Cyber Sentries: AI Insight to Cloud Security

Inside the AI Deepfake ThreatWhat if the voice confirming your wire transfer wasn't actually your client? Ben Colman, founder and CEO of Reality Defender, joins host John Richards to unpack one of the fastest-growing attack surfaces in cybersecurity: AI-generated deepfakes. Once the exclusive domain of Hollywood studios and nation-state actors, real-time voice and video impersonation is now accessible to anyone with a laptop—and fraudsters are scaling up fast.From Specialized Hardware to Your Home ComputerBen traces the evolution from the specialized machinery required six years ago to today's world where anyone can clone a voice with less than five seconds of audio—locally, for free, using open-source models. He walks through the modern fraud landscape, from grandparent scams and bank account takeovers to an eye-opening story about fake job applicants that will make any recruiting team rethink its screening process.Reality Defender's approach is built for how organizations actually work—plugging directly into call centers, video conferencing platforms, and identity verification tools through a simple API, rather than asking teams to adopt yet another standalone product. Their probabilistic detection models scan in real time across thousands of indicators, all without storing or comparing against any biometric data.John and Ben also get into the emerging frontier of agentic AI—what happens when you need to authenticate an AI voice agent rather than a human—and how smart permission gates can define exactly what those agents are and aren't allowed to do.Questions We Answer in This EpisodeHow has the barrier to creating convincing deepfakes changed in the last six years?What are the most common deepfake fraud vectors hitting businesses and consumers right now?How does Reality Defender detect AI-generated media without storing any biometric data?What does deepfake defense look like as agentic AI becomes mainstream?Key TakeawaysVoice cloning now requires less than five seconds of audio and runs locally on consumer hardwareDeepfake fraud spans a wide range—from grandparent scams to fake job applicants to wire transfer hijackingReal-time detection can plug directly into tools organizations already use, with no new workflow requiredAgentic AI is creating a new category of identity challenge—and the defenses are already being builtThe deepfake threat isn't coming—it's already here, hitting call centers, recruiting pipelines, and financial institutions every day. Whether you're a developer looking to integrate detection into your stack or a security leader trying to get ahead of the next wave, this conversation is a essential listen.ResourcesReality DefenderBen ColmanReality Defender on LinkedInFollow Reality Defender on XCyberProofLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (00:35) - Meet Ben Colman, Reality Defender (01:23) - Ben’s Beginnings (02:36) - Changing Landscape (03:57) - What It Looks Like Today (05:07) - Differences (06:16) - Main Ways Fraud’s Committed (09:21) - Way to Tackle It (11:07) - Distinguishing the AI (13:14) - Response Time (14:09) - Recommended Next Steps (15:55) - Where It’s Heading (19:21) - How to Use as Organization (20:52) - Developer Community (22:23) - Audio and Video (23:34) - Risk Assessment (24:41) - Prevalence (26:09) - Wrap Up

When “Ship Fast” Meets “Secure by Design” in AI AppsAI-driven development is moving at breakneck speed—and attackers are taking advantage of the shortcuts. In this episode of Cyber Sentries: AI Insights for Cloud Security, host John Richards sits down with Gaetan Ferry, security researcher at GitGuardian, to unpack how modern AI tooling, MCP servers, and cloud platforms are reshaping the security landscape. The core problem: the same agentic workflows that boost productivity can also multiply identities, credentials, and blast radius if something goes wrong.After John and Gaetan set the stage, Gaetan walks through a real-world-style vulnerability chain involving smithery.ai, an MCP server registry/hosting platform. It’s a practical look at how “classic” web issues can still show up in brand-new AI ecosystems—and how one small weakness can cascade into bigger supply chain risk. Along the way, they explore why secret sprawl is accelerating, what attackers are hunting for, and why observability is becoming as essential for identities and tokens as it is for infrastructure.Why MCP Servers, OAuth, and Secret Sprawl Are CollidingA big theme is the tension between usability and security: teams want agents that can “do everything,” which often means broad permissions and long-lived credentials. Gaetan explains why adopting OAuth is directionally better than static API keys, but still not a silver bullet in a world where agents need delegated access and tokens inevitably “live somewhere.” John pushes on what builders can do now—especially when new frameworks (and new hype cycles) keep resetting hard-won security practices.The conversation lands on pragmatic guidance: reduce blast radius where you can, inventory identities and secrets, and invest in observability so you can respond fast when—not if—credentials leak. Note: This episode discusses breach scenarios and exploitation chains—be thoughtful about sharing internal security details and incident response specifics.Questions We Answer in This EpisodeHow can a simple web flaw turn into an AI supply chain attack through MCP server hosting?Why doesn’t OAuth automatically “solve” agent security and credential risk?What does “limiting blast radius” look like when agents need broad permissions to be useful?How can observability help you detect and respond to secrets sprawl across AI tools?Key TakeawaysTreat MCP servers and agent integrations like critical supply chain dependencies—because they are.Prefer short-lived, scoped credentials (OAuth when possible), but plan for token theft scenarios anyway.Reduce blast radius with least privilege, separation of duties, and segmented agent access.Build identity and secret observability so you can triage and remediate leaks quickly.The Bottom Line for AI Security Teams in 2026If you’re experimenting with MCP servers or rolling out agentic workflows, this episode is a timely reminder that fundamentals still win. John and Gaetan make the case that “moving fast” doesn’t have to mean accepting unlimited credential risk—you can ship quickly while still tightening scopes, tracking identities, and watching where secrets spread. Tune in for the real-world examples and the practical mindset shift that helps teams stay productive without becoming the next supply chain headline.Links & NotesGitGuardianConnect with Gaetan on LinkedInState of Secrets Sprawl Report 2025State of Secrets Sprawl Report 2026 (coming later in March!)CyberProofLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:07) - Meet Gaetan Ferry (02:19) - Attacks (03:17) - Vulnerabilities (07:38) - One-Off or Widespread? (10:20) - Recommendations to Avoid (14:19) - Exploiting (16:50) - Resolving (23:13) - Path Forward (30:53) - Impact (34:48) - Year of Supply Chain Attacks (35:51) - Wrap Up

The Evolution of Identity Security in the Age of AIIn this episode of Cyber Sentries, John Richards sits down with Jasson Casey, CEO and co-founder of Beyond Identity, to explore the intersection of identity security, AI, and enterprise risk management. As organizations rapidly adopt AI tools and agents, the fundamental challenges of identity security are evolving—requiring both new approaches and a return to core principles.Identity: The Foundation of Modern SecurityJasson explains how identity has become the root cause of most security incidents, with identity-based failures accounting for 80% of security tickets. The conversation explores how AI is transforming every role in modern organizations, while highlighting the security implications of this rapid adoption.Key Takeaways:Identity security is fundamental to managing AI risk in enterprisesTraditional security concepts still apply but require new implementation approachesOrganizations need to track data flow and permissions across AI systemsLooking AheadAs AI adoption accelerates, organizations must balance innovation with security. Through proper identity management and understanding of data flow, enterprises can prevent most security incidents while embracing the transformative potential of AI technologies.Links & NotesBeyond IdentityAI SolutionsConnect with Jasson Casey on LinkedInConnect with Jasson Casey on XCyberProofLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:02) - Meet Jasson Casey (02:51) - Regrets? (08:19) - Friction Point (10:28) - Identity (17:08) - Adoption (22:17) - The Hallmark of Network Security (28:10) - Paint Analogy (31:17) - Threats (34:08) - Visualization Tool (35:13) - Their Work in This Space (37:05) - Learning More (37:36) - Wrap Up

