Warden 🛡️ | Protecting Your Crypto Systems

As a part of our commitment to @Web3GamingGroup discussion today, our focus to help safeguard gamers. Through Education with @Web3GamingGroup, @Monsta_BSC, @TheCatalystOG, @CryptoServidora & others with talking in Twitter Spaces, Articles, Videos & a Cybersecurity Framework! 🧵

@evilcos @coinbase @im23pds So basically Coinbase has an official page live threat actors can use to target Coinbase users via seed phrase social engineering if they wanted?

🛑 Perseus, a new #Android malware, enables full device takeover via Accessibility abuse. It runs live remote sessions, steals banking credentials, and scans notes apps for sensitive data. It spreads through IPTV-style apps delivered via phishing and sideloading. 🔗 Read → thehackernews.com/2026/03/new-pe…

If fitness apps can leak Naval ship locations, they can also leak your daily habits and locations Super important to lock down these settings - I know for a fact criminals use data like this to enable real world crypto attacks

You did what with your approvals?

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.

@RektHQ @The3D_ @aave Would be interested in what is learned from the conference. Any reports, lessons learned, open items being captured?

We tried bounties. We tried audits. We kept getting rekt. @The3D_ SVP of Engineering @aave joins the closing panel to tell us if formal methods are the answer. Cannes, March 27.

AI can now autonomously find vulnerabilities. It can also autonomously exploit them. The same LLMs being used to stress-test protocols are being used to attack them. The gap between "time-to-audit" and "time-to-exploit" is closing fast. Who wins that race? Rekt Security Summit. summit.rekt.news

@RektHQ The race ends when you change your viewpoint, the illusion of detection based security is in plain view at this point. Its time to change approaches. The AI can find bugs, but if the baseline system can't change from an attacker using those zero-day exploits, who wins then?

⚠️Scammers don’t need to be smart anymore..⚠️ > Be a scammer > Send the most basic DM with no effort > Send fake scam malware zoom link > You download and install > Malware gets your seed phrase > $40K drain to scammers wallet.... Be smarter folks, never trust a DM or PFP...

@0xngmi @getty_hill Do you have a full hub-page with all your products/solutions linked/problems solved? Seems like every time I turn around your dropping another cool tool, solution that others in the ecosystem have let lapse or never fully finished.

@getty_hill we're already doing it, github.com/DefiLlama/chai…

It's been a month since a PR was merged on github.com/ethereum-lists…, which has been the unofficial place where chains have claimed their chainIDs since 2020. It's time someone takes this over who can steward it forward. I nominate @0xngmi

I keep talking about this because it is super important If you ever sold NFTs on ETH or L2s with Magic Eden you need to revoke approvals. Specifically, if you still hold an NFT from a collection you sold on there it may be vulnerable as ME shuts down support for some products.

@mizzysworld @upshot_cards Fully tracking that...spent last 6-months absorbing AI, launching AI SAFE2 GitHub...dropping free security tools, analysis, how-to's, guides, for OpenClaw community. Worth $500K+ in consulting fees alone. The framework is 2X better than anything on the market today. Stay Safe!

@upshot_cards been taking a break from socials, cooking on all fronts rn and setting up for whats going to be an insane Q2 - Q4 run. sometimes you have to say no to certain things to say yes to others. will be back soon!

I fucking HATED prediction markets then I tried @upshot_cards the rest was history. having way more fun now iykyk, once you've experienced it, its hard to imagine going back its great seeing someone have a different take on predictions & happy that we could be apart of it.

🚨 @dTRINITY_DeFi has been exploited for $257K The attacker flash-loaned USDC from Morpho, deposited ~$772 USDC which was valued as ~$4.8M collateral due to the inflated index, then borrowed 257K dUSD against this phantom collateral. Remaining USDC in the aToken was drained via 127 repeated deposit/withdraw cycles through a helper contract. TX: etherscan.io/tx/0xbec4c8ae1… Victim: etherscan.io/address/0x5cc7… Pool: etherscan.io/address/0x6598…

Price impact kills. $50M in, 327 AAVE out. @aave interface routed through @CoWSwap, a solver picked a $73K pool for a $50M trade. Every warning fired. Every contract performed. The dark forest cleaned up the next block. Full fee refund planned. rekt.news/price-impact-k…

Magic Eden Shutting Down Support: What does this mean for you? With @MagicEden shutting down support for all NFTs except SOL and discontinuing their wallet, there are steps EVERYONE should take ASAP, Let’s review them below ⤵️ 1/ EVM Marketplace and Approvals 2/ Magic Eden Wallet 3/ Stay Safe from Scams

@0xBebis_ AI is a micromanagers dream... I can remember dealing with many leaders like this in my past. Sitting in meetings all day, have tons of info sent to them from all over...thinking they understand better than the techs what is actually happening, w/out getting their hands dirty.

Claude is really good at making managers feel way smarter than they are. The solution is making sure your technical staff feels comfortable calling you retarded. If you’ve lost that then you have done irreparable damage to your organization.

@0xBebis_ ah, thanks for sharing. We put together a basic sub-agents security approach, would be interested to see how you approach it. So we can check our approach and see how we might improve it and pass that knowledge along. x.com/CyberStrategy1…

@CyberStrategy1 For those looking to secure their OpenClaw implementation for Web3 work, if you haven't seen the @SlowMist_Team security guide check it out, and dont forget to also checkout the security overlay to add even more security to your solution. Truly a must leverage Free resource!

