five years, listen to this episode.
Guest Socials - Elad's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:50) Who is Elad Koren? (Palo Alto Networks / RSA Security) (04:00) The Explosion of "Vibe Coding" and AI Applications (05:10) How CNAPP is Evolving from Posture to Active Protection (07:20) The New Threat Model: 25-Minute Exfiltration Windows (09:30) What is "Agentic Cloud Security"? (Fighting Machines with Machines) (11:40) The "Messy Middle" and the Evolution of Security Practitioners (14:30) Platformization: Why Security Can No Longer Survive in Silos (16:50) Blurring the Lines Between Cloud and Enterprise Estates (18:20) Case Study: An Unauthenticated "Internal" AI Workload Exposed (20:30) How AI is Shrinking Code-to-Cloud Cycles to 3 Days (22:30) The Coming Crisis: Security Token Budgets vs. Speed (23:30) Fun Questions: Kangaroo Jerky Tasting (25:20) Hobbies & Family: Cycling, Audiobooks, and Fatherhood (26:30) Favorite Food: Thai Cuisine in the Bay Area
Resources spoken about during the episode:
- Cortex Cloud
- Symphony 26
- The Agentic SOC Summit
- Palo Alto Networks Linkedin Page
- Elad's Linkedin
Why EDR Fails at AI Security & The Rise of Endpoint Behavior Modeling
2026/04/14
Is your EDR blinding you to insider threats? In this episode, Ashish is joined by Brandon Dixon (Co-Founder & CTO of Ent AI, and former Microsoft Security Copilot leader) to discuss why traditional endpoint security tools are failing in the AI era .
Brandon talks about the reality of modern "Insider Risk." Attackers are no longer relying on malware; they are "living off the land" by using legitimate enterprise software (like Zoom or Microsoft Office) to look like everyday employees . Why EDR tools can see that Zoom is running, but are completely blind to a user granting remote control to an outsider .
We also explore the explosion of Shadow AI, highlighting a real-world HIPAA violation where an HR employee tried to feed patient records into Meta AI via WhatsApp . If your SOC team is drowning in alerts from "dumb control points," this episode talks about how to move from reactive pattern matching (legacy DLP) to proactive behavioral intent modeling at the endpoint
Guest Socials - Brandon's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:50) Who is Brandon Dixon? (RiskIQ, Microsoft Copilot, Ent AI) (04:00) Redefining Insider Risk: Malice vs. Mistakes (05:10) "Living Off the Land": Why Adversaries Use Legitimate Tools (06:30) The Zoom Example: Why EDR is Blind to Remote Control Hacks (09:30) The Failure of Security Training against "Click Fix" Attacks (11:50) Case Study: A HIPAA Violation via Meta AI in WhatsApp (13:50) Why Traditional DLP Fails at Semantic Context (16:50) Local AI Usage: Why Workloads Are Returning to the Endpoint (18:50) The Problem with UEBA: Putting Anomalies in Context (22:30) Why You Can't Build This With a Data Lake (26:30) Stopping the "Trophy SOC" and Dumb Alerts (27:40) Fun Questions: Kangaroo Jerky Tasting (28:40) Hobbies & Pride: Ultramarathons and Growing Up in Baltimore (29:20) Favorite Cuisine: Burmese Food (Tea Leaf Salad)
Solving Prompt Injection & Shadow AI for AI Malware
2026/04/07
Are AI agents functioning like adversarial malware inside your network? In this episode of the Cloud Security Podcast, Ashish sits down with Jasson Casey, Co-founder and CEO of Beyond Identity, to speak about the security risks introduced by Shadow AI and code assistants .Jasson explains why an AI agent executing a tool is the perfect opportunity for prompt injection or proprietary data exfiltration comparing unchecked agents to Ron Burgundy reading whatever is on the teleprompter . We discuss the "barbell" reaction of CISOs (either blocking AI entirely or blindly accepting the risk) and why placing device-bound identity at the core of your security stack is the only way to safely enable AI speed .From an $80,000 stolen Anthropic key nightmare on Reddit to a red-team exercise that cloned voices using Hugging Face models in just four hours, this episode highlights the tangible threats and solutions of the AI era .
