My AI spent $15 on a test order, so I built an open-source payment guardrail

felixpg13-glitch — Mon, 31 Aug 2026 15:56:17 +0000

My AI spent $15 on a test order, so I built an open-source payment guardrail

TL;DR: An open-source Python + MCP library that sits between AI agents and money. Spend-capped agent identity (KYA), four deterministic gates (dry-run, budget, amount limit, human approval), prompt-injection defense, encrypted secret vault. pip install spendshield — GitHub

The incident that started it

On Aug 9, 2026, my automation system ran a "test order." I sent dry: true in the body, expecting a price preview. The server only honored ?dry=1 in the URL.

4 orders of ¥99 ($15) went through. Charged. Real money, gone.

I didn't lose much — but I realized something uncomfortable: this exact bug is about to happen everywhere, at much larger scale.

AI agents are starting to order food, buy compute, call paid APIs. Every one of those is a new place where a test flag can silently fail, a budget can be exceeded, a prompt-injected agent can spend without permission.

When AI starts spending real money, who puts a gate in front of it?

I turned my scar into a library.

What it does

from spendshield import SpendShield

guard = SpendShield(budget=200, dry_run=True, whitelist=["McDonald's"])

@guard.protect("order")
def place_order(amount, to):
    return call_real_api(amount, to)   # real payment code

place_order(amount=99, to="McDonald's")
# => DryRunBlocked: nothing executed. dry_run is the default.

guard.dry_run = False
for i in range(4):
    place_order(amount=99, to="McDonald's")
    # 3rd order blocked by BudgetExceeded

Four deterministic gates — dry-run, budget, per-transaction limit, human approval — plus full audit. Rules are code, not AI opinion. An agent cannot argue, trick, or inject its way past.

The three pillars

1. Identity (KYA) — every agent registers with its own budget, blacklist, rate limits. Unregistered agents are denied by default.

guard.register_agent("mcd_bot", budget=50, max_amount=30,
                     blacklist=["unknown_vendor"], whitelist=["McDonald's"])

2. Intent alignment (anti prompt-injection) — new recipients and large amounts always require human sign-off. A prompt-injected agent trying to pay a stranger gets blocked at "human didn't approve."

3. Secret vault — keys encrypted at rest (AES-256), master key never on disk, access gated and audited. No more "private key in a config file."

x402-ready

x402 is the emerging open payment protocol for the internet (HTTP 402) — how agents will pay for APIs. SpendShield already has an adapter: gate the payment before it settles.

from spendshield.adapters.x402 import X402PaywallGuard

pw = X402PaywallGuard(guard)
pw.authorize_resource("weather-api", price="0.01", asset="USDC", pay_to="0x...")

x402 lets agents pay. SpendShield stops them paying recklessly.

State of the project

36 tests, identity/intent/vault/gates all covered
MCP server for Claude Code / OpenClaw / any MCP client
Dockerfile included
MIT licensed

This is a 0-star project today. It was built in one day, from a real scar, for a problem I'm confident is coming.

If you've ever been burned by a "test order" — or you're building agents that will touch money — I'd love your feedback.

⭐ GitHub: felixpg13-glitch/spendshield
📦 pip install spendshield

DEV Community: felixpg13-glitch

My AI spent $15 on a test order, so I built an open-source payment guardrail

My AI spent $15 on a test order, so I built an open-source payment guardrail

The incident that started it

What it does

The three pillars

x402-ready

State of the project