Architecting autonomous security operations (SecOps), managing non-deterministic workflows, verifiable AI guardrails, and the Hierarchy of Needs for AI agents.
Addressing attack velocity (every 39 seconds) and $4.35M breach costs with autonomous self-healing agentic defense, threat summarizers, and Rakshak-AI.
Rethinking security, trust boundaries, multi-agent orchestration, deterministic vs non-deterministic workflows, and enterprise governance in autonomous ecosystems.
Exploring the cybersecurity battlefield, the new agentic attack surface, prompt injection defenses, multi-agent risk multiplication, and runtime intent enforcement.
In-house distributed load testing framework to simulate real-world messaging user journeys, vertically & horizontally stressing backend DBs, caches, queues, and CI/CD pipelines.
The Clean Attack Problem: When nothing looks wrong but everything is compromised. Shifting from anomaly detection to intent reasoning, behavioral sequencing, and runtime decision analysis.
Addressing post-authentication risk and trusted-agent misuse. Why Zero Trust must evolve beyond static identity verification toward continuous behavioral monitoring and runtime intent analysis.
Cybersecurity in the age of autonomous AI. Why autonomous agents don't fail by violating rules—they follow instructions literally while circumventing intent through policy drift and specification gaming.
Deep-dive into inter-agent trust chains, cascade prompt injections, memory and vector store poisoning, and machine-to-machine agentic IAM architecture.
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