SIEM Speed Without the Sprawl—DataBahn’s Take on Security Data PipelinesIn this Cyber Sentries: AI Insights for Cloud Security episode, host John Richards sits down with Dina Kamal, Chief Revenue Officer at DataBahn, to tackle a familiar cloud security problem: teams can’t get the right data into the SIEM fast enough, and when they do, costs and noise spike. After the introductions, John and Dina dig into why data integration and parsing often consume most of the timeline in SIEM projects—and how a security data pipeline layer can compress onboarding from months to weeks.They also explore what “doing more with less” looks like in a modern SOC: filtering and routing data based on detection value, preserving what’s needed for compliance, and keeping flexibility for SIEM migrations. Dina’s bigger point is that AI only becomes truly useful when it’s paired with domain expertise and real operational context—otherwise it’s easy to end up with impressive-looking outputs that don’t hold up under investigation pressure.Questions We Answer in This EpisodeWhy do SIEM projects stall on data onboarding, and what speeds it up?How can you cut SIEM ingestion costs without weakening detections?What does owning your security data change during SIEM migrations?Where does AI help most in SOC workflows, and where do guardrails matter?Key TakeawaysData pipelines remove SIEM “plumbing” bottlenecks by automating collection, parsing, and transformation.Cost reduction works best when you filter by security value, not just by volume.Decoupling data collection from the SIEM reduces lock-in and simplifies vendor changes.AI is strongest when guided by security context and experienced practitioners.The throughline is practical: better detections and faster investigations start upstream with intentional data handling. By treating the SIEM as a high-value analytics destination instead of a dumping ground, teams can regain capacity, reduce noise, and keep options open as tools and vendors change. And when AI is applied to the right parts of the workflow—with clear constraints and real-world context—it can accelerate outcomes without compromising trust.Links & NotesDataBahnConnect with Dina Kamal on LinkedInLearn more about CyberproofGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:02) - Meet Dina Kamal (03:14) - Data Pipeline Management (05:55) - The Target (07:32) - Changing Vendors (08:34) - No Storage (09:31) - Why People Need It (13:09) - Ahead of the Curve (19:54) - Capturing the Data (23:02) - Useful Data (26:02) - More with Less (27:03) - Visibility (29:40) - When to Start (31:04) - Wrap Up

Bridging the AI Security Gap—Inside the Rise of Non‑Human IdentitiesIn this episode of Cyber Sentries from CyberProof, host John Richards sits down with Idan Gour, co-founder and president of Astrix Security, to unpack one of today’s fastest-emerging challenges: securing AI agents and non-human identities (NHIs) in the modern enterprise. As companies rush to adopt generative-AI tools and deploy Model Context Protocol (MCP) servers, they’re unlocking incredible automation—and a brand-new attack surface. Together, John and Idan explore how credential leakage, hard-coded secrets, and rapid “shadow-AI” experimentation are exposing organizations to unseen risks, and what leaders can do to stay ahead.From Non‑Human Chaos to Secure‑by‑Design AIIdan shares the origin story of Astrix Security—built to close the identity-security gap left behind by traditional IAM tools. He explains how enterprises can safely navigate their AI journey using the Discover → Secure → Deploy framework for managing non-human access. The conversation moves from early automation risk to today’s complex landscape of MCP deployments, secret-management pitfalls, and just-in-time credentialing. John and Idan also discuss Astrix’s open-source MCP wrapper, designed to prevent hard‑coded credentials from leaking during model integration—a practical step organizations can adopt immediately.Questions We Answer in This EpisodeHow can companies prevent AI‑agent credentials from leaking across cloud and development environments?What’s driving the explosion of non‑human identities—and how can security teams regain control?When should organizations begin securing AI agents in their adoption cycle?What frameworks or first principles best guide safe AI‑agent deployment?Key TakeawaysStart securing AI agents early—waiting until “maturity” means you’re already behind.Visibility is everything: you can’t protect what you don’t know exists.Automate secret management and avoid static credentials through just‑in‑time access.Treat AI agents and NHIs as first‑class citizens in your identity‑security program.As AI adoption accelerates within every department—from R&D to customer operations—Idan emphasizes that non‑human identity management is the new frontier of cybersecurity. Getting that balance right means enterprises can innovate fearlessly while maintaining the integrity of their data, systems, and brand.Links & NotesLearn more about Paladin CloudLearn more about Astrix SecurityOpen Source MCP Secret WrapperIdan Gour on LinkedInGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:21) - Meet Idan Gour (03:36) - As the Vertical Started to Grow (06:37) - The Journey (09:24) - Struggling (13:18) - Risk (16:15) - Targeting (17:54) - Framework (20:18) - Implementing Early (21:52) - Back End Risks (24:04) - Bridging the Gap (26:13) - When to Engage Astrix (29:54) - Wrap Up

AI-Powered Compliance: Transforming Enterprise SecurityIn this episode of Cyber Sentries, John Richards speaks with Richa Kaul, CEO and founder of Complyance. Richa shares insights on using modular AI systems for enterprise security compliance and discusses the critical balance between automation and human oversight in cybersecurity.Why Enterprise Security Compliance Matters NowThe conversation explores how enterprises struggle with increasing cyber threats and complex third-party vendor networks. Richa explains how moving from reactive to proactive compliance monitoring can transform security posture, sharing real examples from Fortune 100 companies and major sports organizations.AI Implementation That Prioritizes SecurityRicha details their approach to implementing AI in compliance, emphasizing their commitment to data privacy and security. The company uses a modular AI infrastructure with opt-in features and minimal data access principles, demonstrating how AI can enhance security without compromising privacy.Questions We Answer:How can enterprises shift from reactive to proactive compliance monitoring?What are the key considerations for implementing AI in security compliance?How should companies manage third-party vendor risks in the AI era?What role does employee education play in maintaining security compliance?Key Takeaways:Continuous monitoring beats point-in-time compliance checksModular AI systems offer better security control than all-in-one solutionsThird-party vendor risk requires automated, continuous assessmentHuman elements like training and culture can't be fully automatedLooking Ahead: Security ChallengesThe discussion concludes with insights into future challenges, including quantum computing's impact on security and the growing complexity of AI-related risks. Richa emphasizes the importance of building nimble, configurable systems to address emerging threats.Links & NotesMore About Richa KaulComplyance on LinkedIn and the WebLearn more about Paladin CloudLearn more about CyberproofGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:13) - Meet Richa Kaul from Complyance (02:32) - Areas Needing Security (04:19) - Reactive vs. Proactive (06:17) - Integrating AI (07:59) - AI Compliance Challenges (10:48) - Training Their Models (12:16) - Evaluating Third Parties (15:49) - The Team (19:04) - Looking to the Future (20:44) - How Others Are Implementing AI (24:04) - Creating Capacity (25:44) - Companies Doing It Well (27:25) - When They Don’t Have the Resources (28:50) - Wrap Up