Guest Socials - Jasson's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:50) Who is Jasson Casey? (CEO of Beyond Identity) (03:50) The Reality of Shadow AI: Marketers & Devs Moving Fast (05:10) Why AI Agents Execute Like Adversarial Malware (06:20) Prompt Injection Over Time & Agent "Memory" as Persistence (07:40) The CISO "Barbell": Blocking Everything vs. Accepting All Risk (09:30) Applying the NIST Framework to AI Agents (12:00) The Reddit Horror Story: An $80,000 Stolen Claude Key (13:00) Why Device-Bound Identity is the Ultimate AI Control Plane (15:50) The Death of SaaS IT Products (Replaced by Git + Claude Code) (19:30) Fixing Prompt Injection & Exfil via Attributable Identity (20:50) Moving from UI Dashboards to API Data + AI Skills (26:20) Building "Agentic Playbooks" for Security Teams (27:40) Red Teaming: Cloning Voices in 4 Hours via Hugging Face (30:20) Fun Questions: Kangaroo vs. Crocodile Tasting (31:50) Hobbies: Radar Projects & Northern Mexican Cuisine (Dark Mole)
This episode was sponsored by Beyond Identity
Resources spoken about during the episode:
To get started with Ceros, the AI Trust Layer - Visit beyondidentity.ai
Browser Security Explained: Consent Phishing, "Click Fix" Attacks & The Limits of EDR
2026/03/10
Is your security team treating your Identity Provider (IDP) like a firewall? In this episode, Adam Bateman (CEO & Co-founder of Push Security) explains why that's a dangerous mistake and how modern attackers are bypassing SSO entirely .Drawing from his background leading red teams that simulated nation-state attacks , Adam breaks down the massive architectural shift from network-based attacks to browser-native exploits. We dive into the terrifying evolution of phishing, from "Click Fix" attacks that trick users into running malicious commands via their clipboard, to "Consent Phishing" that completely takes over Azure without ever touching the endpoint .If your company relies heavily on SaaS applications or Chromebooks, this episode would be a valuable listen.
Guest Socials - Adam's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:50) Who is Adam Bateman? (Red Teaming & Simulating Nation States) (05:40) Why Identity & MFA Are Not "Solved" Problems (07:50) The Myth: Why an IDP is Not a Firewall (11:30) Consent Phishing: Exploiting OAuth Apps (13:30) The Architectural Shift: Network to Browser (15:30) Scattered Spider & The Rise of Identity Coalitions (19:30) Threat Modeling: On-Prem vs. Chromebooks (23:20) The Problem with SSPM and API Limitations (28:40) How "Click Fix" Attacks Trick Users into Running Malware (32:30) Omnichannel Phishing: LinkedIn, SMS, and Google Ads (34:30) Weaponizing Legitimate SaaS Apps (The DocuSign Exploit) (37:00) Consent Fix: Full Azure Compromise Inside the Browser (38:50) Disrupting the Secure Web Gateway (SWG) Market (41:40) Fun Questions: Wakeboarding, Culture, and Brat's Restaurant
Resources spoken about during the episode:
You can find out more about Push Security here.
Thank you to Push Security for sponsoring this episode.
Is AI Hallucinations a Myth and the Real Threat from AI
2026/03/06
Are attackers really using AI to run end-to-end cyber campaigns? In this episode, Edward Wu (Founder and CEO, DropzoneAI) joins Ashish to separate the hype from reality when it comes to AI-driven attacks .Edward explains how attackers are currently using open-source LLMs for reconnaissance and spear-phishing , and why the major commercial models now explicitly prohibit users from generating exploits without vetting . On the defense side, Edward shares how AI agents have successfully automated over 160 years' worth of alert investigations in the real world proving that 100% software-delivered SOC triage is already here .We also debunk the myth of AI "hallucinations," explaining why most errors are actually just poor context management . If you're building a security operations center or working with an MSSP, this episode will teach you how to shift from manual alert fatigue to leveraging AI for threat hunting.
