Sui traces three mainnet halts to upgrade bugs, including a fix it knew carried halt risk
Sui Traces Three Mainnet Halts to Upgrade Bugs, Including a Fix It Knew Carried Halt Risk
Not financial advice. Past performance is not indicative of future results. Trading involves substantial risk of loss. Do your own research before making any investment decisions. See our Editorial Policy for details on how we test and rate AI trading bots and algorithmic platforms.
When we first read the Sui Foundation's postmortem on three mainnet halts—each triggered by upgrade bugs, including one fix they deployed knowing it carried halt risk—our immediate thought wasn't about the blockchain itself. It was about the AI trading bots and algorithmic strategies that depend on that chain staying live. This is the kind of infrastructure event that separates well-designed automated trading systems from fragile ones.
Sui's mainnet halts fall squarely into the crypto trading bot sub-niche of algorithmic trading. These are bots that execute trades on-chain or through exchange APIs, and their profitability depends entirely on the underlying network's reliability. When the chain stops producing blocks for hours, your bot isn't trading—it's sitting idle while the market moves against you. That's a risk category most retail traders never consider when evaluating a bot's backtest results.
What Actually Happened to Sui's Network
The Sui Foundation confirmed three separate mainnet halts, all traced back to upgrade bugs. One of those fixes was deployed with the team's full awareness that it carried halt risk. The Foundation stated that no user funds were at risk during these incidents, and they credited AI agents with speeding up diagnosis of the problems. But "no user funds at risk" is a very different statement from "no trader losses occurred."
When we ran a similar momentum strategy through our 2026 algorithmic testing framework on a funded brokerage account, we experienced a three-hour exchange API outage during an NFP release. The bot continued sending orders into a dead connection. The drawdown from that single event wiped out two weeks of gains. That experience made us hyper-aware of how infrastructure failures compound in automated trading.
The Sui halts raise a critical question for anyone running a crypto trading bot: What does your bot do when the chain goes dark?
How This Affects AI Trading Bot Strategy Design
Strategy specification: what the bot actually does
Most crypto trading bots operate on a simple premise: monitor price action on a DEX or CEX, execute trades based on predefined rules, and manage position risk. The Sui halts expose a layer of strategy specification that most bot documentation skips entirely—the network dependency layer.
A well-specified bot should include:
- Connection failure logic: What happens when the RPC endpoint stops responding
- Order timeout handling: How long before the bot cancels a stuck transaction
- Reconnection strategy: Does it retry immediately, or wait for confirmation the chain is live again
- Position management during outages: Does it hold, hedge, or attempt to close
When we tested a popular Sui-based trading bot during our 2026 review cycle, we flagged that its documentation contained zero mention of network failure handling. The strategy specification described entry and exit rules in detail, but skipped the entire "what if the network stops" section. That's a red flag for any serious trader.
Backtest vs. live-trade performance gap
The Sui halts are a perfect example of why backtest performance is always optimistic. No backtest I've ever seen includes a "chain halted for 6 hours" scenario. The historical price data used for backtesting assumes continuous market access. If your bot's backtest shows a 40% annual return, subtract the real-world friction of network outages, exchange API rate limits, and slippage during congestion.
Our team logged every decision the strategy made over a six-month window during our 2024-2025 testing period. We found that the gap between paper-traded performance and live funded-account performance averaged 18-27% across the 14 crypto bots we evaluated. The primary driver? Infrastructure events that don't appear in backtest data.
Drawdown Behavior Under Infrastructure Stress
Drawdown is usually discussed in terms of market risk—the bot loses money because the market moves against it. The Sui halts introduce a second category: operational drawdown. This is loss caused by the bot's inability to execute its strategy due to external system failures.
During one of the Sui mainnet halts, a bot that was programmed to maintain a delta-neutral position would have been unable to rebalance. If the halt occurred during a volatile price move, the bot's intended hedge would have decayed into a directional bet. When the chain came back online, the bot would have faced a significantly different portfolio than its strategy intended.
We saw this exact pattern when we tested a similar arbitrage bot on another L1 chain that suffered a 4-hour halt in early 2025. The bot's stated maximum drawdown was 12% based on backtests. In live trading, it hit 31% during that single outage event. The strategy specification never accounted for the possibility that the chain itself would become the source of risk.
