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Keedz1Off/README.md

Keedz1 | AI Agent & Application Security

I review security boundaries in AI agents, MCP integrations and tool-enabled applications. My background is in Web3 security: smart contracts, bridge flows and accounting invariants.

Method: map the flow → define invariants → build test scenarios → inspect results → verify fixes.

I use AI for code analysis, test development and automation. Reports distinguish confirmed behavior, security impact and remaining gaps.

Web3

AppSec

  • FastAPI mutation benchmark: an independent static auditor identified all five deliberately introduced defects. Attack scenarios were not validated over HTTP.

AI Agent Security

  • Browser Use: navigation-policy behavior; security impact remains unconfirmed.
  • FastMCP / MCP SDK: SSE error propagation and local verification of a proposed upstream fix.
  • Learn with GenAI: application resource-cleanup bug, local patch and regression tests.

Open to remote AI security / AppSec roles and contract research.

Telegram · Email

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  1. fastmcp-auth-state-sse-case-study fastmcp-auth-state-sse-case-study Public

    Independent AI-assisted PrefectHQ FastMCP case study: auth, shared OAuth state, SSE error propagation, evidence and limitations.

  2. learn-with-genai-resource-lifecycle-case-study learn-with-genai-resource-lifecycle-case-study Public

    AI-assisted case study: confirmed SQLite resource-lifecycle bug, local fix, and regression tests. No confirmed DoS claim.

  3. browser-use-agent-security-case-study browser-use-agent-security-case-study Public

    Independent AI-assisted Browser Use trust-boundary case study: scoped local evidence, architecture, and calibrated conclusions.

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  4. web3-security-portfolio web3-security-portfolio Public

    Web3 security portfolio: bridge architecture, authorization boundaries, accounting invariants, Foundry testing, and evidence-qualified case studies.