Guest Socials - Edward's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security
, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:50) Who is Edward Wu? (Founder of Dropzone AI) (04:50) The Reality of AI Cyber Attacks Today (Recon vs. End-to-End) (07:20) Why Commercial LLMs Are Blocking Exploit Generation (11:50) How MSSPs are Evolving with AI Triage (18:20) The Asymmetric Capacity Gap: Why Humans Can't Keep Up (22:30) Automating 160 Years of Alert Investigations (23:50) Why AI Hallucinations are Actually Context Management Failures (26:00) Build vs. Buy: The Data Network Effect for AI Agents (29:20) The New Workflow for SOC Analysts & Threat Hunters(31:30) Defining "Threategy": Scope, Authorization, and Context (35:50) How to Detect Prompt Injection (Treat it like an Insider Threat) (38:30) Dropzone AI Announcements at RSAC
Resources spoken about during the episode:
- Dropzone Diner RSAC 2026
- If you want to learn more about Dropzone- you can do that here!
Why AI Infrastructure is Harder to Secure Than Cloud
2026/02/20
Is AI security just "Cloud Security 2.0"? Toni De La Fuente, creator of the open-source tool Prowler, joins Ashish to explain why securing AI workloads requires a fundamentally different approach than traditional cloud infrastructure.
We dive deep into the "Shared Responsibility Gap" emerging with managed AI services like AWS Bedrock and OpenAI. Toni spoke about the hidden dangers of default AI architectures, why you should never connect an MCP (Model Context Protocol) directly to a database.
We discuss the new AI-driven SDLC, where tools like Claude Code can generate infrastructure but also create massive security blind spots if not monitored.
Guest Socials - Toni's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security
, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:50) Who is Toni De La Fuente? (Creator of Prowler)(03:50) AI Security vs. Cloud Security: What's the Difference? (07:20) The Shared Responsibility Gap in AI Services (Bedrock, OpenAI) (11:30) The "Fifth Party" Risk: Managed AI Access (13:40) AI Architecture Best Practices: Never Connect MCP to DB Directly (16:40) Prowler's AI Pillars: Generating Dashboards & Detections (22:30) The New SDLC: Securing Code from Claude Code & Lovable (25:30) The "Magic" Trap: Why AI Doesn't Know Your Security Context (28:30) Top 3 Priorities for Security Leaders (Infra, LLM, Shadow AI) (30:40) Future Predictions: Why Predicting 12 Months Out is Impossible
How Attackers Bypass AI Guardrails with Natural Language
2026/02/10
In the world of Generative AI, natural language has become the new executable. Attackers no longer need complex code to breach your systems, sometimes, asking for a "poem" is enough to steal your passwords .
In this episode, Eduardo Garcia (Global Head of Cloud Security Architecture at Check Point) joins Ashish to explain the paradigm shift in AI security. He shares his experience building AI-powered fraud detection systems and why traditional security controls fail against intent-based attacks like prompt injection and data poisoning .
We dive deep into the reality of Shadow AI, where employees unknowingly train public models with sensitive corporate data , and the sophisticated world of Deepfakes, where attackers can bypass biometric security using AI-generated images unless you're tracking micro-movements of the eye .
Guest Socials - Eduardo's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security
, you can check out our sister podcast - AI Security Podcast
(00:00) Introduction(01:55) Who is Eduardo Garcia? (Check Point)(03:00) Defining Security for GenAI: The Focus on Prompts (05:20) Why Natural Language is the New Executable (08:50) Multilingual Attacks: Bypassing Filters with Mandarin (12:00) Shift Left vs. Shift Right: The 70/30 Rule for AI Security (15:30) The "Poem Hack": Stealing Passwords with Creative Prompts (21:00) Shadow AI: The "HR Spreadsheet" Leak Scenario (25:40) Security vs. Compliance in a Blurring World (28:00) The Conflict: "My Budget Doesn't Include Security" (34:00) The 5 V's of AI Data: Volume, Veracity, Velocity (40:00) Deepfakes & Biometrics: Detecting Micro-Movements (43:40) Fun Questions: Soccer, Family, and Honduran Tacos
Vulnerability Management vs. Exposure Management
2026/02/06
In this episode, Brad Hibbert (COO & Chief Strategy Officer at Brinqa) joins Ashish to explain why traditional risk-based vulnerability management (RBVM) is no longer enough in a cloud-first world .
We explore the evolution from simple patch management to Exposure Management a holistic approach that sits above your security tools to connect infrastructure, code, and cloud risks to actual business impact . Brad breaks down the critical difference between a "Risk Owner" (the service owner) and a "Remediation Owner" (the team fixing the bug) and why this distinction solves the "who fixes this?" problem .
