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When Depth Becomes an Illusion: Polymarket Faces 'Order Attack' Stress Test

A sophisticated "order attack" is exploiting a critical vulnerability in Polymarket's hybrid off-chain matching/on-chain settlement system. For less than $0.10 in gas fees on Polygon, an attacker can initiate a trade and then, in the brief window before on-chain execution, drain their wallet via a high-gas transfer. This causes the initial trade to fail on-chain due to insufficient funds. However, Polymarket's off-chain system responds by forcibly removing all the legitimate market maker orders that were matched with the failed transaction. This attack has two primary profit methods. First, attackers clear the order book of competitors, create a liquidity vacuum, and then place their own orders with artificially wide spreads to monopolize trading. Second, they "hunt" automated trading bots: after a trade is matched off-chain, a bot hedges its new position, but the attacker then forces the original trade to fail on-chain. This leaves the bot with an unhedged, risky position, which the attacker exploits for profit. One identified attacker address, created in February 2026, reportedly profited over $16,000 in a single day by targeting just 7 markets. The attack severely undermines market maker confidence, threatens the platform's liquidity, and exposes a fundamental design flaw. While the community has developed monitoring tools, Polymarket team has not yet issued an official fix.

比推02/26 04:52

When Depth Becomes an Illusion: Polymarket Faces 'Order Attack' Stress Test

比推02/26 04:52

High-Frequency Trading, $100K Annual Income: The Most 'Boring' Profit Myth on Polymarket

A user known as planktonXD (0x4ffe49ba2a4cae123536a8af4fda48faeb609f71) has generated over $106,000 in profit on Polymarket within a year by executing more than 61,000 predictions—averaging around 170 trades per day. This high-frequency, automated strategy focuses on exploiting small, certain opportunities rather than betting on high-risk, high-reward outcomes. The approach is characterized by market-making and micro-arbitrage: placing orders on both sides of the order book to capture spreads or profiting from mispriced options in low-liquidity markets. The largest single win was only $2,527, illustrating a disciplined, risk-managed method that avoids large drawdowns. The bot operates across diverse categories—sports, weather, crypto prices, politics—constantly scanning for pricing inefficiencies. Notable examples include buying heavily undervalued options in niche markets, such as esports matches or extreme crypto price movements, where probability is mispriced due to emotional trading or thin order books. For instance, a $16 bet on SOL falling to $130 (priced at 0.7¢, implying <1% chance) returned $1,574 during a volatile period. Key takeaways: The strategy highlights the power of compounding small gains, the necessity of automation and API tools, and the superiority of high-probability opportunities over high-risk bets. In prediction markets, the most advanced approach isn’t forecasting—it’s managing probability and liquidity.

marsbit02/11 13:06

High-Frequency Trading, $100K Annual Income: The Most 'Boring' Profit Myth on Polymarket

marsbit02/11 13:06

Making a Profit of $100,000 from 'Mosquito Meat' with 170 High-Frequency Trades per Day?

A quantitative trading bot, planktonXD, generated over $106,000 in profit on Polymarket within a year by executing more than 61,000 predictions—averaging 170 trades per day. Instead of betting on high-risk "black swan" events, it employed a high-frequency market-making and arbitrage strategy, focusing on small, consistent gains with minimal drawdowns. The bot capitalized on mispriced odds in low-liquidity markets—such as regional esports matches and crypto price predictions—by placing tiny bets on highly improbable outcomes that were statistically undervalued. For example, it achieved returns as high as 23,750% on a VALORANT match and 9,285% on a SOL price prediction by buying nearly worthless shares that surged during market panics or emotional mispricings. Key takeaways include the power of compounding small gains, the necessity of automated tools and API access, and the importance of probability management over high-risk bets. The strategy highlights that success in prediction markets lies not in forecasting outcomes, but in exploiting liquidity gaps and probabilistic edges.

比推02/11 12:36

Making a Profit of $100,000 from 'Mosquito Meat' with 170 High-Frequency Trades per Day?

比推02/11 12:36

Essential for Polymarket Developers: 18 Core Open-Source Libraries Proven in Practice

Essential Open-Source Tools for Polymarket Developers: 18 Core Libraries This article compiles a curated list of 18 essential, battle-tested open-source libraries for developers building on Polymarket. The selection is based on GitHub stars (community validation), recent activity, fork count, and reliability scores. Key tools include: - **Polymarket Official AI Trading Agent**: For building automated trading strategies. - **Copy Trading Bots**: Multiple bots to automatically replicate top traders' strategies. - **Arbitrage Bots**: Tools to identify and execute risk-free arbitrage opportunities across markets. - **Automated Market Makers**: Bots for providing liquidity and earning fees. - **Official Client SDKs**: Python, TypeScript/JavaScript, and Rust clients for interacting with Polymarket's Central Limit Order Book (CLOB). - **Data & Analytics Tools**: For real-time market intelligence, historical data retrieval, and building analytical dashboards. - **Multi-Platform API**: A unified API for trading across multiple prediction markets. - **Core Smart Contracts**: The official Conditional Token Framework (CTF) contracts. The list is a subset of a larger, sortable database featuring over 1,500 repositories, categorized by reliability, type, programming language, and activity status.

