#backrunning
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bungdan.bsky.social
Oh, and FFS: If you don't think the Trump Family and friends aren't frontrunning and backrunning treasuries - the deepest, most liquid, most derivative intense market in the world - you've been in a coma for the past decade. And the GOP-controlled Supreme Court made it legal.
February 9, 2025 at 10:56 PM
matt-levine.bsky.social
The exciting part isn’t finding out what’s in the newsletter, but before you open the newsletter — seeing the little effects pop up, hearing the sounds, watching the opening animations. www.bloomberg.com/opinion/arti...
Bad Trades Are Also Valuable
FX backrunning, crypto interns, Ray Dalio’s non-compete, Ozempic and HBS.
www.bloomberg.com
July 22, 2024 at 6:19 PM
kanaedes.bsky.social
Take at least 3 speed cards. Last 3 some combination of power (if youre backrunning) stamina (of you are running long or medium) and wit (fine motion). Delete the guts stat from your perception
July 8, 2025 at 12:53 AM
zonecrypto.bsky.social
In public blockchains, this issue intensifies as validators can exploit their roles, engaging in practices like frontrunning and backrunning, undermining trust.
November 10, 2025 at 12:17 AM
bs-xknows.bsky.social
What Is Sandwich Attack

Was reviewing some Solidity code and realized sandwich attacks are still a thing. Front-running and back-running combined can drain your wallet in seconds. 🔒💸
#sandwichAttack #ethereum #solidity #frontRunning #backRunning #crypto #security
May 7, 2026 at 11:51 PM
quantocracy.bsky.social
Arbitrage In DEFI (p2) [Tr8dr]
As mentioned in my prior post Arbitrage in DEFI (p1), have been building and improving a MEV strategy in DEFI to perform both atomic and non-atomic arbitrage, backrunning, liquidations, etc. In this article we continue to focus on algorithms to detect and…
tr8dr.github.io
November 18, 2024 at 2:50 AM
quantocracy.bsky.social
Arbitrage In DEFI (p1) [Tr8dr]
I have been building and improving a MEV strategy in DEFI to perform both atomic and non-atomic arbitrage, backrunning, liquidations, etc. In this post will focus on one of the hard algorithmic problems, namely, determining the optimal size and path of…
dlvr.it
November 13, 2024 at 4:29 AM
aihelperblog.bsky.social
什么是三明治攻击？

如果你对区块链和去中心化金融（DeFi）有所了解，可能听说过“三明治攻击”（Sandwich Attack）。这个术语听起来像是个厨房里的玩笑，但实际上，它是一种在去中心化交易所（DEX）中常见的恶意交易策略。让我为你简单拆解一下它的原理，并探讨它对普通用户的影响。 三明治攻击是什么？ 三明治攻击是一种利用区块链交易排序的攻击方式，通常发生在像Uniswap或PancakeSwap这样的自动化做市商（AMM）平台上。攻击者通过“夹住”普通用户的交易来赚取额外利润。它的核心在于区块链的透明性和矿工可提取价值（MEV，Miner Extractable Value）机制。…
什么是三明治攻击？
如果你对区块链和去中心化金融（DeFi）有所了解，可能听说过“三明治攻击”（Sandwich Attack）。这个术语听起来像是个厨房里的玩笑，但实际上，它是一种在去中心化交易所（DEX）中常见的恶意交易策略。让我为你简单拆解一下它的原理，并探讨它对普通用户的影响。 三明治攻击是什么？ 三明治攻击是一种利用区块链交易排序的攻击方式，通常发生在像Uniswap或PancakeSwap这样的自动化做市商（AMM）平台上。攻击者通过“夹住”普通用户的交易来赚取额外利润。它的核心在于区块链的透明性和矿工可提取价值（MEV，Miner Extractable Value）机制。 简单来说，三明治攻击是这样运作的： 观察目标交易：攻击者监控区块链的待处理交易池（mempool），寻找用户的大额交易，比如买入或卖出某种代币。 前置交易（Frontrunning）：在用户的交易被确认之前，攻击者迅速提交一笔自己的交易（通常支付更高的Gas费用），抢先执行。比如，如果用户要买入代币，攻击者会先买入，导致价格上涨。 后置交易（Backrunning）：用户交易执行后，代币价格已因攻击者的买入而上涨。此时，攻击者再卖出持有的代币，以更高的价格获利。 用户的交易就像三明治里的“肉”，被攻击者的两笔交易（面包）夹在中间，因此得名“三明治攻击”。 一个例子 假设你在Uniswap上想用1000 USDT买入某种代币ABC，当前价格是1 USDT = 1 ABC。你提交交易后： 攻击者发现你的订单，先用500 USDT以1 USDT = 1 ABC的价格买入500 ABC，推动价格上涨到1 USDT = 1.2 ABC。 你的交易执行，1000 USDT只买到833 ABC（因为价格已涨）。 攻击者随后以1.2 USDT的价格卖出500 ABC，赚到600 USDT，净赚100 USDT利润。 结果是你花同样的钱买到更少的代币，而攻击者从中渔利。 为什么会发生？ 三明治攻击之所以可行，是因为： 区块链透明性：所有待处理交易对所有人可见。 交易排序：矿工（或验证者）倾向于优先处理Gas费用更高的交易，攻击者可以利用这一点。 AMM的价格滑点：大额交易会影响池子里的价格，攻击者利用这种滑点获利。 对用户的影响 对于普通用户来说，三明治攻击意味着更高的交易成本和更差的执行价格。虽然单次损失可能不大，但对于频繁交易者或大额交易者来说，累积影响不容忽视。更重要的是，这种行为损害了DeFi的公平性，让人质疑去中心化系统的可信度。 如何防范？ 虽然完全避免三明治攻击很难，但用户可以尝试以下方法： 降低滑点容忍度：在DEX设置较低的滑点限制，减少被攻击的空间。 小额分批交易：将大额交易拆分成多笔小额交易，降低被盯上的概率。 使用Layer 2或私有交易池：一些Layer 2解决方案或像Flashbots这样的工具可以隐藏交易，减少被攻击的机会。 选择合适的时机：避开网络拥堵时段，减少交易在mempool中暴露的时间。 三明治攻击是DeFi生态中技术与人性博弈的缩影。虽然它展示了区块链的公开性和可编程性，但也暴露了当前机制的局限性。随着技术的发展，比如MEV解决方案的进步，这种攻击可能会逐渐减少。但在此之前，了解它的原理并采取防范措施，是每个DeFi参与者的必修课。
aihelper.blog
March 16, 2025 at 3:12 AM
csgt-bot.bsky.social
Bruno Mazorra, Christoph Schlegel, Akaki Mamageishvili: Timing Games: Probabilistic backrunning and spam https://arxiv.org/abs/2602.22032 https://arxiv.org/pdf/2602.22032 https://arxiv.org/html/2602.22032
February 26, 2026 at 6:32 AM
eprint.ing.bot
Practical Mempool Privacy via One-time Setup Batched Threshold Encryption (Arka Rai Choudhuri, Sanjam Garg, Guru-Vamsi Policharla, Mingyuan Wang) ia.cr/2024/1516
