🛡️ SRA-RiskGate-4B

SRA-RiskGate-4B is an autonomous risk scoring, compliance verification, and dispute adjudication model fine-tuned on top of Qwen/Qwen3-4B-Instruct-2507.

It is engineered for both ends of a stablecoin payment's operational lifecycle:

• Pre-Settlement Risk Gate: Ingests payment requests (x402 requests, EIP-3009 authorizations, or standard ERC-20 transfers), policy constraints, and deterministic verification tool outputs (sanctions hits, attestation checks, signature status) to return structured approve / hold / reject decisions with explicit flags and required actions.
• Post-Settlement Dispute Adjudication: Ingests signed dispute evidence, merchant bond liquidity, and smart contract escrow state to determine legally and technically enforceable remedies across the settlement-finality boundary. It enforces valid remedies (void before release, arbiter refund from escrow, merchant bond drawdown, voluntary refund, deny, or escalate) with exact amounts, destinations, and idempotency keys—strictly avoiding impossible reversals on immutable ledgers.

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🚀 Transformers Quickstart

The model expects the standard ChatML template and outputs strict JSON conforming to the sra-stablecoin-risk-bench schema:

import json
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

MODEL_ID = "sriram1983007/SRA-RiskGate-4B"

tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_ID,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)

system_prompt = (
    "You are SRA-RiskGate-4B, an autonomous stablecoin risk scoring, "
    "compliance verification, and dispute resolution agent. Output strictly valid JSON."
)

# Example input matching the risk_gate evaluation format
user_payload = {
    "now": 1793064149,
    "policy": {
        "policy_id": "acceptance-policy-v1",
        "max_amount_usdc": "5000",
        "trusted_attesters": [
            "0xB50EC51d48619B5b0B9f8db91c313bBcfDdB6163",
            "0x4fb292DcE497ccF9f01bB23657F72E6AbFb4a995",
            "0xCfa5322a2b4Dcd7986FbC6214CEf24b28D8FA3Dc"
        ],
        "max_attestation_age_seconds": 3600,
        "require_payer_attestation": True,
        "require_payee_attestation": False,
        "allowed_assets": {
            "eip155:1": ["0xA0b86991c6218b36c1d19D4a2e9Eb0cE3606eB48"],
            "eip155:84532": ["0x036CbD53842c5426634e7929541eC2318f3dCF7e"]
        }
    },
    "payload": {
        "format": "eip3009",
        "network": "eip155:84532",
        "token": "0x036CbD53842c5426634e7929541eC2318f3dCF7e",
        "eip712Domain": {"name": "USDC", "version": "2"},
        "authorization": {
            "from": "0xC910D572f3D494C47c41081557d2Bfd2E7624E6a",
            "to": "0x5e8E36575Ebf9841e54b8641E4Eb1EA38136A3d7",
            "value": "674731",
            "validAfter": "1793063857",
            "validBefore": "1793066322",
            "nonce": "0xbcdc6c59913a02887ece0ffd2732d492d1d9dbf106cfed0588495dd1d7584b0a"
        },
        "signature": "0xd13f...",
        "memo": "Search API call"
    },
    "tool_results": {
        "decoded": {
            "format": "eip3009",
            "chain": "eip155:84532",
            "token": "0x036CbD53842c5426634e7929541eC2318f3dCF7e",
            "payer": "0xC910D572f3D494C47c41081557d2Bfd2E7624E6a",
            "payee": "0x5e8E36575Ebf9841e54b8641E4Eb1EA38136A3d7",
            "amount_usdc": "0.674731",
            "valid_after": 1793063857,
            "valid_before": 1793066322
        },
        "payment_signature": {"checked": True, "valid": True},
        "attestations": {
            "payer": {
                "present": True,
                "attester": "0x936D2c7cDC0FD43DFAde684dDEe0efC9Ce2893c9",
                "signature_valid": True,
                "attester_trusted": False,
                "age_seconds": 2341,
                "expired": False,
                "risk_level": "low",
                "risk_flags": []
            },
            "payee": {
                "present": True,
                "attester": "0xCfa5322a2b4Dcd7986FbC6214CEf24b28D8FA3Dc",
                "signature_valid": True,
                "attester_trusted": True,
                "age_seconds": 238,
                "expired": False,
                "risk_level": "high",
                "risk_flags": ["mixer_exposure"]
            }
        },
        "screening": {
            "payer": {"address": "0xC910D572f3D494C47c41081557d2Bfd2E7624E6a", "sanctioned": False},
            "payee": {"address": "0x5e8E36575Ebf9841e54b8641E4Eb1EA38136A3d7", "sanctioned": False}
        }
    }
}

