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lordkruk
lordkruk

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Why Regex isn't enough: Auditing Discord Bots with AI Reasoning Models

The Discord ecosystem has a malware problem.
Traditional bot lists rely on automated scripts that check two things:

  1. Is the bot online?
  2. Does the token work?

If yes -> Approved. 🚨
This lazy approach is why so many malicious bots infiltrate servers.

At DiscordForge, we decided to take a harder path. We combined manual verification with AI Reasoning Models (Gemini 3). Here is why purely algorithmic checks fail and how "Deep Thinking" models fix it.

The "Context" Problem

Imagine a bot with this description:

"A simple tool to help you backup your server channels."

A standard regex check sees keywords like "backup" and "channels" and tags it as a Utility Bot. ✅

However, a Reasoning Model looks at the Permissions Intent:

  • Permissions Requested: Manage Webhooks, Mention Everyone.
  • Logic Analysis: Why does a backup bot need to mention everyone?

Gemini 3 Deep Think flags this mismatch immediately. It understands that while "backups" are a valid feature, the combination of mass-ping permissions with a backup tool is a high-probability heuristic for a Raid Bot.

Our Hybrid Pipeline

We built a pipeline that scores every submission:

  1. Static Analysis: Checks uptime and API response time.
  2. AI Audit: Scans the description, commands, and requested permissions for logical fallacies and social engineering vectors.
  3. Human Review: A real human (me or a trusted verifier) makes the final call based on the AI's report.

It’s slower than auto-approval, but the result is a directory where server owners can actually trust the "Add Bot" button.

Try to trick it?

We are currently beta-testing this verification flow. If you are a bot developer who cares about security, I invite you to list your bot on the Forge.

Submit your bot to DiscordForge

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