acuris-agent-guard 0.1.0

Verify the merchant before your AI agent pays. A pre-pay storefront-legitimacy check (address + company-register + domain-binding + sanctions) for LangChain, CrewAI, Anthropic computer-use, or any MCP agent.

Acuris Agent Guard

Verify the merchant before your AI agent pays.

When an AI agent shops on someone's behalf, the entire trust stack verifies the buyer's agent (Visa Trusted Agent Protocol, Mastercard Agent Pay) — and nobody verifies the merchant. Agents don't read the URL bar or sniff a "too good to be true" deal; they autofill the saved card and pay. Security researchers have already shown agentic browsers checking out on fake stores (Guardio "Scamlexity", 2025), and AI assistants surface clone storefronts on look-alike domains (Netcraft: 34% of brand URLs returned by an LLM weren't brand-owned).

acuris-agent-guard is the one pre-pay check that answers:

Is this storefront a real, operating, sanctions-clean legal entity that actually controls the domain it claims?

{ address_valid, company_exists, website_bound, sanctions } → one decision: PROCEED / ABORT / REVIEW. The differentiator is website_bound — catching a clone that shows a real company's name/VAT on a fresh look-alike domain, which a plain "does this company exist?" check waves through.

See it in 10 seconds (zero setup, runs offline)

Install into a virtualenv (recommended — modern Debian/Ubuntu block pip into the system Python with an externally-managed-environment error; that's an OS guard, not this package):

python3 -m venv .venv && . .venv/bin/activate
pip install git+https://github.com/Acuris-GmbH/acuris-agent-guard   # PyPI: pip install acuris-agent-guard (coming soon)
python -m acuris_agent_guard.demo

Prefer an isolated CLI? pipx install git+https://github.com/Acuris-GmbH/acuris-agent-guard works too.

The same autonomous agent, same task, same clone — one checks the merchant first:

task: Buy the Aurora Linen Dress for me.

AGENT A — WITHOUT Acuris
  • top result = aurora-boutique-official.shop → choosing it
  • autofill saved card + shipping address → submit payment … €149
  ✗ Payment sent. €149 gone. Goods never arrive.   (clone, 6-day-old domain)

AGENT B — WITH Acuris guard
  • pre-pay check → acuris.verify_storefront("aurora-boutique-official.shop")
    ↩ ABORT  domain_bound=False  entity_resolves=True
    reason: This domain is NOT bound to the registered company it claims — likely a clone.
  ✓ Purchase ABORTED. €149 protected.
  • fall back to aurora-linen.example → PROCEED (bound to AURORA LINEN GMBH)
  ✓ Paid the real Aurora Linen GmbH.

Demo mode ships faithful, illustrative responses so it runs with no key. Set ACURIS_API_KEY (and pass --live) to hit the real API.

Where it plugs into your loop

Any MCP agent (Claude Desktop / Claude Code / others) — one config line

First install the MCP extra into a venv (pip install "acuris-agent-guard[mcp] @ git+https://github.com/Acuris-GmbH/acuris-agent-guard"), then point the config at that venv's Python (use the absolute path, or pipx, so it resolves regardless of the system Python):

"mcpServers": {
  "acuris": {
    "command": "/path/to/.venv/bin/python",
    "args": ["-m", "acuris_agent_guard.mcp_server"],
    "env": { "ACURIS_API_KEY": "your-key" }   // omit for offline demo mode
  }
}

Then: "Before paying any merchant, call verify_storefront and abort if it is not safe_to_pay."

Plain Python (framework-agnostic guardrail)

from acuris_agent_guard import pre_pay_guard, PaymentBlocked

try:
    pre_pay_guard("aurora-boutique-official.shop", name="Aurora Linen")  # raises if unsafe
    charge_card(...)                                                      # only runs if verified
except PaymentBlocked as e:
    agent.note(str(e))   # do not pay; route to a verified seller

LangChain — integrations/langchain_guard.py

Adds verify_storefront as a tool and wraps your real pay tool so payment is structurally impossible unless the storefront verifies (don't rely on the model remembering to check).

Anthropic computer-use — integrations/computer_use_guard.py

Intercepts the action loop right before a "place order / pay" click; if the storefront fails, the click never executes and the block is fed back to the model as the tool result so it re-plans.

The verdict

from acuris_agent_guard import StorefrontVerifier
v = StorefrontVerifier().verify("aurora-boutique-official.shop", name="Aurora Linen")
v.decision        # "ABORT"
v.safe_to_pay     # False
v.reason          # "This domain is NOT bound to the registered company ..."
v.to_dict()       # full structured signals + score + evidence

The decision is derived from structured signals (domain_bound, entity_resolves, sanctions_hit, reachability), and fails closed — an unreachable/unverifiable storefront returns REVIEW, never a silent PROCEED.

Honest scope

• A pre-pay risk signal, not fraud insurance, not a delivery guarantee, and not a certification. It catches impersonation / fabrication / sanctions — it cannot predict whether a genuine registered merchant will fail to ship.
• Domain↔entity binding is inferred from official registers + corroborating signals (TLS org, domain age, VAT), since WHOIS/RDAP is largely GDPR-redacted.
• It is not an anti-prompt-injection control; it scores the merchant, so wire it as a hard guardrail on the payment step, not an optional tool.

MIT © Acuris GmbH · built on the Acuris trust-data API.