Show HN: Doberman: The AI watchdog that stops Claude from deleting your database (github.com)
Landing Page: https://www.trydoberman.dev/
The Problem: AI guardrails only protect against 89% of dangerous commands. This may seem pretty good until you think of it as a lock that lets 1 in 9 intruders in.
What is Doberman: Doberman is a two layer security system wrapped around your LLM monitoring every input, output and tool call. The first layer is deterministic based on state of the art security guidelines, the second layer is dynamic, learning from your use and personal preferences.
How is Doberman different: It is a dynamic two-layer security system that sits at runtime and monitors every input, output, and tool execution, adapting with you as you work.
7 comments
[ 4.2 ms ] story [ 16.9 ms ] threadWhoops, I’ve read too far into the readme. Scratch that first one :)
Anyway, given OP appears to be the author: how are you differentiating from the rest of the (some well funded) guard dogs? The adaptive learning; totp integration; simple tool proxy model; your turn gate state machine’s novelty?
Each piece of tech of the framework is not novel, since I'm not trying to reinvent the wheel here. My focus is on the depth of security and a set of invariants that the system is built around. It's designed to be overprotective sitting on the execution path fail closed and raise only. The adaptive learning lowers that security based on your needs so eventually it can become a silent protector that doesn't constantly bother you like CC asking you for permission to do a git push.
I'm not saying we shouldn't have built in precautions and permissions, this should be standard practices, but Doberman is a system built to handle the inevitable case when these precautions fail.