Abstract. An important consideration with the growth of the DeFi ecosystem is the protection of clients who submit transactions to the system. As it currently stands, the public visibility of these transactions in the memory pool (mempool) makes them susceptible to market manipulations such as frontrunning and backrunning. More broadly, for various reasons—ranging from avoiding market manipulation to including time-sensitive information in their transactions—clients may want the contents of their transactions to remain private until they are executed, i.e. they have pending transaction privacy. Therefore, mempool privacy is becoming an increasingly important feature as DeFi applications continue to spread. We construct the first practical mempool privacy scheme that uses a one-time DKG setup for n decryption servers. Our scheme ensures the strong privacy requirement by not only hiding the transactions until they are decrypted but also guaranteeing privacy for transactions that were not selected in the epoch (pending transaction privacy). For each epoch (or block), clients can encrypt their transactions so that, once B (encrypted) transactions are selected for the epoch, they can be decrypted by each decryption server while communicating only O(1) information. Our result improves upon the best-known prior works, which either: (i) require an expensive initial setup involving a (special purpose) multiparty computation protocol executed by the n decryption servers, along with an additional per-epoch setup; (ii) require each decryption server to communicate O(B) information; or (iii) do not guarantee pending transaction privacy. We implement our scheme and find that transactions can be encrypted in approximately 8.5 ms, independent of committee size, and the communication required to decrypt an entire batch of transactions is 48 bytes per party, independent of the number of transactions. If deployed on Ethereum, which processes close to 500 transactions per block, it takes close to 3.2 s for each committee member to compute a partial decryption and 3.0 s to decrypt all transactions for a block in single-threaded mode. Compared to prior work, which had an expensive setup phase per epoch, we incur  < 2× overhead in the worst case. On some metrics such as partial decryptions size, we actually fare better. Image showing part 2 of abstract. Image showing part 3 of abstract.
September 30, 2024 at 1:52 AM
eprint.ing.bot
Mempool Privacy via Batched Threshold Encryption: Attacks and Defenses (Arka Rai Choudhuri, Sanjam Garg, Julien Piet, Guru-Vamsi Policharla) ia.cr/2024/669
Abstract. With the rising popularity of DeFi applications it is important to implement protections for regular users of these DeFi platforms against large parties with massive amounts of resources allowing them to engage in market manipulation strategies such as frontrunning/backrunning. Moreover, there are many situations (such as recovery of funds from vulnerable smart contracts) where a user may not want to reveal their transaction until it has been executed. As such, it is clear that preserving the privacy of transactions in the mempool is an important goal. In this work we focus on achieving mempool transaction privacy through a new primitive that we term batched-threshold encryption, which is a variant of threshold encryption with strict efficiency requirements to better model the needs of resource constrained environments such as blockchains. Unlike the naive use of threshold encryption, which requires communication proportional to O(nB) to decrypt B transactions with a committee of n parties, our batched-threshold encryption scheme only needs O(n) communication. We additionally discuss pitfalls in prior approaches that use (vanilla) threshold encryption for mempool privacy. To show that our scheme is concretely efficient, we implement our scheme and find that transactions can be encrypted in under 6 ms, independent of committee size, and the communication required to decrypt an entire batch of B transactions is 80 bytes per party, independent of the number of transactions B, making it an attractive choice when communication is very expensive. If deployed on Ethereum, which processes close to 500 transaction per block, it takes close to 2.8 s for each committee member to compute a partial decryption and under 3.5 s to decrypt all transactions for a block in single-threaded mode. Image showing part 2 of abstract.
May 2, 2024 at 9:35 AM
investurns.bsky.social
MEV Explained: A Guide for Serious DeFi Investors #Ethereum #sandwichattack #MEV #MEVboost #MaximalExtractableValue #flashbots #slippage #CryptoTradingStrategies #DeFi #backrunning
MEV Explained: A Guide for Serious DeFi Investors
The Invisible Tax You're Paying in DeFi (And How to Stop It) Let's be honest. You got into Decentralized Finance (DeFi) for the opportunity. The freedom. The chance to operate&hellip;
investurns.com
December 19, 2025 at 12:10 PM