This conversation covers practical steps to uplift your VM program, how AI is helping prioritize the noise , and why compliance often just "proves activity" rather than reducing real risk . Whether you're drowning in Jira tickets or trying to automate remediation, this episode provides a roadmap for modernizing your security posture
Guest Socials - Brad's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security
, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:50) Who is Brad Hibbert? (Brinqa)(04:55) The Evolution: From Scanning Servers to Cloud Complexity (06:50) What is Risk-Based Vulnerability Management? (08:50) Risk Owners vs. Remediation Owners: Who Fixes What? (12:00) How AI is Changing Vulnerability Management (15:20) Defining Exposure Management: Moving Beyond the Tools (18:30) The Challenge of "Data Inconsistency" Between Tools (22:30) Readiness Check: Are You Ready for Exposure Management? (25:10) Automated Remediation: Is "Zero Tickets" Possible? (28:40) Compliance vs. Risk: Why "Activity" isn't "Impact" (31:30) Maturity Milestones for Exposure Management (36:50) Fun Questions: Golf, Turkish Kebabs & Friendships
Is Developer Friendly AI Security Possible with MCP & Shadow AI
2026/02/05
Is "developer-friendly" AI security actually possible? In this episode, Bryan Woolgar-O'Neil (CTO & Co-founder of Harmonic Security) joins Ashish to dismantle the traditional "block everything" approach to security.
Bryan explains why 70% of Model Context Protocol (MCP) servers are running locally on developer laptops and why trying to block them is a losing battle . Instead, he advocates for a "coaching" approach, intervening in real-time to guide engineers rather than stopping their flow .
We dive deep into the technical realities of MCP (Model Context Protocol), why it's becoming the standard for connecting AI to data, and the security risks of connecting it to production environments . Bryan also shares his prediction that Small Language Models (SLMs) will eventually outperform general giants like ChatGPT for specific business tasks .
Guest Socials - Bryan's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security
, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(01:55) Who is Bryan Woolgar-O'Neil?(03:00) Why AI Adoption Stops at Experimentation(05:15) The "Shadow AI" Blind Spot: Firewall Stats vs. Reality (08:00) Is AI Security Fundamentally Different? (Speed & Scale) (10:45) Can Security Ever Be "Developer Friendly"? (14:30) What is MCP (Model Context Protocol)? (17:20) Why 70% of MCP Usage is Local (and the Risks) (21:30) The "Coaching" Approach: Don't Just Block, Educate (25:40) Developer First: Permissive vs. Blocking Cultures (30:20) The Rise of the "Head of AI" Role (34:30) Use Cases: Workforce Productivity vs. Product Integration (41:00) An AI Security Maturity Model (Visibility -> Access -> Coaching) (46:00) Future Prediction: Agentic Flows & Urgent Tasks (49:30) Why Small Language Models (SLMs) Will Win (53:30) Fun Questions: Feature Films & Pork Dumplings
Why AI Can't Replace Detection Engineers: Build vs. Buy & The Future of SOC
2026/01/21
Is the AI SOC a reality, or just vendor hype? In this episode, Antoinette Stevens (Principal Security Engineer at Ramp) joins Ashish to dissect the true state of AI in detection engineering.
Antoinette shares her experience building detection program from scratch, explaining why she doesn't trust AI to close alerts due to hallucinations and faulty logic . We explore the "engineering-led" approach to detection, moving beyond simple hunting to building rigorous testing suites for detection-as-code .
We discuss the shrinking entry-level job market for security roles , why software engineering skills are becoming non-negotiable , and the critical importance of treating AI as a "force multiplier, not your brain".
Guest Socials - Antoinette's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security
, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:25) Who is Antoinette Stevens?(04:10) What is an "Engineering-Led" Approach to Detection? (06:00) Moving from Hunting to Automated Testing Suites (09:30) Build vs. Buy: Is AI Making it Easier to Build Your Own Tools? (11:30) Using AI for Documentation & Playbook Updates (14:30) Why Software Engineers Still Need to Learn Detection Domain Knowledge (17:50) The Problem with AI SOC: Why ChatGPT Lies During Triage (23:30) Defining AI Concepts: Memory, Evals, and Inference (26:30) Multi-Agent Architectures: Using Specialized "Persona" Agents (28:40) Advice for Building a Detection Program in 2025 (Back to Basics) (33:00) Measuring Success: Noise Reduction vs. False Positive Rates (36:30) Building an Alerting Data Lake for Metrics (40:00) The Disappearing Entry-Level Security Job & Career Advice (44:20) Why Junior Roles are Becoming "Personality Hires" (48:20) Fun Questions: Wine Certification, Side Quests, and Georgian Food
AI Vulnerability Management: Why You Can't Patch a Neural Network
2026/01/13
Traditional vulnerability management is simple: find the flaw, patch it, and verify the fix. But what happens when the "asset" is a neural network that has learned something ethically wrong? In this episode, Sapna Paul (Senior Manager at Dayforce) explains why there are no "Patch Tuesdays" for AI models .
