SlowMist

Recently, we’ve shipped a small but solid update to the Crypto Asset Tracing Handbook! 📘✨ 📖Updated version on GitHub: github.com/slowmist/Crypt… 🚀These additions expand the handbook’s coverage of cross-chain and laundering patterns — topics that many readers have been asking for: 1️⃣More bridge explorer links🔗: • Squid • Orbiter • TeleSwap 2️⃣Two new case studies🔍: • BTC Laundering Loops via Hyperunit • Cross-Chain Source Analysis via Stargate Finance If you’ve already read the handbook, this update makes it even more actionable. If you haven’t yet — now’s a great time to dive in. 🛡️We’ll keep refining the handbook over time to make on-chain tracing knowledge accessible to everyone in the crypto ecosystem.

Analyzed by SlowMist AI👇 1️⃣ Attack Overview 🔍 💥 Attack Type: Missing Access Control leading to malicious burn of LP pool tokens, causing extreme AMM price distortion followed by arbitrage 🎯 Victim Contract: ShiMama/Shibaba LP Pool (0x564cb2bae0b35cfc8c77d94d65015fe898f8f927) 🧑‍💻 Attacker Address: 0xd10880e7591e30a336b28a5855f0ccb4b8c7c8e9 (EOA) 📦 Attack Contract: 0xcf7380462b7ca3e9f1717d17372eb093bf87f8d5 (Dynamically deployed in this transaction) 💰 Profit Amount: Approx. 52.98 WBNB (Net profit, after deducting 30.78 shimama token cost and gas) 2️⃣ Root Cause of Vulnerability 🧠 📄 Contract: ShiMamaProtocol (0x5049d10378356fde0b44c93fa7bb75836f10b49a) ⚙️ Function: executePairBurn(uint256 referenceIn, uint256 minPullFromPair, uint256 deadline) ❗ Defect: This function lacks any form of access control, allowing any external address to call it. The attacker can pass an arbitrarily large referenceIn parameter, combined with pairBurnBpOnSell = 10000 (100% burn ratio), to forcefully extract and burn almost all shimama tokens from the LP pool in one go. 📉 This causes the shimama balance in the LP pool to approach zero, leading to an extreme distortion in the AMM pricing mechanism—allowing the attacker to swap out a large amount of shibaba tokens for arbitrage using a very small amount of shimama. 3️⃣ Critical Vulnerability Code as shown in the figure below. 💻 4️⃣ Attack Step Sequence 🧩 🚀 Preparation Phase (Off-chain): The attacker EOA 0xd108... pre-holds approximately 30.78 shimama tokens. 🔗 On-chain Execution: 🔹Deploy Attack Contract 🔹Query Flash Loan Amount + Approve Repayment 🔹Initiate Flash Loan (≈374,585 WBNB) 💸 🔹Callback: Acquire shimama Tokens 🔹Callback: Query LP Pool shimama Balance 🔹Execute executePairBurn (Core Exploit) 🔹Arbitrage Swap (shimama → shibaba → WBNB) 🔹Extract Profit (~52.98 WBNB) 🔹Repay Flash Loan 🔹Result: LP pool loses massive liquidity (shimama + shibaba). Attacker nets ~52.98 $WBNB 5️⃣ Analysis Confidence Statement 📊 ✅ High Confidence (Code Verified) ✅ High Confidence (Trace Verified) ⚠️ Medium Confidence (Some inferred steps, non-critical) 🛡️ Takeaway: Missing access control + extreme parameter settings = catastrophic LP manipulation risk Stay safe.

🦞 Following our previous v2.7 release, OpenClaw Security Practice Guide v2.8 Beta is now live. ⤴️ v2.8 Beta has been validated through hundreds of hours in production, but is still actively evolving. It now covers the latest models including #Gemini / #Opus / #Kimi / #MiniMax / #GPT. 👉 v2.7 remains the stable version — use v2.8 if you want the latest enhancements: github.com/slowmist/openc… Key upgrades vs v2.7: 🤖 Agent-assisted deployment workflow (5-step automation) 🛡️ --light-context Cron anti-hijacking 📝 Hardened inspection script standards 📂 Persistent reports at $OC/security-reports/ + 30-day rotation 🔄 Post-upgrade baseline rebuild process 🔍 Enhanced code audit protocol ⚡ Token optimization (pre-filter in Bash before LLM) 🧠 7 real-world lessons learned (timeouts, model choice, false positives, etc.) ⚠️ Please read the README carefully before use.