AI Governance in an Era of Rapid ChangeIn this episode of Cyber Sentries, John Richards talks with Walter Haydock, founder of StackAware, about navigating the complex landscape of AI governance and security. Walter brings unique insights from his background as a Marine Corps intelligence officer and his extensive experience in both government and private sectors.Understanding AI Risk ManagementWalter shares his perspective on how organizations can develop practical AI governance frameworks while balancing innovation with security. He outlines a three-step approach starting with policy development, followed by thorough inventory of AI tools, and assessment of cybersecurity implications.The discussion explores how different industries face varying levels of AI risk, with healthcare emerging as a particularly challenging sector where both opportunities and dangers are amplified. Walter emphasizes the importance of aligning AI governance with business objectives rather than treating it as a standalone initiative.Questions We Answer in This Episode:How should organizations approach AI governance and risk management?What are the key challenges in implementing ISO 42001 for AI systems?How can companies address the growing problem of "shadow AI"?What are the implications of fragmented AI regulations across different jurisdictions?Key Takeaways:Organizations need clear AI policies that define acceptable use boundariesRisk management should integrate with existing frameworks rather than create separate systemsCompanies must balance compliance requirements with innovation needsEmployee education and flexible approval processes help prevent shadow AI usageThe Regulatory LandscapeThe conversation delves into emerging AI regulations, from New York City's local laws to Colorado's comprehensive AI Act. Walter provides valuable insights into how organizations can prepare for upcoming regulatory changes while maintaining operational efficiency.Links & NotesStackAwareConnect with Walter on LinkedInLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (00:30) - Walter Haydock from Stackaware (01:13) - Walter’s Background (02:36) - Areas Needing Improvement (03:23) - Integrating AI (04:33) - Stackaware’s Role (06:25) - AI Certification Standard (07:17) - Implementation Challenges (08:28) - Thoughts on Looser Protocols (11:16) - Regulations (13:01) - Approaches (14:57) - Areas of Concern (17:26) - Handling Risk (18:37) - Who Should Own AI Governance (19:43) - Pushback? (21:15) - Proper Techniques (22:26) - What Levels (23:49) - Smaller Companies (25:54) - Ideal Legislation (28:48) - Plugging Walter (29:36) - Wrap Up

Revolutionizing Cloud Security with AI-Powered Distributed SystemsIn this episode of Cyber Sentries, John Richards sits down with Mark Fussell, CEO of Diagrid and co-creator of the Distributed Application Runtime (DAPR). Mark shares insights from his extensive experience in distributed systems and discusses how modern architectures are evolving to incorporate AI capabilities.The Evolution of Distributed ApplicationsMark explains how DAPR emerged from observing common challenges teams faced when building distributed systems. The project, which started in 2018 and became open source in 2019, has grown into a graduated Cloud Native Computing Foundation (CNCF) project used by thousands of companies worldwide. He details how DAPR's component model allows teams to swap infrastructure without changing code, providing crucial flexibility for enterprise systems.Questions We Answer in This EpisodeHow are distributed applications transforming modern software development?What role does security play in distributed architectures?How can organizations integrate AI agents into existing distributed systems?What's next for distributed systems in the age of AI?Key TakeawaysDAPR provides essential building blocks for secure, distributed applicationsWorkflow durability is crucial for enterprise-ready AI agent systemsIdentity-based security principles are fundamental to distributed architecturesThe future of distributed systems will blend traditional microservices with AI agentsThe Future of AI in Distributed SystemsMark discusses Diagrid's Catalyst platform, which helps organizations build enterprise-ready distributed applications with integrated AI capabilities. He emphasizes the importance of security, durability, and workflow management as organizations begin incorporating AI agents into their systems.Links & NotesConnect with Mark on LinkedInLearn more about DAPRDiagridLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (00:30) - Diagrid’s Mark Fussell (01:07) - Meet Mark (04:37) - The Journey (10:55) - New AI Models (15:01) - On the Security Side (16:52) - Where Things Go Next (20:10) - Bringing in New Agentic Models (24:20) - Catalyst (27:12) - Getting in Touch (28:35) - Wrap Up

AI-Powered Cloud Security: From Research Lab to Enterprise RealityIn this episode of Cyber Sentries, John Richards talks with Mohit Tiwari, co-founder and CEO of Symmetry Systems and associate professor at UT Austin, about transforming academic research into practical enterprise security solutions. Mohit shares his journey from academic research to founding a company that's revolutionizing how organizations approach data security in the age of AI.Bridging Academia and IndustryMohit discusses how his research team at UT Austin developed innovative approaches to data security and privacy, working with organizations like NSA, Lockheed, and General Dynamics. Their work led to founding Symmetry Systems in 2020, focusing on operationalizing data flow security across enterprise environments.The Evolution of Data SecurityThe conversation explores how traditional asset-centric security approaches are giving way to data-centric models. Mohit explains how Symmetry Systems helps organizations protect data flows across multiple applications and platforms, making security more efficient and effective than traditional bespoke solutions.Questions We Answer in This Episode:How can organizations move from bespoke security solutions to systematic approaches?What role does AI governance play in modern enterprise security?How can companies effectively manage data security across different AI implementation scenarios?Key Takeaways:Data-centric security approaches are becoming crucial as AI adoption increasesOrganizations need interoperable policy languages for effective AI governancePurpose-built, smaller AI models can be more effective than large, general-purpose onesSecurity solutions must evolve to handle the massive scale of modern enterprise dataLooking Ahead: The Future of AI SecurityThe episode concludes with insights into emerging challenges in AI security, including the need for better business purpose frameworks and advanced detection capabilities for sophisticated attacks like ransomware.ResourcesSymmetry Systems websiteConnect with Symmetry Systems on LinkedInLearn more about Paladin CloudLearn more about CyberproofGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:02) - Meet Mohit (03:06) - Application Examples (08:15) - Key Metrics (10:52) - Effects of AI (14:16) - Environments and Interfaces (16:39) - Tying It Together (18:19) - AI in the Process (22:51) - Model Decisions (25:41) - Research to Project (29:13) - Problems (31:25) - Wrap Up

AI-Powered Identity Verification: Beyond Passwords and into the FutureIn this episode of Cyber Sentries, host John Richards sits down with Michael Engle, co-founder and CSO of 1Kosmos, to explore how AI is revolutionizing identity verification and authentication in cybersecurity. Mike brings decades of experience from Wall Street to modern startups, offering unique insights into the evolution of digital identity protection.The Identity Crisis in Modern SecurityIdentity verification has become the new perimeter in cybersecurity, accounting for 80% of security problems. Mike explains how traditional methods like passwords and basic MFA are failing to meet current security challenges, especially as AI agents become more prevalent in our digital lives. 1Kosmos is tackling this through advanced biometric verification, behavioral analysis, and AI-powered authentication systems.Questions We Answer in This Episode:How is AI changing the landscape of identity verification?What makes biometric authentication more secure than traditional methods?How can organizations transition from password-based to identity-based security?What role do digital wallets play in the future of identity verification?Key Takeaways:Identity verification has replaced perimeter security as the primary security concernAI enables more sophisticated identity verification through behavioral analysis and pattern recognitionBiometric authentication offers a more secure alternative to traditional passwords and MFADigital wallets are emerging as the future of portable, verified identityThe Future of Digital IdentityLooking ahead, Mike discusses 1Kosmos's work on digital wallets and universal identity verification systems. These innovations aim to create reusable, trusted identities that can work across multiple platforms while maintaining security through biometric verification and AI-powered fraud detection.Links & NotesLearn more about CyberproofLearn more about 1KosmosGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:03) - Meet Michael Engle (03:03) - Identity Threat (04:09) - With AI (05:50) - What 1Kosmos Does (12:48) - Adapting with AI (15:42) - Protecting Credentials (26:36) - Passkey Challenges (28:12) - AI-Driven Development (32:18) - What’s Next for 1Kosmos (34:40) - Learning More (35:42) - Wrap Up

