The Evolution of Identity Security in the Age of AI

In 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 Security

Jasson 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 enterprises
• Traditional security concepts still apply but require new implementation approaches
• Organizations need to track data flow and permissions across AI systems

Looking Ahead

As 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 & Notes

• Beyond Identity
• AI Solutions
• Connect with Jasson Casey on LinkedIn
• Connect with Jasson Casey on X
• CyberProof
• Learn more about Paladin Cloud
• Got a question? Ask us here!

• (00:04) - Welcome to Cyber Sentries
• (01:26) - Meet Jasson Casey
• (03:15) - Regrets?
• (08:43) - Friction Point
• (10:52) - Identity
• (17:32) - Adoption
• (22:41) - The Hallmark of Network Security
• (28:34) - Paint Analogy
• (31:41) - Threats
• (34:32) - Visualization Tool
• (35:37) - Their Work in This Space
• (37:29) - Learning More
• (38:00) - Wrap Up

SIEM Speed Without the Sprawl—DataBahn’s Take on Security Data Pipelines

In 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 Episode

• Why 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 Takeaways

• Data 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 & Notes

• DataBahn
• Connect with Dina Kamal on LinkedIn
• Learn more about Cyberproof
• Got 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

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Bridging the AI Security Gap—Inside the Rise of Non‑Human Identities

In 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 AI

Idan 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 Episode

• How 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 Takeaways

• Start 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 & Notes

• Learn more about Paladin Cloud
• Learn more about Astrix Security
• Open Source MCP Secret Wrapper
• Idan Gour on LinkedIn
• Got a question? Ask us here!

• (00:04) - Welcome to Cyber Sentries
• (01:47) - Meet Idan Gour
• (04:02) - As the Vertical Started to Grow
• (07:03) - The Journey
• (09:50) - Struggling
• (13:44) - Risk
• (16:41) - Targeting
• (18:20) - Framework
• (20:44) - Implementing Early
• (22:18) - Back End Risks
• (24:30) - Bridging the Gap
• (26:39) - When to Engage Astrix
• (30:21) - Wrap Up