Topics on Pawan Khandavillihttps://pawankhandavilli.com/topics/Recent content in Topics on Pawan KhandavilliHugo -- 0.165.0en-USAgent and MCP Securityhttps://pawankhandavilli.com/topics/agent-security/Mon, 01 Jan 0001 00:00:00 +0000https://pawankhandavilli.com/topics/agent-security/Identity, delegation, tool permissions, and the trust boundaries behind autonomous AI systems.AI agents turn language into actions. That makes identity, delegated authority, tool permissions, and execution integrity part of the security boundary—not implementation details.

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  1. Trust Is the Next Bottleneck explains why authorization alone cannot establish that an agent is running the expected code.
  2. AI Agents Have an Identity Crisis examines verifiable delegation across multi-agent workflows.
  3. MCP Is a Capability System provides the practical permission model.
  4. Hardening MCP Servers with Confidential Computing addresses the infrastructure trust boundary around tool credentials.
  5. Google’s AP2 Protocol applies these ideas to agent-initiated commerce.

Together, these essays describe a security model built from bounded authority, measured execution, and evidence that survives every hop.

]]>Confidential Computinghttps://pawankhandavilli.com/topics/confidential-computing/Mon, 01 Jan 0001 00:00:00 +0000https://pawankhandavilli.com/topics/confidential-computing/How trusted execution environments protect data in use—and what it takes to make their assurances verifiable.Confidential computing protects data while it is being processed. The interesting question is not whether a workload runs inside a trusted execution environment, but whether the complete path from measurement to attestation to secret release deserves trust.

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  1. WhatsApp’s Private Processing introduces confidential computing through a system operating at internet scale.
  2. What WhatsApp’s Trail of Bits Audit Teaches Us shows how real implementations can break the intended trust model.
  3. From “Trust Us” to “Verify Us” explores confidential AI inference and the next identity problem.
  4. TEEs in Crypto looks at hardware isolation as a pragmatic coordination layer.
  5. Follow the Data offers the broader architecture method behind the technology.

These pieces move from the basic promise—protecting data in use—to the harder work of proving what is actually inside the trusted boundary.

]]>Security Product Leadershiphttps://pawankhandavilli.com/topics/security-product-leadership/Mon, 01 Jan 0001 00:00:00 +0000https://pawankhandavilli.com/topics/security-product-leadership/Practical lessons about security architecture, product judgment, and making trust an enabler rather than a gate.Security becomes more useful when it shapes product decisions early. These essays connect architecture, customer value, and the judgment required to ship systems people can trust.

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  1. Follow the Data presents the five questions I use to make unfamiliar security architecture problems clearer.
  2. Making Security an Enabler explains how security teams can replace late-stage vetoes with early design partnership.
  3. From NFC Startups to Confidential Computing traces the career experiences behind that perspective.
  4. The AI Security Stack turns the ideas into an executive operating model.

The common theme is simple: start with the asset and the user outcome, make the trust boundary explicit, and design controls that help the product move.

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