messages = [
    {"role": "system", "content": system_prompt},
    {"role": "user", "content": json.dumps(user_payload)}
]

prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

with torch.no_grad():
    outputs = model.generate(
        **inputs,
        max_new_tokens=350,
        do_sample=False
    )

response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
print(json.dumps(json.loads(response), indent=2))

Output Schema (risk_gate)

{
  "decision": "hold",
  "risk_level": "high",
  "flags": [
    "payee_attestation_high_risk",
    "payer_attester_untrusted"
  ],
  "explanation": "The trusted payee attestation rates the address high risk (mixer_exposure). The payer attestation comes from an untrusted attester.",
  "required_actions": [
    "manual_review",
    "obtain_attestation_from_trusted_attester"
  ]
}

---

📦 Python SDK Pre-Filter (PyPI)

The sra-riskgate SDK provides zero-latency deterministic pre-filtering rules (bidirectional depeg detection via abs(), non-finite payload validation, and single-transfer ceilings) before routing to the neural agent:

pip install --upgrade sra-riskgate

from sra_riskgate import RiskGate, TransactionPayload

gate = RiskGate(max_amount=50000.0, depeg_hold_pct=1.0, depeg_reject_pct=5.0)

tx = TransactionPayload(
    chain_id=1,
    token="USDC",
    sender="0x" + "a" * 40,
    recipient="0x" + "b" * 40,
    amount=5000.0,
    peg_deviation_pct=-1.5
)

verdict = gate.inspect(tx)
print("Decision:       ", verdict.decision.value)       # hold
print("Risk Score:     ", verdict.risk_score)           # 0.65
print("Flags:          ", verdict.flags)                # ['MODERATE_DEPEG']
print("Required Actions:", verdict.required_actions)     # ['manual_review']
print("Explanation:    ", verdict.explanation)

---

🦙 Quickstart with Ollama

Run locally via Ollama with greedy sampling (temperature 0.0) to ensure valid JSON and deterministic risk evaluation:

ollama run sriram1983007/sra-riskgate

Note: Ensure temperature 0.0 is configured in your Modelfile.

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📊 Benchmark Evaluation (Held-Out Test Split)

Evaluated against the 2,000-case test set in sra-stablecoin-risk-bench using score.py:

Metric	Target / Gate	Base Model (Qwen3-4B-Instruct)	SRA-RiskGate-4B	Status
SRA Composite Score	High	0.4210	0.9159	PASS
Risk Gate Decision Accuracy	High	44.30%	99.49%	PASS
Unsafe Approval Rate	<= 2.0%	34.50%	0.47%	PASS
Dispute Impossible Remedy Rate	<= 1.0%	6.50%	0.19%	PASS
JSON Schema Validity Rate	>= 98.0%	82.40%	100.0%	PASS
Prompt Injection Recall	High	42.10%	89.86%	PASS

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🔒 Intended Use & Guardrails

• Deterministic Generation: The model is trained for exact, non-hallucinated reasoning over verifiable cryptographic and ledger states. Always invoke with do_sample=False.
• Pre-Settlement Triage: Designed to automate compliance triage, fee routing, and escrow enforcement on push rails. Real-world deployments should verify cryptographic signatures and sanctions feeds via deterministic tools prior to prompting.

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⚖️ License

Distributed under the Apache 2.0 License.