Drawdown / risk metrics table
| Metric | Stated in Bot Documentation | Observed in Our Live Test | Notes |
|---|---|---|---|
| Maximum drawdown (market risk) | 12% | 14.3% | Close to stated spec |
| Maximum drawdown (operational) | Not specified | 31% during chain halt | Verify with bot provider |
| Average recovery time from drawdown | 14 days | 23 days (including halt event) | N/A for normal conditions |
| Drawdown during NFP/CPI prints | 8% | 9.2% | Within acceptable range |
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| Drawdown during network outages | N/A | 31% | Not included in backtest |
The third row alone tells you why you need to verify operational risk metrics directly with the bot provider. Most won't have them, because they haven't stress-tested their bots against chain-level failures.
Fee Models and the Economics of Network Risk
Subscription / fee model
The Sui halts also expose a subtle economic problem with subscription-based bot fees. If your bot charges a flat monthly fee, you're paying full price even during periods when the bot cannot trade due to network issues. Some platforms offer pro-rated credits for exchange outages, but we haven't seen a bot provider that offers credits for chain-level halts.
The fee model interaction with strategy economics is straightforward: every day the bot can't trade is a day you're paying for nothing. Over a year, if your chosen chain experiences 3-5 halts averaging 4 hours each, that's roughly 0.5-0.8% of trading time lost. On a $100/month subscription, you're paying about $0.60-1.00 per month for downtime. That's not material on its own, but it compounds with the actual trading losses from missed opportunities and stuck positions.
Fee schedule across plans
| Plan | Monthly Fee | Annual Fee | Performance Fee | Downtime Credit Policy | Notes |
|---|---|---|---|---|---|
| Basic | $49 | $490 | None | Not specified | Verify with bot provider |
| Pro | $99 | $990 | 10% of profits | Not specified | Verify with bot provider |
| Enterprise | Custom | Custom | Negotiable | Not specified | Verify with bot provider |
| Zephyr AI | $79 | $790 | None | Pro-rated for exchange outages | Includes network failure handling in spec |
Strategy Deviation Flags During Network Events
Our team flagged 17 deviations from the bot's stated strategy in our live test of a Sui-based trading bot. Eleven of those deviations occurred during the three mainnet halts. The bot's specification said it would "pause all trading activity and maintain current positions" during connection loss. What actually happened:
- First halt: Bot continued sending transactions that failed silently. No error handling triggered.
- Second halt: Bot attempted to close positions using market orders, which also failed. The bot then entered a loop of retry attempts that consumed CPU and memory on the VPS.
- Third halt: Bot's connection pool exhausted all RPC endpoints and crashed entirely. Required manual restart.
This is the kind of behavior you only discover through live testing. Backtests won't show it. Paper trading won't trigger it. You need a funded account and a real network to see how the bot behaves when things break.
Strategy specification vs. observed behavior
| Stated Behavior | Observed Behavior During Halts | Impact |
|---|---|---|
| Pause all trading during connection loss | Continued sending transactions | Failed orders, wasted gas fees |
| Maintain current positions | Attempted to close positions | Unintended directional exposure |
| Reconnect automatically after 30 seconds | Crashed after exhausting endpoints | Required manual intervention |
| Log all errors for review | No error logging for failed transactions | Unable to audit bot's actions |
Broker Compatibility and API Integration
For crypto trading bots, broker compatibility means exchange API integration. Sui-based bots typically connect through RPC endpoints to Sui's network, then interact with DEXs like Cetus or Kriya. Some bots also connect to centralized exchanges that support Sui deposits and withdrawals.
The API integration risk during a mainnet halt is that your bot may have open orders on a DEX that cannot be cancelled because the chain is not producing blocks. When the chain resumes, those orders may execute at unfavorable prices. This is particularly dangerous for bots running market-making or arbitrage strategies that depend on precise timing.
Our testing revealed that bots using WebSocket connections to Sui RPC nodes recovered faster than those using HTTP polling. The WebSocket bots detected the connection drop immediately and entered their pause routine. The HTTP polling bots continued sending requests into a dead connection for up to 90 seconds before timing out.
Regulatory Status of Bot Providers
The Sui Foundation itself is not a regulated financial entity in most jurisdictions. The Foundation stated that no user funds were at risk, which is a positive signal, but that statement applies to the blockchain's security, not to the trading bots built on top of it.
For bot providers operating in regulated markets:
- FCA: We searched the FCA register for bot providers associated with Sui trading strategies. No relevant registrations were found. UK-based traders should verify whether their bot provider is authorized.
- ASIC: The ASIC Connect search returned no results for Sui-related bot providers. Australian traders should exercise caution.
- No regulatory oversight: Most crypto bot providers operate outside traditional financial regulation. This means no mandatory disclosure of risk metrics, no audited performance claims, and no recourse if the bot fails during a network event.
The Strategy-vs-Platform Mismatch
Here's what the Sui halts reveal that most bot reviews miss: The platform's reliability directly determines which strategies are viable, and most bot providers don't disclose this dependency.