AI's Evolution in Security Operations: From Support to CollaborationDoron Davidson, Managing Director of Security Operations at Cyberproof, joins John Richards to explore how AI is transforming security operations and pushing SOC maturity models into new territory. With extensive experience from telecom security to founding SecBI, Doron brings unique insights into the evolution of managed security services.Rethinking Security Maturity ModelsDoron outlines Cyberproof's innovative approach to service maturity, moving beyond traditional frameworks to incorporate AI capabilities. He describes how they've developed a 1-5 scale measuring people, processes, and technology—with quantifiable 20% year-over-year improvement targets.Questions We Answer:How are security operations teams evolving with AI integration?What does SOC maturity look like in an AI-enabled world?How can organizations measure and verify AI's security impact?What role will agentic AI play in future security operations?Key Takeaways:AI is enabling better collaboration between security servicesAutomated investigation has significantly reduced L1 analyst workloadWell-defined processes and KPIs are crucial for successful AI implementationNew maturity levels (6-8) are emerging focused on agentic AI capabilitiesThe Future of Security OperationsThe conversation explores how Cyberproof is moving beyond traditional AI integration toward agentic models where multiple AI agents collaborate across security functions. This shift enables enhanced threat intelligence sharing, automated investigations, and improved visualization of security metrics for stakeholders.Practical Applications and ImpactFrom automating email attack investigations to improving cross-team collaboration, Doron shares concrete examples of how AI is reducing human error while expanding security capabilities. He emphasizes the importance of maintaining human oversight while leveraging AI's strengths.ResourcesLearn more about CyberproofLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (00:33) - Today’s Guest: Doron Davidson (01:32) - Doron’s Background (03:27) - Latest Challenges (05:57) - Honesty Mindset (09:16) - Current AI Strategy (12:23) - Focus Areas (19:43) - Shifting Models (25:04) - What He’s Excited About (26:40) - Maturity Model (28:49) - Wrap Up

AI, Investment, and Security: A Venture Capitalist's PerspectiveSherman Williams, managing partner at AI and Ventures, joins John Richards to explore the intersection of artificial intelligence, cloud security, and venture capital. As a Naval Academy graduate turned investor, Sherman brings unique insights from both military and commercial technology perspectives. His firm focuses on dual-use technologies - innovations that serve both government and commercial applications - making him particularly well-positioned to discuss AI's evolving role in security.The conversation delves deep into how organizations should approach AI implementation, viewing it as a powerful tool rather than a solution in itself. Sherman shares valuable perspectives on the distinction between AI DevTools and application layer AI, and how entrepreneurs should focus on solving specific problems rather than getting caught up in AI hype. The discussion explores critical considerations around open-source versus closed-source models, particularly in sensitive sectors like government, healthcare, and insurance.Questions we answer in this episode:How should organizations approach AI implementation in their security strategy?What's the difference between AI DevTools and application layer AI?How are security concerns shaping the development of AI solutions?Key Takeaways:AI should be viewed as a tool for efficiency and productivity, not a standalone solutionThe best AI implementations focus on solving specific, acute problemsSecurity considerations are driving innovation in both AI development and deploymentThis episode offers essential insights for anyone interested in the future of AI in security and technology development. Sherman's unique perspective, combining military experience with venture capital expertise, provides valuable context for understanding how AI is reshaping the security landscape while highlighting both opportunities and challenges ahead.Links & NotesAIN VenturesFollow Sherman on LinkedInThe 2017 Google Article MentionedSecurity Company MentionedLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (00:34) - Sherman Williams (01:02) - Sherman’s Background (05:26) - AI from the Investment Space (08:23) - Dev Tools or Application Layer AI (12:24) - Security (22:46) - Promising Work in Security (33:59) - Wrap Up

Transforming Cloud Security Through AI and Data FabricDaniel Deeney, CEO and co-founder of Paladin Cloud, joins John Richards to explore how artificial intelligence is revolutionizing cloud security. With extensive experience as an enterprise software CEO and venture capitalist, Deeney brings unique insights from his successful track record of building and scaling cybersecurity companies. After his previous company's acquisition by VMware in 2019, he launched Paladin Cloud to address the growing challenges of managing security across multiple cloud environments.The episode delves deep into the concept of data fabric and its crucial role in modern cybersecurity. Richards and Deeney discuss how organizations struggle with tool proliferation and data overload in cloud security. They explore how Paladin Cloud's innovative approach uses data fabric to unify risk assessment across various security tools while leveraging generative AI for enhanced threat intelligence. The conversation highlights practical solutions for teams dealing with overwhelming security alerts and the challenge of prioritizing threats effectively.Questions we answer in this episode:How can organizations handle the overwhelming amount of security data from multiple tools?What role does generative AI play in modern cloud security?How can teams better prioritize security risks across different environments?Key Takeaways:Data fabric technology enables unified risk assessment across multiple security toolsAI-powered risk scoring helps teams prioritize threats more effectivelySecurity teams need both technological solutions and services support to manage modern threatsThis episode offers invaluable insights for security professionals, DevOps teams, and technology leaders grappling with cloud security challenges. Whether you're dealing with alert fatigue, struggling to prioritize security risks, or looking to understand how AI can enhance your security operations, this discussion provides practical guidance and strategic perspectives on navigating the complex landscape of modern cloud security.Links & NotesLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (01:05) - Meet Daniel Deeney (01:25) - Starting Paladin Cloud (02:53) - The Approach (04:54) - Data Fabric Layer (09:39) - Addressing Pain Points (15:54) - Bringing Data Together and Normalizing (18:52) - Users (20:37) - Other Models (26:02) - Prioritization (29:19) - Customer Service (31:16) - Wrap Up

