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AppSec → LLM security

Chevy Phillip

Application security engineer focused on securing AI and LLM systems.

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Research log

Blog

Page 2 of insights on application security, threat modeling, and building AI-powered applications.

Oct 19, 2026/Chevy Phillip

Securing AI Agents in Practice: Least Privilege, Prompt Injection, Isolation, and Approval Gates

The four controls I set up before my AI agents touch real work: least privilege connectors, tool output as data, network isolation with Tailnet Lock, and human approval gates.

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AIAgentsSecurityPrompt-InjectionThreat-Modeling

Oct 17, 2026/Chevy Phillip

I Shipped a Real Product Solo. Nobody's Bought It Yet. Here's the Whole Scoreboard.

The first build-in-public scoreboard for Agent Wins: what I shipped solo with Cursor and Grok, and the real numbers four days after launch, including 0 sales.

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AIAgentsBuildingBuild-in-Public

Oct 14, 2026/Chevy Phillip

What I'm Building: Agent Wins, AI Agent Use Cases With Receipts

Agent Wins collects AI agent use cases that actually worked, each with a verified public source and a copy-ready recipe for the agent you already use.

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AIAgentsAI-Agent-Use-CasesBuilding

Jan 6, 2026/Chevy Phillip

The State of LLM Security in 2026: Threats, Trends, and Predictions

From OWASP Top 10 updates to MCP vulnerabilities and agentic AI risks—what security teams need to know and do now.

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AISecurityThreat-Modeling
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