We’re currently assisting @more_login with the investigation. Good news: together with relevant platforms, a portion of the funds has been successfully frozen. 🛑 The investigation is still ongoing—please stay tuned for official updates.

🚨 AI is trading for you now. But is your money safe? Proud to collaborate with @bitget, @Bitget_zh on our latest research: #AI Agents> 🎉🎉 ⚠️ Prompt injection can hijack trading decisions 🔌Malicious plugins can steal your data & keys 🔑Leaked API = full account execution access 🤖One wrong autonomous action = real asset loss In #Web3, mistakes are irreversible. Protect your funds before it’s too late. We present a 5-layer security framework + practical checklists for users & devs. 🛡️ Dive in 👉 slowmist.medium.com/slowmist-bitge…

@jeffsecurity Thanks for the shoutout! Hope it helps more people use OpenClaw more securely.🤗

Planning to use OpenClaw? Make sure you read this safety guide from SlowMist first!!! github.com/slowmist/openc…

SlowMist KYT equips VASPs with the tools to stay ahead of regulatory requirements and structural risks, turning reactive compliance into proactive, auditable #AML operations.💡 🚀 Deployment Options: • Starter Plan — Early-stage teams, < $1 per check, up to 3 members • Enterprise Plan — Rapid-growth platforms, tiered pricing, up to 10 members 🤝We welcome interested organizations to contact us for trial inquiries and procurement! 👉Email: kyt@slowmist.com

6️⃣Stablecoin Ecosystem Risk Monitoring Handling #stablecoins? SlowMist KYT keeps you one step ahead. 🚀 🔄 Fully automated continuous screening ⏱️ Monitors every blockchain transaction in real time 💰 Detects high-risk exposure during issuance, redemption & large transfers 🌐 Gives issuers & regulators a complete view of the risk landscape 💡 Stay proactive, spot risks early, and protect your stablecoin ecosystem

⚠️ With crypto adoption growing and stablecoins accelerating cross-border fund flows, VASPs face increasingly complex #AML & #KYT challenges. 🎉🎉🎉We're thrilled to announce our new product: SlowMist KYT, transforming years of blockchain intelligence into a full-lifecycle compliance system 👋For more detailed industry insights and AML trends, read our latest report: slowmist.medium.com/the-cat-and-mo…

9/ AI Security Open-Source Resources by @SlowMist_Team 🔓 To help developers build safer environments for #AI Agents and #Web3 systems, we’ve open-sourced several security tools and resources: 📘 OpenClaw Security Practice Guide An end-to-end deployment guide for securing high-privilege AI Agents in real production environments. github.com/slowmist/openc… 📋 MCP Security Checklist A structured checklist to audit and harden Agent services, MCPs, Skills, and AI toolchains. github.com/slowmist/MCP-S… 🧪 MasterMCP A malicious MCP server example for security research and defense testing, helping teams reproduce real attack scenarios. github.com/slowmist/Maste… ⛓ MistTrack Skills A plug-and-play Agent skill that enables on-chain AML compliance checks and address risk analysis. github.com/slowmist/mistt… These resources help developers understand real-world AI Agent attack paths and defense practices. Need support with AI Agent security or Web3 governance? 👇 Get in touch 📩 team@slowmist.com

8/ How the Core Security Capabilities Work Together 🧩 In this architecture, MistEye, @MistTrack_io, and MistAgent are not isolated tools — they operate within the execution chain of the user’s AI Agent (e.g., @openclaw). Their roles are clearly layered: 👁MistEye → Detect potential threats and risks before execution ⛓ @MistTrack_io → Perform on-chain risk determination for addresses and transactions 🧠MistAgent → Conduct deep analysis of complex or uncertain threats 🔧 Together, they enable Agents to operate with security that is: perceptible → controllable → auditable → recoverable even in high-value Web3 scenarios. Appendix: Mapping of ADSS Services to the Implementation of This Solution👇

🚨 AI Agents like #openclaw are evolving into high-privilege operators across AI and Web3 environments. To address these risks, we introduce a comprehensive security Solution for #AI and #Web3 Agents — designed to make autonomous systems observable, controllable, and auditable.✨ 🛡️ The architecture forms a five-layer “Digital Fortress” around AI Agents: 🔹 MistEye serves as the retina (threat perception) 🔹 MistTrack as the immune system (on-chain risk control) 🔹 OpenClaw security practices as the skeleton (behavioral constraints) 🔹 MistAgent as the brain (deep analysis and auditing) 🔹 ADSS as the armor (full lifecycle protection) 🔗 Read the Full Security Solution: slowmist.medium.com/comprehensive-…