Diving into the Rise of On-Prem AI and Cloud SecurityIn this episode of Cyber Sentries, host John Richards is joined by Doron Caspin, a Senior Manager of Product Management at Red Hat, and Christopher Nuland, a Technical Marketing Manager at Red Hat. They explore the growing trend of on-premise open source models for running AI and the unique benefits and challenges that come with it. The conversation also touches on how DeepSeek has challenged the big players and validated the value of smaller agentic models.John, Doron, and Christopher dive into the shifting landscape of AI and cloud security. They discuss the trends Red Hat is seeing in the industry, such as the move towards smaller, domain-specific language models and the importance of securing AI workloads in hybrid cloud environments. The guests share insights on the key considerations organizations face when deciding to run AI models on-premises, including compliance requirements and the need to treat AI models with the same level of security as databases.Questions we answer in this episode:What are the benefits and challenges of running AI on-premises?How can organizations secure their AI workloads in hybrid cloud environments?What impact has DeepSeek had on the AI industry?Key Takeaways:On-prem AI offers unique advantages for industries with strict compliance requirementsTreating AI models like databases is crucial for ensuring robust securityThe future of AI is likely to be open source, with smaller, domain-specific models gaining tractionThis episode is a must-listen for anyone interested in the intersection of AI and cloud security. John, Doron, and Christopher provide valuable insights and practical advice for organizations navigating this rapidly evolving landscape. Whether you're a security professional, data engineer, or business leader, you'll come away with a deeper understanding of the trends shaping the future of AI and the steps you can take to secure your AI workloads.Links & NotesTry Red Hat Advanced Cluster Security Cloud ServiceRed Hat Advanced Cluster Security for KubernetesTraining an AI to Conquer Double Dragon: Reinforcement Learning DemoLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (00:31) - Red Hat (01:04) - Meet Christopher and Doron (05:26) - Past to Present (07:54) - Trends in the Approach (12:24) - The Security Side (16:15) - Key Considerations (19:26) - Training and Models (22:33) - Iterations and Shifts (25:36) - Importance of Security Foundations (28:35) - Security in Agent Space (30:00) - Wrap Up

Navigating AI Adoption: From Exploration to ImplementationIn this illuminating episode of Cyber Sentries, John Richards sits down with Jim Wilt, distinguished chief architect at Weave and veteran security practitioner. With decades of experience in emerging technologies since the mainframe era, Jim brings unique insights into how organizations can successfully integrate AI while maintaining robust security practices.The conversation delves deep into a three-phase approach for AI adoption: learning, growing, and landing. Jim emphasizes the importance of experimentation before commitment, challenging the common rush to define use cases before understanding the technology's capabilities. He shares practical examples of how organizations can progress from internal testing to external deployment, while maintaining security at each stage. The discussion explores how AI isn't about replacement but enhancement - whether for individual roles or organizational processes - and why adaptability in implementation is crucial for success.Questions we answer in this episode:How should organizations approach their initial AI adoption?What's the optimal timeline for moving from experimentation to implementation?When and how should security measures be integrated into AI initiatives?Key Takeaways:"Replaceable architecture" is becoming more critical than "reusable architecture" in the AI eraOrganizations need 9-18 months of internal testing before external AI deploymentSecurity measures should scale up gradually, from minimal during learning to comprehensive in productionThis episode provides invaluable guidance for any organization navigating AI adoption. Jim's practical, experience-based insights cut through the hype, offering a clear roadmap for sustainable AI integration while maintaining security integrity. Whether you're just starting your AI journey or looking to refine your existing approach, this discussion offers actionable strategies for success.Links & Notes‘What Air Canada Lost In ‘Remarkable’ Lying AI Chatbot Case’CIO.com: From risk to reward: Mastering the art of adopting emerging technologiesGenerative AI (GenAI) – A PrimerGenAI and the Human ExperienceReplaceable is the New ReusableApplied AIConnect with Jim on LinkedInLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (00:55) - Meet Jim Wilt (01:46) - Jim’s Background (03:59) - Where to Start (13:28) - Public vs. Private Models (17:52) - Time in Growth Period (18:48) - Use Cases (21:57) - Transitioning to External Use (29:06) - Scaling from Personal to Organizational (31:52) - Safeguarding (37:21) - Flexibility (38:34) - Wrap Up

Bel Lepe Reveals How AI Reduces Security Risks By Removing the Human ElementIn this episode of Cyber Sentries, host John Richards is joined by Bel Lepe, Co-founder and CEO of Cerby, to explore how removing the human factor through automation can dramatically decrease an organization's attack surface. John and Bel dive into the transformative potential of AI in identity and access management, especially for applications that don't support modern security protocols.Bel shares his insights on the current state of identity security and how Cerby is tackling the challenge of securing disconnected apps at scale. He explains how generative AI enables Cerby to build and maintain integrations for thousands of apps without relying on standards. The discussion also touches on emerging trends in identity, including the fragmentation of identity across multiple platforms and the growing threat of AI-powered impersonation attacks.Questions we answer in this episode:How can AI reduce security risks by removing the human element?What are the key challenges in securing apps that don't support modern identity protocols?How will the rise of AI shape the future of identity security?Key Takeaways:The majority of security incidents are caused by human errorAI allows custom integrations to be built at scale without relying on standardsMulti-factor authentication is crucial for protecting against emerging threatsWhether you're a security professional looking to stay ahead of the curve or a business leader seeking to understand the impact of AI on your organization's security posture, this episode is packed with valuable insights. Tune in to learn how AI is revolutionizing identity and access management and what you can do to safeguard your organization in the face of evolving threats.Links & NotesLearn more about CerbyLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (01:03) - Meet Bel Lepe (02:42) - Validating the Problem (04:07) - The Problem (06:32) - Their Approach (08:24) - Scaling (10:38) - Looking to the Future (15:32) - The Future of Identity (22:25) - Building Better Awareness (23:46) - Wrap Up

Securing the Digital Future with Former Fortune 500 CISO Tim YoungbloodJohn Richards welcomes Timothy Youngblood, a four-time Fortune 500 CISO and current CISO in Residence at Astrix Security, to discuss the evolving landscape of cybersecurity leadership. With experience at Dell, Kimberly Clark, McDonald's, and T-Mobile, Tim brings unique insights into how security leadership must adapt to emerging threats while maintaining operational effectiveness.The conversation explores Tim's journey from Dell's first CISO to handling security across diverse industries. John and Tim delve into fascinating security incidents, including a notable McFlurry API DDoS attack at McDonald's, demonstrating how modern security challenges can emerge from unexpected places. The discussion shifts to the critical topic of non-human identity attacks and the growing importance of managing machine identities in cloud environments. Tim shares his perspective on how AI is reshaping security practices and why education remains fundamental to effective security programs.Questions we answer in this episode:How do companies integrate security during acquisitions and mergers?What unique challenges do global companies face in cybersecurity?How should organizations approach non-human identity security?Key Takeaways:Security leadership requires strong business acumen alongside technical expertiseEducation and culture-building are crucial for successful security programsThe scale of non-human identities poses a major security blind spot for many organizationsThis episode offers invaluable insights for security professionals navigating complex organizational challenges while adapting to emerging threats. Whether you're a seasoned CISO or aspiring security leader, Tim's practical experiences and strategic approaches provide actionable wisdom for building robust security programs in any environment.Links & NotesSecuring Non-human IdentitiesFind Tim on LinkedInLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:12) - Meet Tim Youngblood (08:07) - Challenges (11:03) - Change Management (11:37) - Transitioning to Next Role (16:21) - McDonald’s (19:57) - Flexibility (21:50) - Handling New Challenges (26:11) - Non-Human Identity Attacks (33:55) - Wrap Up