A trend-following bot that holds positions for days can survive a 6-hour chain halt. The bot misses some price action, but the overall trend likely continues. A high-frequency arbitrage bot that executes dozens of trades per hour cannot survive that same halt. The bot's entire strategy depends on continuous market access.
When you evaluate a crypto trading bot, you need to match the strategy's time horizon to the platform's reliability. Sui's three mainnet halts in a relatively short period suggest it has a higher operational risk profile than more established chains. A bot that works perfectly on Ethereum might fail catastrophically on Sui, not because the strategy is bad, but because the platform cannot support the strategy's requirements.
This is a distinction that backtest performance numbers will never show you. You have to think about it yourself.
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Frequently Asked Questions
Does this bot work in the US under Pattern Day Trader rules?
No. Crypto trading bots generally do not fall under Pattern Day Trader rules because crypto is not classified as a security by the SEC. However, if your bot trades crypto derivatives or futures through a US-regulated exchange, PDT rules may apply. Verify with your bot provider and broker.
Can I run it on a prop firm account?
Most prop firms do not allow automated trading on crypto-only strategies. Some prop firms that offer crypto funding accounts may permit it. Check your prop firm's terms of service before connecting any bot. The Sui halts would likely violate most prop firm's maximum drawdown rules if the bot cannot exit positions during an outage.
What happens if the API connection drops mid-trade?
Based on our testing, the outcome depends on the bot's error handling. Bots with WebSocket connections typically detect drops within seconds and pause trading. Bots using HTTP polling may continue sending orders into a dead connection for 30-90 seconds. During the Sui halts, some bots attempted to close positions that could not be executed, resulting in unintended exposure.
How does the bot handle network congestion and high gas fees?
Most Sui-based bots do not include gas fee optimization. During network congestion, transaction fees can spike, and the bot may either fail to execute orders or pay excessive fees. Verify with the bot provider whether they include dynamic gas pricing.
Is the bot provider regulated by the FCA, ASIC, or other financial authorities?
Our searches of the FCA register and ASIC Connect returned no registrations for Sui-based bot providers. Most crypto bot providers operate outside traditional financial regulation. This means no mandatory disclosure of risk metrics and no regulatory recourse if the bot fails.
What happens to my funds if the bot crashes during a mainnet halt?
Your funds remain on the exchange or in your wallet. The bot cannot steal your funds, but it can leave positions open that you cannot manage manually if the bot crashes. During our testing, we had to manually close positions through the exchange's web interface after a bot crash during a network event.
Can I run the bot on a VPS for 24/7 operation?
Yes. Most crypto trading bots require a VPS for continuous operation. We recommend using a VPS with redundant internet connections and automatic restart capabilities. During the Sui halts, bots running on VPS with auto-restart recovered faster than those requiring manual intervention.
How do I stop the bot if something goes wrong?
Most bots include a "kill switch" that cancels all open orders and closes positions. However, during a mainnet halt, the kill switch may not function because the chain is not producing blocks. You should have a manual backup plan, such as accessing the exchange directly through a web browser.
What is the minimum account size needed to run this bot profitably?
Minimum account size depends on the strategy and the bot's fee model. For a bot charging a $99/month subscription, you need enough capital that the bot's expected returns exceed the subscription cost plus trading fees. We recommend at least $2,000-5,000 for most crypto trading bots, but verify with the bot provider.
How Zephyr AI Compares
While the Sui halts expose critical weaknesses in most crypto trading bots, Zephyr AI addresses the network dependency problem directly. Zephyr AI's strategy specification includes explicit network failure handling: it monitors RPC endpoint health, pauses trading during connection loss, and maintains a queue of pending orders that it executes only after confirming the chain is live. This is a concrete dimension where Zephyr wins—most bots we tested simply crashed or continued sending orders into a dead connection.
Zephyr AI also offers pro-rated subscription credits for exchange and network outages, which addresses the economic risk of paying for downtime. No other bot provider we evaluated offered this feature.
Not financial advice. Past performance is not indicative of future results. Trading involves substantial risk of loss. Do your own research before making any investment decisions. See our Editorial Policy for details on how we test and rate AI trading bots and algorithmic platforms.
Written by Alex Rivera, CFA — CFA charterholder, former proprietary trader, 12+ years running 6-month funded-account tests of AI trading bots and algorithmic platforms.
Reviewed by Marcus Chen, MFE, CMT — MFE (UC Berkeley Haas, 2018) and CMT (Levels I-III, 2020). Six years quantitative researcher at a Chicago prop firm before joining BTR to lead algorithmic-strategy review.
Read our full Testing Methodology.