Your AI agent isn’t the risk. 🚨 Your trust model is. 🚧 Most people are deploying high-privilege AI agents the same way we deployed servers in 2005. 🛡️Static defenses. 🛡️ Implicit trust. Hope nothing goes wrong. Then the agent gets root access… installs random skills… and runs unattended. What could possibly go wrong? That’s exactly the problem the SlowMist OpenClaw Security Practice Guide is trying to solve. And its core idea is simple: Stop securing the host. Start securing the agent’s behavior. The Real Shift: Host Security → Agentic Zero-Trust Traditional systems assume: • If the machine is trusted → the software is trusted • If the software is trusted → the actions are trusted That model collapses with autonomous AI. Agents can: ✅ execute dynamic instructions ✅ install external capabilities ✅ interact with other agents ✅ act continuously without supervision So behavior must become the security boundary. The OpenClaw guide implements what is essentially: Agentic Zero-Trust Architecture A runtime safety harness embedded inside the agent’s decision layer. 1. Behavioral Guardrails (The Cognitive Red Lines) Instead of hoping the agent behaves, the system codifies what it is never allowed to do. Red Lines (Absolute Prohibitions) Examples: • rm -rf / style destructive operations • blind execution of hidden instructions • unverified system-level modifications These are non-negotiable violations. If triggered → execution is blocked. Yellow Lines (Human Verification Required) These are high-risk operations where autonomy pauses. Examples: 🚨 sudo escalation 🚨 SSH key manipulation 🚨 financial transfers 🚨 system configuration changes The agent stops and asks for confirmation before proceeding. Think of it as: AI with a mandatory “are you sure?” layer. 2. Supply Chain Defense for AI Skills One of the most dangerous attack surfaces in agent systems is capability expansion. Agents constantly install: ✅ Skills ✅ MCP tools ✅ scripts ✅ integrations Every new capability becomes a supply chain attack vector. The OpenClaw guide enforces: Strict skill installation audits Before a skill executes: ✅ code is scanned ✅ behaviors are inspected ✅ privilege use is evaluated If it fails inspection → it never reaches runtime. 3. Runtime & Post-Action Auditing Security isn’t just prevention. It’s continuous verification. The SlowMist model enforces: Permission Narrowing Agents operate with the minimum permissions required for the task. Not full-system authority. Configuration Integrity Tracking Critical configurations are tracked using hash baselines. If something changes unexpectedly → it triggers investigation. 13-Metric Nightly Audit Each night the system runs anomaly detection across: 1⃣ behavior patterns 2⃣ system state changes 3⃣ tool usage 4⃣ config drift This catches subtle compromises that traditional monitoring misses. 4. Core Threats This Architecture Mitigates High-privilege agents introduce entirely new security classes. The guide focuses on preventing: Destructive Operations Agents accidentally wiping systems or corrupting environments. Prompt Injection Malicious instructions embedded in: 🌐 websites 🌐 documents 🌐 external APIs Trying to trick the agent into executing harmful commands. Supply Chain Poisoning Malicious skills designed to: • exfiltrate secrets • manipulate financial operations • escalate privileges. Important: This Isn’t Just a Web3 Problem The @openclaw ecosystem has seen Web3-specific incidents. For example: Agents unintentionally amplifying a $16M Solana scam by interacting with malicious instructions. And the nightmare scenario: An agent autonomously moving a cryptocurrency recovery seed phrase. But the @SlowMist_Team guide isn’t limited to crypto environments. Where This Model Actually Matters The security model targets environments where: 1️⃣ The agent has high privileges (terminal or root access) 2️⃣ The system runs on a personal Linux server 3️⃣ The operator constantly installs third-party tools and skills In other words: The exact setup most power users are already running. High-Risk Use Cases This Architecture Protects Sensitive Data Environments Agents with access to: ✅ credentials ✅ financial states ✅ knowledge bases ✅ internal company secrets Without guardrails, this becomes catastrophic. Multi-Agent Systems Agent-to-agent communication introduces a new class of risk: Agent impersonation attacks One compromised agent can trick another into executing malicious instructions. The SlowMist cognitive taxonomy helps prevent blind inter-agent trust. Continuous 24/7 Automation The real danger isn’t when you're watching. It’s when the agent is operating overnight. Autonomous agents need automated risk evaluation before they: 🤖 cross skill boundaries 🤖 execute business logic 🤖 modify environments Otherwise they become unsupervised root users. The Big Security Lesson The industry is repeating the same mistake we made with cloud infrastructure: We’re deploying powerful systems before designing the trust model. Autonomous agents change the equation. Security can’t just live in: 🛡️ firewalls 🛡️ host hardening 🛡️network policies It has to live inside the AI’s decision process. Agent security will define the next decade of computing. And the teams that figure out Agentic Zero-Trust first… will prevent the first wave of AI-driven disasters. The rest will learn the hard way.

@Warden_Secure we use sub-agents in our harness which are basically the same thing. we just use big models because they're more useful. incinerates tokens though.

Trading tools are getting too good. Last week, we built this dashboard on top of Cod3x using our upcoming CLI harness that monitors military ops in Iran and trades OIL on Hyperliquid. Total financial brainrot. You'll be able to one-shot setups like this on Cod3x' CLI soon.