Open Source AI: Transparency, Sovereignty, and Who Controls the DataIn this episode of Cyber Sentries, host John Richards is joined by JJ Asghar, an Open Source Champion and Developer Advocate at IBM. They explore the importance of open source in the AI world, how transparency can allow for AI sovereignty, and why we should care about who controls the data.JJ shares his journey into the AI space at IBM and his strong opinions formed from working on open source AI projects. The discussion delves into the differences between mainstream closed-source AI models and the emerging open-source alternatives, highlighting the privacy and trust aspects that are becoming increasingly important, especially outside the United States.Questions we answer in this episode:How does open source fit into the recent surge of AI?What are the benefits of open-source AI models compared to closed-source ones?Why is AI sovereignty important, and how does it relate to open source?The conversation covers the challenges of building and running AI models, the compute resources required, and how open-source approaches can provide more transparency and control. JJ explains the concept of AI sovereignty, where countries and organizations want to run AI within their borders and under their own rules and restrictions. This brings up issues of hardware accessibility and the lifecycle of AI models.Key Takeaways:Open-source AI allows for greater transparency and trust compared to closed-source modelsAI sovereignty is becoming increasingly important for countries with strict privacy lawsThe lifecycle of AI involves training, fine-tuning, and inferencing, each with different compute requirementsWhile open source offers many benefits, the discussion also touches on the challenges, such as the potential for model poisoning and the current lack of genealogy in AI models. Despite these hurdles, open source remains a powerful force in the AI world, with the potential to provide more eyes on the code and faster problem resolution.This episode offers valuable insights into the complex world of AI, the role of open source, and the importance of data control and transparency. Whether you're a developer, a security professional, or simply interested in the future of AI, this conversation provides a thought-provoking look at the challenges and opportunities ahead.Links & NotesIBM's open source foundational model GraniteGranite Foundation Models PaperHugging FaceIBM's coding assistance projectInstructLabCrew AIAI Sovereignty PaperLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (00:55) - Meet JJ Asghar (03:17) - Working with AI (04:29) - AI and Open Source (10:31) - Approach (14:38) - Sovereignty (18:20) - Inferencing (20:47) - Black Box Situation (30:10) - Weighing the Differences (35:09) - Timeline (40:39) - Finding JJ (42:06) - Communities (44:49) - Wrap Up

Decoding Zero Trust Security for Cloud Native EnvironmentsIn this episode of Cyber Sentries, John Richards welcomes Zack Butcher, Founding Engineer at Tetrate, to explore the critical components of zero trust security for cloud native and microservice environments. Zack, with deep expertise from his time at Google and work with NIST, shares practical insights on achieving a zero trust posture.John and Zack dive into the fundamental mindset shift required for zero trust - moving from implicit to explicit trust. They break down the five key policy checks that define runtime zero trust, and how these controls can enable identity-based segmentation. Zack illuminates how this approach allows organizations to boost assurance while strategically relaxing painful network-level constraints.Questions we answer in this episode:• What does Zero Trust really mean in practice?• How can organizations adopt a Zero Trust mindset?• What role does a service mesh play in Zero Trust?Key Takeaways:• Zero Trust requires making all trust explicit• 5 key runtime policy checks define a Zero Trust posture• Identity-based policies boost assurance and agilityWhether you're wrestling with Zero Trust definitions, microservice security, or cloud native challenges, this episode delivers a wealth of battle-tested wisdom. Zack's clear explanations and examples, combined with John's knack for extracting practical takeaways, make this a must-listen for anyone navigating the complex world of cloud native security.Links & NotesZack on LinkedInSecurity Strategies for Microservices-based Application Systems (Sidebar has the A-D publications)A Zero Trust Architecture Model for Access Control in Cloud-Native Applications in Multi-Cloud EnvironmentsTetrate AcademyLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (01:01) - Meet Zack (04:55) - Reflecting on the Journey (05:46) - Deep on Security Aspect (09:52) - Zero Trust and Definitions (15:35) - Consensus (18:09) - Availability and Assurance (22:28) - Driving Growth (25:44) - How AI Can Be Used for Security (30:07) - Links and Finding Zack (30:36) - Wrap Up

Decoding the Language of Machines: AI's Potential to Revolutionize Cloud SecurityIn this episode of Cyber Sentries, host John Richards is joined by Murali Balcha, founder and CTO at Trilio, to explore how AI could transform cloud security by understanding the unique language of machines. Balcha brings over 20 years of experience in IT, particularly in storage systems, to the conversation.Harnessing AI for Proactive SecurityJohn and Murali dive into the potential of AI to enhance cloud security by analyzing the vast amounts of data generated by IT systems. By treating system logs as a language that AI can learn, models could be trained to identify threats and anomalies in real-time, even detecting zero-day attacks that traditional rule-based systems might miss. This shift towards proactive, AI-driven security could significantly reduce the time between a threat emerging and its detection.Questions we answer in this episode:How can AI be applied to cloud security?What advantages does AI offer over traditional rule-based security systems?How can AI models be trained to understand the unique language of machines?Key Takeaways:AI has the potential to revolutionize cloud security by learning the language of machinesAI models can identify threats and anomalies in real-time, even detecting zero-day attacksShifting towards proactive, AI-driven security could significantly enhance threat detection and response timesThis episode offers valuable insights into the cutting-edge applications of AI in cloud security. Listeners will gain a deeper understanding of how machine learning can be harnessed to protect their systems and data, as well as a glimpse into the future of proactive, intelligent security solutions.Links & NotesCheck out Murali’s blogFind Murali on LinkedInLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (00:56) - Meet Murali Balcha (03:29) - AI’s Evolution (06:06) - Transferring Data (14:43) - How Trillio’s Looking at AI (23:36) - Wrap Up

Ori Bendet Shares Insights on AppSec and Managing AI RisksIn this episode of Cyber Sentries, John Richards is joined by Ori Bendet, VP of Product Management at Checkmarx, a leader in application security. They explore the critical role of application security in today's digital landscape and discuss strategies for managing the risks and opportunities presented by the rapid adoption of AI in software development.Ori shares his journey into the cybersecurity industry and offers advice for those transitioning into the field. He emphasizes the importance of focusing on areas that are business-critical, such as application security, as more companies become software-driven. Ori also discusses the shift in application security from finding every vulnerability to prioritizing the most critical risks, given the accelerated pace of development and deployment.Questions we answer in this episode:• How can organizations effectively prioritize application security risks?• What are the key challenges and opportunities presented by AI in software development?• How should security teams adapt their practices to manage AI-generated code?The conversation delves into the disruptive impact of AI on software development and the new types of risks it introduces, such as AI hallucination, data poisoning, and prompt injection. Ori stresses the importance of a layered approach to securing AI-generated code and the need for organizations to assess their specific use cases and risks before defining policies and tools.Key Takeaways:• Application security is critical as companies become increasingly software-driven.• Focus on prioritizing the most critical risks rather than trying to find every vulnerability.• Adopt a layered approach to securing AI-generated code and keep the human in the loop.This episode offers valuable insights for anyone looking to understand the evolving landscape of application security and the impact of AI on software development. Ori's expertise and practical advice make this a must-listen for security professionals, developers, and business leaders alike.Links & NotesCheck out CheckmarxThe Stanford Research on Secure Code Generated by GenAI SolutionsLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (00:56) - Meet Ori Bendet (02:31) - Advice When Thrust Into Cyber Security (04:34) - Application Security (07:37) - Opportunities for Growth (09:58) - Shift to Business Risk (12:28) - Making Assessment (16:08) - Core Cybersecurity Principals (20:31) - Restrictions Needed? (23:17) - Using AI in Checkmarx (27:57) - Give Them What Matters Most (29:40) - Wrap Up

