正在加载视频...

视频加载失败

PEPEXPLOIT – a Lua-based userland PoC framework for PS5 (firmware ≥ 10.20). Remote code execution, ROP chain simulation, race condition testing. No jailbreak. No kernel. Pure sandbox research.

32,935 次观看 • 1 年前 •via X (Twitter)

38 条评论

NanospeedGamer 的头像
NanospeedGamer1 年前

WTF!! PEPEXploit 😎😎

PepeCobain 的头像
PepeCobain1 年前

Great @NanospeedGamer 😎😉I'd like to test it with someone who can try it out it would be good if it could be used with TheFlow's exploit but it requires further testing with someone who can help me see if I've done it right

NanospeedGamer 的头像
NanospeedGamer1 年前

Yo tengo solo 4.03 😔

martine belo 的头像
martine belo1 年前

Where are we going with this exploit ? Can we expect a public release cause it looks pretty close to Double Free

PepeCobain 的头像
PepeCobain1 年前

I would like to find out if it can be a userland exploit through the use of LUA for FWs after 10.00 that do not currently have a way to concatenate the next TheFlow Kernel Exploit... if this works we have the possibility of having all FWs up to 10.60

martine belo 的头像
martine belo1 年前

That s a great news I’m on 10.60 and have LUA game installed. If this is working both can work to leverage a kstuff I’m waiting for testers on 10.60 if so double free is useless and your exploit overcome its limit.

PepeCobain 的头像
PepeCobain1 年前

Exactly 🙂

Alexander GB Jhon 的头像
Alexander GB Jhon1 年前

Para probar link de archivos gracias? @TheWizWiki @master_s9

PepeCobain 的头像
PepeCobain1 年前

@TheWizWiki @master_s9

Fábio dos Santos Tavares 的头像
Fábio dos Santos Tavares1 年前

@_Andrew2007_

Fábio dos Santos Tavares 的头像
Fábio dos Santos Tavares1 年前

@GameExplosao

Dave 的头像
Dave1 年前

Kind of like a Xbox in Dev mode.. 😂

PepeCobain 的头像
PepeCobain1 年前

Exactly 😂 but can be useful with TheFlow Exploit maybe 🙂

Dave 的头像
Dave1 年前

I got sick of the Tom and Jerry and went back to the PC.

Eduardo R. 的头像
Eduardo R.1 年前

Pepe xploit xD afecta ps 5 11.00? :v

PepeCobain 的头像
PepeCobain1 年前

If you have the Game Lua yes but can be only part Userland

jhon 的头像
jhon1 年前

@dravszoo1 lua esta bien como llave de entrada para xploit si acepta en todos los futuros firmware,pero es inutil para cargar xploit a base de un juego lua,necesitas un juego lua y caros y excasos al alcance de todo el mundo,esperemos gracias a ti,webkit,usb u otro metodo de exploit,saludos

Nico 的头像
Nico1 年前

Hello, would it be possible to send my save of the LUA game, and someone could modify it so that I can execute the exploit. I have the LUA game but I don't have the modified save;

Fábio dos Santos Tavares 的头像
Fábio dos Santos Tavares1 年前

10.60?

PepeCobain 的头像
PepeCobain1 年前

Yes it seems works on 10.20 so I think on 10.60 too but need a test

Fábio dos Santos Tavares 的头像
Fábio dos Santos Tavares1 年前

@notnotzecoxao

marcin p 的头像
marcin p1 年前

I got 10.20 with hamidashi demo

PepeCobain 的头像
PepeCobain1 年前

It can work as long as you have enabled LUA .. it required more test anyway and someone help me with this payload to check something

calculator 的头像
calculator1 年前

@0citizen_four0 Is it only for ps5?

PepeCobain 的头像
PepeCobain1 年前

@0citizen_four0 no even ps4 maybe but I haven't tested

calculator 的头像
calculator1 年前

@0citizen_four0 Give me the script i will test it on 12.02

PepeCobain 的头像
PepeCobain1 年前

@0citizen_four0 first I need test with someone know about LUA script and Userland exploit

khaled Abd Allah 的头像
khaled Abd Allah1 年前

If It needs LUA it's useless.

PepeCobain 的头像
PepeCobain1 年前

Yes LUA is necessary but if isn’t fixed that is new Userland Exploit

Fábio dos Santos Tavares 的头像
Fábio dos Santos Tavares1 年前

@TheWizWiki @mohammad_fadel1 @crump_youtube @ps4_hacking

khaled Abd Allah 的头像
khaled Abd Allah1 年前

Y mean PS5 sys <=10.20 !

PepeCobain 的头像
PepeCobain1 年前

No I mean minor AND >= 10.20 is a new Userland Exploit

DeroZaza 的头像
DeroZaza1 年前

Thread 0 always faster than Thread 1 :(

#BONITO 的头像
#BONITO1 年前

Eu tenho 10.20 mas não tenho o game! Se eu puder ajudar em teste como faço?