Sapna breaks down the three critical layers of AI vulnerability management: protecting production models, securing the data layer against poisoning, and monitoring model behavior for technically correct but ethically flawed outcomes . We discuss how to update your risk register to speak the language of business and the essential skills security professionals need to survive in an AI-first world .
The conversation also covers practical ways to use AI within your security team to combat alert fatigue , the importance of explainability tools like SHAP and LIME , and how to align with frameworks like the NIST AI RMF and the EU AI Act .
Guest Socials - Sapna's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Security
, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:00) Who is Sapna Paul?(02:40) What is Vulnerability Management in the Age of AI? (05:00) Defining the New Asset: Neural Networks & Models (07:00) The 3 Layers of AI Vulnerability (Production, Data, Behavior) (10:20) Updating the Risk Register for AI Business Risks (13:30) Compliance vs. Innovation: Preventing AI from Going Rogue (18:20) Using AI to Solve Vulnerability Alert Fatigue (23:00) Skills Required for Future VM Professionals (25:40) Measuring AI Adoption in Security Teams (29:20) Key Frameworks: NIST AI RMF & EU AI Act (31:30) Tools for AI Security: Counterfit, SHAP, and LIME (33:30) Where to Start: Learning & Persona-Based Prompts (38:30) Fun Questions: Painting, Mentoring, and Vegan Ramen
Why Backups Aren't Enough & Identity Recovery is Key against Ransomware
2025/12/16
Think your cloud backups will save you from a ransomware attack? Think again. In this episode, Matt Castriotta (Field CTO at Rubrik) explains why the traditional "I have backups" mindset is dangerous. He distinguishes between Disaster Recovery (business continuity for operational errors) and Cyber Resilience (recovering from a malicious attack where data and identity are untrusted) .
Matt speaks about the "dirty secrets" of cloud-native recovery, explaining why S3 versioning and replication are not valid cyber recovery strategies . The conversation shifts to the critical, often overlooked aspect of Identity Recovery. If your Active Directory or Entra ID is compromised, it's "ground zero” and you can't access anything. Matt argues that identity must be treated as the new perimeter and backed up just like any other critical data source .
We also explore the impact of AI agents on data integrity, how do you "rewind" an AI agent that hallucinated and corrupted your data? Plus, practical advice on DORA compliance, multi-cloud resiliency, and the "people and process" side of surviving a breach.
Guest Socials - Matt's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Cybersecurity, you can check out our sister podcast - AI Security Podcast
Questions:
(00:00) Introduction(02:20) Who is Matt Castriotta?(03:20) Defining Cyber Resilience: The Ability to Say "No" to Ransomware(05:00) Why "I Have Backups" is Not Enough(06:45) The Difference Between Disaster Recovery and Cyber Recovery(10:20) Cloud Native Risks: Versioning and Replication Are Not Backups(12:50) DORA Compliance: Multi-Cloud Resiliency & Egress Costs(15:10) The "Shared Responsibility Model" Trap in Cloud(17:45) Identity is the New Perimeter: Why You Must Back It Up(22:30) Identity Recovery: Can You Restore Your Active Directory in Minutes?(25:40) AI and Data: The New "Oil" and "Crown Jewels"(27:20) Rubrik Agent Cloud: Rewinding AI Agent Actions(29:40) Top 3 Priorities for a 2026 Resiliency Program(33:10) Fun Questions: Guitar, Family, and Italian Food
How to secure your AI Agents: A CISOs Journey
2025/12/09
Transitioning a mature organization from an API-first model to an AI-first model is no small feat. In this episode, Yash Kosaraju, CISO of Sendbird, shares the story of how they pivoted from a traditional chat API platform to an AI agent platform and how security had to evolve to keep up.