Kubernetes, AI, and Edge Computing: A Powerful CombinationIn this episode of Cyber Sentries, John Richards is joined by Saad Malik, CTO and co-founder of SpectroCloud, to explore the intersection of Kubernetes, AI, and edge computing. Saad shares his insights on how these technologies are transforming various industries and the challenges organizations face when implementing them at scale.Unlocking the Potential of Kubernetes and AIThroughout the episode, John and Saad discuss the growing adoption of Kubernetes and AI across different environments, from public and private clouds to data centers and edge locations. Saad explains how SpectroCloud's platform simplifies the management of Kubernetes clusters, enabling organizations to leverage the unique capabilities of each environment while maintaining consistency and security.Questions we answer in this episode:How can organizations manage Kubernetes across diverse environments?What are the primary use cases for edge computing?How can developers scale up their Kubernetes deployments faster?Key Takeaways:Templating Kubernetes configurations and integrations simplifies management at scale.Edge computing enables data pre-processing, unique experiences, and robotics applications.AI operations (AIOps) can provide actionable insights and automate Kubernetes management.The conversation also touches on the cultural shift required to embrace AI-driven automation in Kubernetes management. Saad suggests that organizations will gradually adopt these technologies as they gain confidence in the recommendations and actions taken by AI systems.This episode offers valuable insights for anyone interested in the future of Kubernetes, AI, and edge computing. Whether you're a developer, platform engineer, or IT decision-maker, you'll come away with a better understanding of how these technologies can be leveraged to drive innovation and efficiency in your organization.Links & NotesLearn more about SpectroCloudLearn more about Paladin CloudGot a question? Ask us here! (00:04) - Welcome to Cyber Sentries (00:57) - Saad Malik and Spectral Cloud (02:33) - Environments (04:29) - Spread (06:06) - Edge Adoption (08:47) - AI Adoption (12:06) - Scaling Up Faster (15:36) - Security (18:20) - Integrating AI (23:44) - Ownership Models (25:32) - Wrap Up

Unlocking the Power of AI in DevSecOpsIn this episode of Cyber Sentries, host John Richards sits down with John Bush, solutions architect at GitLab, to explore how artificial intelligence is transforming the day-to-day lives of developers. Bush, who has been coding since childhood, shares his insights on how AI is becoming embedded into every aspect of the DevSecOps pipeline, from writing code to identifying and remediating security vulnerabilities.John and Bush dive deep into GitLab's AI-powered features, collectively known as Duo, which are sprinkled throughout the software development process. They discuss how these features enhance productivity, automate monotonous tasks, and provide valuable insights to both developers and business users alike. Bush also sheds light on the importance of human oversight in the AI-assisted development process, emphasizing the need for thorough code reviews and security scans.Questions we answer in this episode:How is AI changing the daily work of developers?What are some real-world use cases for AI in the DevSecOps pipeline?How can organizations ensure the security and reliability of AI-generated code?Key Takeaways:AI is becoming an integral part of the entire software development lifecycleDevelopers must still carefully review and vet AI-generated code before deploymentGitLab's AI gateway allows routing requests to the most appropriate AI modelsBush provides a fascinating look at the evolution of DevSecOps, stressing the importance of considering security throughout the development process rather than as an afterthought. He explains how GitLab's AI-powered features, such as vulnerability scanning and automated remediation, help developers efficiently identify and fix security issues early on, saving time and resources in the long run.This episode is a must-listen for anyone interested in the cutting-edge intersection of AI and DevSecOps. Whether you're a seasoned developer, a security professional, or simply curious about the future of software development, you'll come away with valuable insights and a clearer understanding of how AI is revolutionizing the industry.Episode NotesLinks & NotesFind John Bush on LinkedInFind John Bush on XTry GitLab DuoLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (00:58) - About John Bush (03:58) - Moving to GitLab (05:30) - Solution Architects (06:40) - Duos AI Solutions (10:26) - Context (12:17) - Switching Models (13:58) - Best Practices (17:51) - Policy Capability (22:37) - Remediate the Vulnerabilities (23:59) - Dev Sec Ops in This Ecosystem (26:21) - Organization Approaches (28:55) - Level of Knowledge Required (31:09) - Finding John (32:14) - Wrap Up

On this episode, Paladin Cloud’s CEO and co-founder Dan Deeney steps into John Richards’ shoes to play host! He welcomes cybersecurity veteran Mike Crowe to the show. With over 30 years of experience as CIO of Colgate-Palmolive, Mike provides unique insight into the evolution of threats, strategies for defense, and trends that keep CISO’s up at night.Dan and Mike explore the increasingly complex threat landscape companies face today. From expanding digital footprints and geopolitical instability empowering nation-state attacks, the challenge grows for security teams. However, new tools also emerge to help lighten the load, such as automation that prioritizes risks and enables efficient remediation across global organizations.The conversation dives into specific trends like AI and how guardrails must develop alongside new capabilities. Open source models offer both risks and opportunities when thoughtfully incorporated into private LLMs. Throughout, Mike stresses finding what you don't know through proactive testing as the best way to stay ahead of attackers.Questions we answer in this episode:What are the top threats keeping CISOs up at night?How can security and DevOps teams better collaborate to reduce risks?Key Takeaways:Continually evolve defenses as the threat landscape grows ever more complexAutomation and integration are critical to managing overwhelming workloadsChallenge your security assumptions through ethical offensive testingWith Mike's wealth of practical experience, this episode provides valuable strategic perspective on cybersecurity that both new and seasoned professionals can apply to strengthening their own organizations' posture. Listeners will gain insights on current realities and where the industry is heading to stay ahead of evolving dangers.Links & NotesLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (00:23) - Paladin Cloud CEO Dan Deeney Talks With Mike Crowe (00:51) - Meet Mike Crowe (02:01) - Overall Threat Landscape’s Evolution (03:55) - Example Threat (05:44) - AI (08:47) - Open Source (10:18) - Trends and Strategies in Defense (12:04) - Risk-Based Prioritization (13:40) - Remediation (16:55) - Ticketing Systems (18:38) - IntegratingTeams (21:57) - Emergence of a Hybrid Team (23:51) - Final Thoughts (27:20) - Wrap Up