Odaily星球日报01/27 07:38

Essential for Polymarket Developers: 18 Core Open-Source Libraries Proven in Practice

Odaily星球日报01/27 07:38

Polymarket Developer Essentials: 18 Battle-Tested Core Open-Source Tool Libraries

Essential Open-Source Tools for Polymarket Developers: 18 Vetted Libraries This article compiles 18 essential, community-vetted open-source libraries for developers building on Polymarket. The selection is based on GitHub stars (community validation), recent activity, fork count, and reliability scores. Key tools include: - **Polymarket Official AI Trading Agent (⭐1,869):** For building automated trading strategies. - **Copy Trading Bots (Multiple):** Bots to automatically replicate trades of top performers (e.g., vladmeer's bot, ⭐1,140). - **Arbitrage Bots (Multiple):** Bots to exploit price differences across markets for profit (e.g., vladmeer's bot, ⭐813). - **Automated Market Maker (⭐792):** A bot using Google Sheets to provide liquidity. - **Official Client SDKs:** Python (⭐700), TypeScript/JavaScript (⭐419), and Rust (⭐418) clients for the Polymarket CLOB. - **Data & Analytics Tools:** Libraries for real-time market intelligence (Polyseer, ⭐532) and historical data retrieval (poly_data, ⭐453). - **Multi-Platform & Advanced Bots:** Tools for cross-market trading (pmxt, ⭐396) and bots combining strategies like copy trading and arbitrage. The article also provides a link to a complete database of over 1,500 repositories, sorted by category, programming language, and activity status.

marsbit01/27 07:36

Polymarket Developer Essentials: 18 Battle-Tested Core Open-Source Tool Libraries

marsbit01/27 07:36

86% Return? How to Use a Bot to 'Earn Passively' on Polymarket

This article details the development and backtesting of an automated trading bot for the "BTC 15-minute UP/DOWN" market on Polymarket. The author identified market inefficiencies and automated a manual strategy to exploit them. The bot operates in two modes. In manual mode, users can directly place orders. In auto mode, it runs a two-leg cycle: First, it observes the market for a set time after a round begins. If either the "UP" or "DOWN" side drops by a specified percentage (e.g., 15%) within seconds, it triggers "Leg 1" and buys the crashed side. It then waits for "Leg 2," a hedging trade on the opposite side, which is only executed if the sum of the Leg 1 entry price and the opposite ask price meets a target threshold (e.g., ≤ 0.95). Due to a lack of historical market data from Polymarket's API, the author created a custom backtesting system by recording 6 GB of live price snapshots over four days. A conservative backtest with parameters of a 15% crash threshold and a 0.95 sum target showed an 86% ROI, turning $1,000 into $1,869. An aggressive parameter set resulted in a -50% loss, highlighting the critical role of parameter selection. The author acknowledges significant limitations of the backtesting, including its short data period, failure to model order book depth, partial fills, variable network latency, and the market impact of the bot's own orders. Future improvements include rewriting the bot in Rust for performance, running a dedicated node, and deploying on a low-latency VPS.

marsbit12/30 04:07

86% Return? How to Use a Bot to 'Earn Passively' on Polymarket

marsbit12/30 04:07

How to Build a Polymarket Passive Income Bot from Scratch

Polymarket, a leading prediction market platform on Polygon, allows users to bet on real-world events using USDC. Its open API, transparent order book, low fees, and numerous human traders making errors create a fertile ground for automated trading bots. This article breaks down bot strategies from basic to advanced. Beginner-level bots include airdrop farming bots that generate volume by repeatedly buying and selling the same position, and volatility捕捉 bots that bet on mean reversion after sharp price swings. Intermediate strategies involve market-making bots, which profit from bid-ask spreads and liquidity rewards by placing limit orders, though they require significant capital and risk losses during sudden market moves. Advanced bots include arbitrage bots that exploit pricing inefficiencies between related outcomes (e.g., YES/NO shares summing under 100%), and AI-powered bots that integrate multiple data sources—historical prices, news, on-chain activity, social sentiment—to identify mispriced probabilities and execute trades across hundreds of markets. All bots require access to Polymarket’s API, a Polygon wallet for USDC transactions, historical data storage (e.g., PostgreSQL), and a Python-based toolchain. Bots succeed due to their speed, discipline, scalability, and data-processing capabilities. However, effective risk management is crucial, as strategies can fail due to liquidity issues, unexpected news, or intense competition. Building a profitable AI bot is particularly resource-intensive, akin to running a startup.

Odaily星球日报12/10 03:15

How to Build a Polymarket Passive Income Bot from Scratch

Odaily星球日报12/10 03:15

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