llm-trading-agent-security
审计 AI 交易代理的安全威胁模型,防止注入攻击和权限滥用导致资产损失
npx skills add https://github.com/affaan-m/everything-claude-code --skill llm-trading-agent-securityBefore / After 效果对比
1 组手动审查交易代理代码,依赖个人经验识别安全漏洞,容易遗漏注入点和权限绕过问题,一个代理系统需要 2-3 天审计,仍存在高风险漏洞
系统化评估交易代理的威胁模型,自动检测注入攻击面、权限边界和交易签名逻辑,1 小时生成详细的安全报告和修复清单
llm-trading-agent-security
LLM Trading Agent Security
Autonomous trading agents have a harsher threat model than normal LLM apps: an injection or bad tool path can turn directly into asset loss.
When to Use
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Building an AI agent that signs and sends transactions
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Auditing a trading bot or on-chain execution assistant
-
Designing wallet key management for an agent
-
Giving an LLM access to order placement, swaps, or treasury operations
How It Works
Layer the defenses. No single check is enough. Treat prompt hygiene, spend policy, simulation, execution limits, and wallet isolation as independent controls.
Examples
Treat prompt injection as a financial attack
import re
INJECTION_PATTERNS = [
r'ignore (previous|all) instructions',
r'new (task|directive|instruction)',
r'system prompt',
r'send .{0,50} to 0x[0-9a-fA-F]{40}',
r'transfer .{0,50} to',
r'approve .{0,50} for',
]
def sanitize_onchain_data(text: str) -> str:
for pattern in INJECTION_PATTERNS:
if re.search(pattern, text, re.IGNORECASE):
raise ValueError(f"Potential prompt injection: {text[:100]}")
return text
Do not blindly inject token names, pair labels, webhooks, or social feeds into an execution-capable prompt.
Hard spend limits
from decimal import Decimal
MAX_SINGLE_TX_USD = Decimal("500")
MAX_DAILY_SPEND_USD = Decimal("2000")
class SpendLimitError(Exception):
pass
class SpendLimitGuard:
def check_and_record(self, usd_amount: Decimal) -> None:
if usd_amount > MAX_SINGLE_TX_USD:
raise SpendLimitError(f"Single tx ${usd_amount} exceeds max ${MAX_SINGLE_TX_USD}")
daily = self._get_24h_spend()
if daily + usd_amount > MAX_DAILY_SPEND_USD:
raise SpendLimitError(f"Daily limit: ${daily} + ${usd_amount} > ${MAX_DAILY_SPEND_USD}")
self._record_spend(usd_amount)
Simulate before sending
class SlippageError(Exception):
pass
async def safe_execute(self, tx: dict, expected_min_out: int | None = None) -> str:
sim_result = await self.w3.eth.call(tx)
if expected_min_out is None:
raise ValueError("min_amount_out is required before send")
actual_out = decode_uint256(sim_result)
if actual_out < expected_min_out:
raise SlippageError(f"Simulation: {actual_out} < {expected_min_out}")
signed = self.account.sign_transaction(tx)
return await self.w3.eth.send_raw_transaction(signed.raw_transaction)
Circuit breaker
class TradingCircuitBreaker:
MAX_CONSECUTIVE_LOSSES = 3
MAX_HOURLY_LOSS_PCT = 0.05
def check(self, portfolio_value: float) -> None:
if self.consecutive_losses >= self.MAX_CONSECUTIVE_LOSSES:
self.halt("Too many consecutive losses")
if self.hour_start_value <= 0:
self.halt("Invalid hour_start_value")
return
hourly_pnl = (portfolio_value - self.hour_start_value) / self.hour_start_value
if hourly_pnl < -self.MAX_HOURLY_LOSS_PCT:
self.halt(f"Hourly PnL {hourly_pnl:.1%} below threshold")
Wallet isolation
import os
from eth_account import Account
private_key = os.environ.get("TRADING_WALLET_PRIVATE_KEY")
if not private_key:
raise EnvironmentError("TRADING_WALLET_PRIVATE_KEY not set")
account = Account.from_key(private_key)
Use a dedicated hot wallet with only the required session funds. Never point the agent at a primary treasury wallet.
MEV and deadline protection
import time
PRIVATE_RPC = "https://rpc.flashbots.net"
MAX_SLIPPAGE_BPS = {"stable": 10, "volatile": 50}
deadline = int(time.time()) + 60
Pre-Deploy Checklist
-
External data is sanitized before entering the LLM context
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Spend limits are enforced independently from model output
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Transactions are simulated before send
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min_amount_outis mandatory -
Circuit breakers halt on drawdown or invalid state
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Keys come from env or a secret manager, never code or logs
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Private mempool or protected routing is used when appropriate
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Slippage and deadlines are set per strategy
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All agent decisions are audit-logged, not just successful sends
Weekly Installs522Repositoryaffaan-m/everyt…ude-codeGitHub Stars157.6KFirst Seen11 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykWarnInstalled oncodex492opencode476gemini-cli473kimi-cli472antigravity472amp472
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