Exploring the AI-Powered Future of Cloud Security with Thomas JohnsonOn this episode of Cyber Sentries, host John Richards interviews Thomas Johnson, CTO and co-founder of Multiplayer, about how AI is transforming cloud security. As AI capabilities rapidly advance, Thomas provides insights into how engineering teams can leverage AI to enhance workflows, generate code, and convert basic sketches into functional systems.John and Thomas dive into key questions surrounding AI ethics, choosing open source vs proprietary models, and best practices for handling sensitive data. Listen in to hear Thomas' advice for developers looking to integrate AI into their tech stacks.Questions we answer in this episode:How are dev teams currently using AI like Copilot?What are the main differences between neural networks and other AI?What security risks exist with generative AI models?Key TakeawaysFocus on choosing the right problem and having clean, quality data.Open source models offer more control compared to proprietary models.Do not put sensitive data into generative models.This fascinating discussion explores how AI is transforming cloud security and development workflows. Thomas provides practical insights into leveraging AI's immense potential while avoiding pitfalls. Whether you're an engineering leader or a developer new to AI, this episode offers an enlightening look at the AI-powered future of tech.Links & NotesMultiplayerLearn more about Paladin CloudGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (00:22) - Meet Thomas Johnson (01:02) - AI Background (01:58) - Neural Networks (02:47) - Current Buzz (04:43) - Integrating AI (07:41) - Improving AI (10:57) - Think About the Problem and Data (12:25) - If Data Is the Problem (14:00) - Securities and Access (15:50) - RAG Model (17:52) - Open Source v. Proprietary (19:20) - Training and Inference Side (20:35) - Multiplayer (21:43) - Wrap Up

John sits down with Shreyans Mehta, CTO and co-founder of Cequence Security, to discuss how AI and machine learning can be applied to improve cloud security. They provide valuable insights for security teams looking to leverage AI to protect their cloud environments and applications.The conversation focuses on using AI for security use cases like detecting anomalies and suspicious behavior, identifying misconfigurations, and automating response. Shreyans shares real-world examples of how Cequence Security has developed AI models to analyze network traffic, APIs, logs, and other data sources to detect threats targeting cloud applications and infrastructure.Questions we answer in this episode:How can AI improve visibility across cloud environments?What are some common use cases for AI in cloud security?How can AI help overburdened security teams?Key Takeaways:AI excels at detecting subtle anomalies and identifying emerging threats based on learned patterns.AI models must be continuously trained on new data to remain effective as attacks evolve.AI augments human analysts by automating tedious tasks so they can focus on higher-value security activities.An advantage businesses have in the AI arms race with attackers is being able to train their AI on their unique user activity patterns.This insightful discussion highlights the transformative potential of AI to improve threat detection, investigation, and response. Security teams looking to apply AI can come away with a better understanding of where to start and how to build an effective AI strategy. John and Shreyans explore key considerations around data quality, model accuracy, and responsible AI practices.Overall, this episode delivers practical guidance to help security leaders successfully navigate the AI landscape. Listen in to learn how to harness the power of AI to advance your cloud security program.Links & NotesPaladin CloudCequenceGot a question? Ask us here!Got a question about cybersecurity, AI, or something else related? Ask us here, and we'll get to it in a future episode! (00:00) - Welcome to Cyber Sentries (00:22) - Meet Shreyans Mehta (27:06) - Wrap Up

Exploring the Transformative Potential of AI for Cloud SecurityIn this episode of Cyber Sentries, host John Richards speaks with Shawn Anderson, an expert in cybersecurity and current CTO at Boston Meridian. They have an insightful discussion about how artificial intelligence is transforming cloud security.Shawn shares his valuable perspective from years of experience leading security initiatives for major corporations. He and John dive into topics like using AI to process massive amounts of data and telemetry, enabling new security capabilities. They also talk about how identity has become cybersecurity's new perimeter.Key themes from their conversation:AI allows security teams to analyze data at a scale not possible for humans, identifying risks and vulnerabilities more quickly.With cloud computing, the focus needs to be on protecting data itself, not just traditional network perimeters.Identity is central - knowing the user and device accessing data is critical for zero trust security.Compliance regulations help incentivize robust cybersecurity programs and controls.AI models need transparency, accountability, and governance to avoid misuse.Questions we answer in this episode:How can AI transform cloud security?What can we learn from past technological shifts like cloud adoption?How does identity enable zero trust security?Key Takeaways:AI enables security teams to find the most critical risks to prioritize.Mindsets need to evolve as new technologies emerge.Governance and accountability are crucial when applying AI.This insightful episode explores how AI is transforming cloud security and identity management. Shawn provides an expert viewpoint on applying AI securely and responsibly. Any cybersecurity or technology leader will gain valuable perspectives from this discussion.Links & NotesPaladin CloudBoston MeridianSean Anderson's blogGot a question? Ask us here!Got a question about cybersecurity, AI, or something else related? Ask us here, and we'll get to it in a future episode! (00:00) - Welcome to Cyber Sentries (00:57) - Meet Shawn Anderson (04:09) - Cybersecurity and AI (06:32) - Identifying Exploitability (09:45) - Identity and Security (12:06) - How to Secure (14:16) - New Approaches? (16:58) - Accountability (22:54) - Exciting Times (26:03) - Finding Shawn (28:39) - Wrap Up

Navigating the AI Security Landscape with Somesh JhaIn this Cyber Sentries episode, host John Richards interviews AI expert Somesh Jha on using AI for security. They discuss the promise and perils of AI in cybersecurity, best practices for implementation, challenges with fine-tuning models, and adopting a multi-agent approach.Jha provides insights on the potential of AI to transform cloud security through automating tasks like intrusion detection. However, attackers could also weaponize AI for large-scale spear phishing. As the technology matures, it remains unclear exactly what will be possible. The episode covers common mistakes like applying AI too broadly, the need for careful benchmarking to avoid hallucinations, the large data requirements for fine-tuning models, and the benefits of a multi-agent framework.Questions You May HaveHow can AI be used for good and bad in cybersecurity?What are some common mistakes when applying AI to security?How can we evaluate if an AI model is working well for security?Key TakeawaysAI can automate spear phishing at scale, but also help detect intrusionsStart with a narrow security problem before expanding AI to broader onesCareful benchmarking is crucial to evaluate AI security toolsBeware of AI hallucinations - grounding techniques can helpFine-tuning AI models requires large datasets to work wellAdopt a multi-agent approach when building AI applicationsJha advises starting with a focused security use case and doing careful benchmarking to demonstrate value before expanding AI more broadly. He notes the challenges of fine-tuning models with limited data. Jha explains how Langroid is designed around a multi-agent approach for maintainable and extensible AI code.This episode provides insights for security teams on leveraging AI responsibly, with practical advice on implementation pitfalls. Jha offers perspectives on realizing the future potential of AI in cybersecurity. His expertise provides a useful guide for applying AI to security effectively.Links & NotesPaladin CloudLangroidGot a question? Ask us here! (00:00) - Welcome to Cyber Sentries (32:45) - Wrap Up

Welcome to Cyber Sentries, an exciting new podcast from Paladin Cloud exploring the transformative potential of AI for cloud security.Each episode, host John Richards will be speaking with visionary thought leaders, pioneering developers, and cybersecurity experts about how artificial intelligence is reshaping the future of cloud security.Expect mind-expanding insights, lively debates, and cutting-edge discoveries that will change how you think about AI and security. In line with our open-source-first philosophy, we also want to hear from you, our listeners. We’re looking forward to getting thoughts and questions from you and even suggestions for guests you’d like to hear on the show. So plug in and get ready for an illuminating journey into the future of AI and cloud security. The first episode launches on December 13th. Be sure to subscribe now on your favorite podcast app so you don't miss it! Cyber Sentries, AI Insights to Cloud Security.Learn more about Paladin Cloud at paladincloud.io!