Zero Trust for AI & LLM Systems
Microsegmentation for machine identities, continuous verification for agentic pipelines, and NIST SP 800-207 applied to AI infrastructure.
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Securing Enterprise AI & Agentic Workflows
Shadow AI governance, trust boundaries for agents, NHI sprawl defense, and a 30/90/180-day roadmap for CISOs and AppSec directors.
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AI Red Teaming: The Enterprise LLM Security Testing Playbook
Jailbreaks, prompt injection, data extraction, and DoS β the structured adversarial testing methodology that finds vulnerabilities before attackers do.
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Securing Autonomous AI Agents
Tool poisoning, memory hijacking, privilege escalation β the complete enterprise defense architecture for agentic AI systems.
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Prompt Injection Attacks
How attackers trick LLMs and the 5-layer defense that stops 95% of attacks.
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Securing LLM APIs
The exact checklist used by top AI companies for authentication, rate limiting, and monitoring.
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Data Poisoning Defense
How malicious training data breaks models and the robust protection strategy that works today.
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Model Inversion Attacks
How attackers extract training data from AI models and the hardening techniques that stop them.
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AI Supply Chain Security
Compromised model weights, poisoned pip packages, and how to verify integrity end-to-end.
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Securing RAG Pipelines
Retrieval-Augmented Generation opens new attack surfaces β here's how to lock them down.
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