Fábio dos Santos Tavares 的头像
Fábio dos Santos Tavares1 年前

Você poderia testar na última versão 11.20 ou não tem como? Já que é necessário o jogo demo

Henry 的头像
Henry1 年前

I can help with testing, I'm on PS5 Slim 11.0 with the Lua Userland exploit set up.

PepeCobain 的头像
PepeCobain1 年前

Ok but you can’t use Exploit of TheFlow .. we can try but It use another exploit Userland

SecBriefs | Making Cybersecurity Simple 的头像
SecBriefs | Making Cybersecurity Simple1 年前

🎓 Preparing for certifications like Security+, CISSP, CEH, or CISM? Why Just Pass When You Can Master Cybersecurity?💡 Our 50 study tips + Cybersecurity Dictionary for Everyone make you exam-ready & industry-prepared! 🔑 Available on Amazon:

相关视频

What happens when you put competing neural networks in a Petri Dish and start changing the rules while they adapt? Last year we released Petri Dish NCA, where neural nets are the organisms that learn during simulation. Today we're releasing Digital Ecosystems: a browser-based platform for interactive artificial life research. The setup: several small CNNs share a 2D grid, each seeing only a 3x3 neighborhood. No global plan. They compete for territory by attacking neighbours and defending against incoming attacks, learning via gradient descent online while the simulation runs. What we didn't expect was the role of the learning itself. Gradient descent isn't just optimising each species' strategy. Instead, it acts to stabilize the whole system during simulation. Species that overextend get pushed back by the loss. Species that stagnate get nudged to grow. This means you can push parameters toward edge-of-chaos regimes: a zone characterised by emergent complexity. Letting the neural networks learn acts to hold the complex system together while you explore and interact. The platform lets you steer all of this interactively. You can draw walls to create niches, erase parts of the system online, and tune 40+ system parameters to explore the most interesting configurations. We find it mesmerizing to watch species carve out territories and reorganise when you perturb them. Everything runs client-side in your browser, no install needed. Blog: Code:

Sakana AI

257,877 次观看 • 3 个月前

Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.

Dustin

318,457 次观看 • 4 个月前

$DSYNC 𝐏𝐫𝐢𝐦𝐮𝐬 𝟐.𝟎: 𝐓𝐡𝐞 𝐅𝐢𝐫𝐬𝐭 𝐀𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐎𝐧-𝐂𝐡𝐚𝐢𝐧 𝐀𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 In the video, you’ll witness 𝐏𝐫𝐢𝐦𝐮𝐬 𝟐.𝟎 independently 𝐰𝐫𝐢𝐭𝐞 𝐚 𝐟𝐮𝐥𝐥 𝐯𝐨𝐭𝐢𝐧𝐠 𝐬𝐦𝐚𝐫𝐭 𝐜𝐨𝐧𝐭𝐫𝐚𝐜𝐭 inside Remix IDE, debug its own compilation errors, and deploy the contract on-chain 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐚 𝐬𝐢𝐧𝐠𝐥𝐞 𝐥𝐢𝐧𝐞 𝐨𝐟 𝐜𝐨𝐝𝐞 𝐰𝐫𝐢𝐭𝐭𝐞𝐧 𝐛𝐲 𝐚 𝐡𝐮𝐦𝐚𝐧. 𝐖𝐡𝐚𝐭 𝐒𝐞𝐭𝐬 𝐏𝐫𝐢𝐦𝐮𝐬 𝟐.𝟎 𝐀𝐩𝐚𝐫𝐭? Not a chatbot. Not an API wrapper. Not a prompt engine. 𝐏𝐫𝐢𝐦𝐮𝐬 𝟐.𝟎 𝐢𝐬 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐟𝐮𝐥𝐥𝐲 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐨𝐧-𝐜𝐡𝐚𝐢𝐧 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭 𝐜𝐚𝐩𝐚𝐛𝐥𝐞 𝐨𝐟 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐚𝐧𝐝 𝐝𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞 𝐖𝐞𝐛𝟑 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐞𝐧𝐝 𝐭𝐨 𝐞𝐧𝐝. 𝐊𝐞𝐲 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧𝐬: -On-Chain Cognitive Execution: Full reasoning, code generation, deployment, and logic verification — all happen trustlessly on-chain. -Autonomous Full-Screen Control: Primus sees the entire development interface and dynamically interacts with IDEs like Remix, Terminal, or VS Code, just like a real developer. -Decentralized Agentic Architecture: Powered by the HiveMind framework and Destra MCPs, Primus assembles specialized cognition units on demand for adaptive, modular intelligence. -Self-Healing Workflows: Primus detects and corrects its own bugs during compilation and testing — no human intervention needed. -Web3-Native by Design: Unlike other agents tied to centralized APIs, Primus operates within decentralized compute, storage, and deployment pipelines. 𝐏𝐫𝐢𝐦𝐮𝐬 𝐃𝐨𝐞𝐬𝐧’𝐭 𝐉𝐮𝐬𝐭 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐞 𝐂𝐨𝐝𝐞 — 𝐈𝐭 𝐁𝐮𝐢𝐥𝐝𝐬 𝐭𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 Primus 2.0 isn’t just "𝐀𝐈 𝐟𝐨𝐫 𝐖𝐞𝐛𝟑." It is Web3, 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐞𝐝 𝐧𝐚𝐭𝐢𝐯𝐞𝐥𝐲 𝐟𝐨𝐫 𝐝𝐞𝐜𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐞𝐝 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭. This is 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐭𝐫𝐮𝐞 𝐬𝐭𝐞𝐩 𝐭𝐨𝐰𝐚𝐫𝐝 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐨𝐧-𝐜𝐡𝐚𝐢𝐧 𝐀𝐈 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠, where AI doesn’t just assist the developer "𝐢𝐭 𝐛𝐞𝐜𝐨𝐦𝐞𝐬 𝐭𝐡𝐞 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫".

