41 lines
1.9 KiB
Markdown
41 lines
1.9 KiB
Markdown
# 2026-02-13 - Daily Memory Log
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## YouTube Summary: Zero Trust in the Age of Agentic AI
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**Video:** https://youtu.be/d8d9EZHU7fw
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**Topic:** Cybersecurity - Securing AI Agent Systems with Zero Trust Principles
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### Key Concepts
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**Agentic AI Risks**
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- AI agents that act (call APIs, buy things, move data, spawn sub-agents) introduce entirely new attack surfaces
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- Non-Human Identities (NHIs) - software actors using credentials - proliferate rapidly and need same/more control than human users
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**Core Zero Trust Principles**
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- "Never trust, always verify" - verification precedes trust
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- Just-in-time access vs. just-in-case (privilege only when needed)
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- Principle of least privilege
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- Move from perimeter-based security to pervasive controls throughout the system
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- Assumption of breach (design assuming attackers are already inside)
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**Attack Vectors on Agentic Systems**
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1. Direct prompt injection - breaking context to make agents do unauthorized things
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2. Policy/preference poisoning - manipulating training data or context
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3. Interface insertion - hijacking MCP calls or tool interfaces
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4. Credential attacks - stealing/copying NHI credentials to escalate privileges
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5. Attacks on APIs, data sources, tools, and spawned sub-agents
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**Zero Trust Solutions for AI**
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- Unique dynamic credentials for every agent/user stored in vaults (never embedded in code)
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- Tool registries with vetted/verified secure APIs only
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- AI firewalls/gateways for prompt injection detection and blocking
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- Continuous monitoring for data leaks and improper calls
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- Just-in-time privilege enforcement with strong authentication
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### Why It Matters
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As AI agents become more autonomous and integrated into systems, traditional perimeter security fails. Zero Trust principles adapted for software actors (NHIs) and agent-to-agent interactions will become critical for securing AI-native infrastructure.
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---
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*Stored during pre-compaction flush*
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