Yash spoke about the industry's obsession with "Zero Trust," arguing instead for a practical "Multi-Layer Trust" approach that assumes controls will fail . We dive deep into the specific architecture of securing AI agents, including the concept of a "Trust OS," dealing with new incident response definitions (is a wrong AI answer an incident?), and the critical need to secure the bridge between AI agents and customer environments .
This episode is packed with actionable advice for AppSec engineers feeling overwhelmed by the speed of AI. Yash shares how his team embeds security engineers into sprint teams for real-time feedback, the importance of "AI CTFs" for security awareness, and why enabling employees with enterprise-grade AI tools is better than blocking them entirely .
Questions asked:
Guest Socials - Yash's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Cybersecurity, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:20) Who is Yash Kosaraju? (CISO at Sendbird)(03:30) Sendbird's Pivot: From Chat API to AI Agent Platform(05:00) Balancing Speed and Security in an AI Transition(06:50) Embedding Security Engineers into AI Sprint Teams(08:20) Threats in the AI Agent World (Data & Vendor Risks)(10:50) Blind Spots: "It's Microsoft, so it must be secure"(12:00) Securing AI Agents vs. AI-Embedded Applications(13:15) The Risk of Agents Making Changes in Customer Environments(14:30) Multi-Layer Trust vs. Zero Trust (Marketing vs. Reality) (17:30) Practical Multi-Layer Security: Device, Browser, Identity, MFA(18:25) What is "Trust OS"? A Foundation for Responsible AI(20:45) Balancing Agent Security vs. Endpoint Security(24:15) AI Incident Response: When an AI Gives a Wrong Answer(29:20) Security for Platform Engineers: Enabling vs. Blocking(30:45) Providing Enterprise AI Tools (Gemini, ChatGPT, Cursor) to Employees(32:45) Building a "Security as Enabler" Culture(36:15) What Questions to Ask AI Vendors (Paying with Data?)(39:20) Personal Use of Corporate AI Accounts(43:30) Using AI to Learn AI (Gemini Conversations)(45:00) The Stress on AppSec Engineers: "I Don't Know What I'm Doing"(48:20) The AI CTF: Gamifying Security Training(50:10) Fun Questions: Outdoors, Team Building, and Indian/Korean Food
AI-First Vulnerability Management: Should CISOs Build or Buy?
2025/12/04
Thinking of building your own AI security tool? In this episode, Santiago Castiñeira, CTO of Maze, breaks down the realities of the "Build vs. Buy" debate for AI-first vulnerability management.
While building a prototype script is easy, scaling it into a maintainable, audit-proof system is a massive undertaking requiring specialized skills often missing in security teams. The "RAG drug" relies too heavily on Retrieval-Augmented Generation for precise technical data like version numbers, which often fails .
The conversation gets into the architecture required for a true AI-first system, moving beyond simple chatbots to complex multi-agent workflows that can reason about context and risk . We also cover the critical importance of rigorous "evals" over "vibe checks" to ensure AI reliability, the hidden costs of LLM inference at scale, and why well-crafted agents might soon be indistinguishable from super-intelligence .
Guest Socials - Santiago's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Cybersecurity, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:00) Who is Santiago Castiñeira?(02:40) What is "AI-First" Vulnerability Management? (Rules vs. Reasoning)(04:55) The "Build vs. Buy" Debate: Can I Just Use ChatGPT?(07:30) The "Bus Factor" Risk of Internal Tools(08:30) Why MCP (Model Context Protocol) Struggles at Scale(10:15) The Architecture of an AI-First Security System(13:45) The Problem with "Vibe Checks": Why You Need Proper Evals(17:20) Where to Start if You Must Build Internally(19:00) The Hidden Need for Data & Software Engineers in Security Teams(21:50) Managing Prompt Drift and Consistency(27:30) The Challenge of Changing LLM Models (Claude vs. Gemini)(30:20) Rethinking Vulnerability Management Metrics in the AI Era(33:30) Surprises in AI Agent Behavior: "Let's Get Back on Topic"(35:30) The Hidden Cost of AI: Token Usage at Scale(37:15) Multi-Agent Governance: Preventing Rogue Agents(41:15) The Future: Semi-Autonomous Security Fleets(45:30) Why RAG Fails for Precise Technical Data (The "RAG Drug")(47:30) How to Evaluate AI Vendors: Is it AI-First or AI-Sprinkled?(50:20) Common Architectural Mistakes: Vibe Evals & Cost Ignorance(56:00) Unpopular Opinion: Well-Crafted Agents vs. Super Intelligence(58:15) Final Questions: Kids, Argentine Steak, and Closing
SIEM vs. Data Lake: Why We Ditched Traditional Logging?
2025/12/02
In this episode, Cliff Crosland, CEO & co-founder of Scanner.dev, shares his candid journey of trying (and initially failing) to build an in-house security data lake to replace an expensive traditional SIEM.
Cliff explains the economic breaking point where scaling a SIEM became "more expensive than the entire budget for the engineering team". He details the technical challenges of moving terabytes of logs to S3 and the painful realization that querying them with Amazon Athena was slow and costly for security use cases .
This episode is a deep dive into the evolution of logging architecture, from SQL-based legacy tools to the modern "messy" data lake that embraces full-text search on unstructured data. We discuss the "data engineering lift" required to build your own, the promise (and limitations) of Amazon Security Lake, and how AI agents are starting to automate detection engineering and schema management.
Guest Socials - Cliff's Linkedin
Podcast Twitter - @CloudSecPod
If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:
-Cloud Security Podcast- Youtube
- Cloud Security Newsletter
If you are interested in AI Cybersecurity, you can check out our sister podcast - AI Security Podcast
Questions asked:
(00:00) Introduction(02:25) Who is Cliff Crosford?(03:00) Why Teams Are Switching from SIEMs to Data Lakes(06:00) The "Black Hole" of S3 Logs: Cliff's First Failed Data Lake(07:30) The Engineering Lift: Do You Need a Data Engineer to Build a Lake?(11:00) Why Amazon Athena Failed for Security Investigations(14:20) The Danger of Dropping Logs to Save Costs(17:00) Misconceptions About Building Your Own Data Lake(19:00) The Evolution of Logging: From SQL to Full-Text Search(21:30) Is Amazon Security Lake the Answer? (OCSF & Custom Logs)(24:40) The Nightmare of Log Normalization & Custom Schemas(28:00) Why Future Tools Must Embrace "Messy" Logs(29:55) How AI Agents Are Automating Detection Engineering(35:45) Using AI to Monitor Schema Changes at Scale(39:45) Build vs. Buy: Does Your Security Team Need Data Engineers?(43:15) Fun Questions: Physics Simulations & Pumpkin Pie
Podcast reviews
Read Cloud Security Podcast podcast reviews
Maocol99 2024/11/22
Awesome podcast
Always bringing experts and covering insights and risky topics for protecting the cloud. Keep it up!
mvelasco07 2023/03/13
Great show!
Cloud Security Podcast has quickly become a favorite in my feed! I’m consistently impressed by the engaging conversations, insightful content, and act...
gblind8 2021/11/30
Insightful questions I’m curious to know the answer to
If you’re looking to hear from professionals in the field from a spectrum of experience, I would highly recommend this podcast. Some interview guests ...
Kapil CSP 2021/11/06
Best in class Cloud Security Updates
Over the last few years, podcasts have grown from a fringe media to one of the most popular ways to get news and information. For those in the know, o...
UsulMuadDib 2021/11/03
Amazing weekly cloud security podcast!
When I started trying to get an understanding of “What is Cloud Security?”, “What do all these crazy acronyms mean?”, and “How do I keep up to date wi...
frank_cap 2021/11/03
Must listen for all levels of cloud
Whether you are an experienced cloud Jedi or just beginning your cloud journey, you’re going to want to listen to the Cloud Security Podcast. CSP has ...
BrandonE211 2021/11/02
Great content on an important subject.
Keep it up, Ashish!
TrojanBagder 2021/11/02
Insightful and entertaining
With nearly every business moving to the cloud, focus on cloud security is at the forefront. This podcast will give you the insights you need to secur...
Yoni Leitersdorf 2021/04/14
A great show with an awesome reach
A few months ago I’ve heard of Ashish’s show. Since then I’ve started listening in regularly, and there’s a lot of useful content with interesting per...
Havok0750 2021/02/19
Technical and practical
Really enjoying this podcast so far as it strikes a useful balance between technical and applicable content. Things that allow you to actually walk aw...
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