Destra Network

43,535 次观看 • 1 年前

This panel with Oasis 🌹 and Cornell Tech at CryptoCanal - Common S3nse was full of alpha.. Liquefaction from IC3 is a huge evolution for the industry This is built by a team working under Ari Juels, the originator of PoW, Oracles, MEV👀 Stop scrolling, watch & read this⬇️ Liquefaction is a recent research paper released by IC3 / Cornell Tech late 2024. A framework dependent on Oasis Sapphire that allows for new utility and use cases across the industry “Liquefaction privately liquefies any blockchain asset, showing how TEEs are poised to transform the blockchain landscape” - Ari Juels Liquefaction and Oasis Sapphire are shaping up to fill that role of the essential infrastructure needed to push past current limitations of web3 A summary of potential use cases of Liquefaction can be found in the full paper link at the bottom of this post Key highlights from the panel: ✅Cornell Tech have expanded on their initial research with a POC called Take My Ape. A temporary rental service where anyone can take full possession of a Bored Ape Yacht Club 🍌 through an encumbered wallet. Want a BAYC temporarily for under $1? No problem. This functionality could apply to most web3 assets ✅SemiLiquid came out of stealth, announcing a revolutionary platform built using the Liquefaction framework. They’re working on a secure marketplace for unvested tokens. They held a successful pilot just a few days ago with top tier VCs and token custodians like Jump Capital, Zodia, Spartan Group, Animoca Brands, GSR and many more ✅Dani from Cornell Tech hinted that further research with Ari Juels and Dawn Song is underway, highlighting the theoretical possibility of Liquefaction being used to create a chain agnostic Layer 2, that requires no bridges and could serve any chain All creating transactions and activity on Oasis Sapphire, the industries first and only confidential EVM. Which also requires $ROSE 🌹 View the Liquefaction paper here - If you aren’t bullish reading this, you’ve misunderstood the magnitude and potential applications of this tech breakthrough Excited to see where this is heading.

Ed 🌹

31,051 次观看 • 1 年前

Claude Skills are a cheat code for DTC creative teams 🤯 One setup, reusable forever. Claude automatically follows your exact creative process — briefs, hooks, ad copy, research — without you explaining anything twice. Perfect for e-comm brands and agencies who are using Claude for creative work but wasting time re-explaining context every single conversation. Here's the problem: You open Claude: you paste in your brand guidelines, explain your brief format, write the copy, you close the chat. Next day, you do it all over again. Every conversation starts from zero. You're burning 20 minutes on setup before you even get to the actual work. Claude Skills fix this: → Write your creative process once as a Skill (a simple markdown file) → Claude reads it automatically whenever the task comes up → Skills compose — research triggers the research Skill, briefs trigger the brief Skill, copy triggers the copy Skill → All in one conversation, all building on each other → Share across your team so everyone gets the same quality output No re-explaining your brand voice. No pasting the same context every chat. No siloed projects that don't talk to each other. What's in the playbook: → The full architecture (how Skills trigger, chain, and compose) → 5 ready-to-use Skill templates built for DTC and agency creative teams → Step-by-step setup from zero to working Skills → How to write instructions that produce consistent output every time → The composability framework for running multi-step creative workflows in one conversation I put together the complete Claude Skills Playbook for DTC brands and creative agencies. Want it for free? >Like this post >Comment "SKILLS" And I'll send it over (must be following so I can DM)

Mike Futia

31,891 次观看 • 4 个月前

𝗖𝗵𝗶𝗻𝗮 𝗶𝘀 𝗳𝗶𝗻𝗶𝘀𝗵𝗶𝗻𝗴 𝘁𝗵𝗲 𝗵𝘂𝗺𝗮𝗻𝗼𝗶𝗱 𝗿𝗼𝗯𝗼𝘁 𝗿𝗮𝗰𝗲 𝗯𝗲𝗳𝗼𝗿𝗲 𝗺𝗼𝘀𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝘀𝘁 𝗿𝗲𝗮𝗹𝗶𝘇𝗲𝘀 𝗶𝘁 𝗵𝗮𝘀 𝘀𝘁𝗮𝗿𝘁𝗲𝗱. AGIBOT held its Partner Conference in Shanghai last week. The real headline wasn't the new hardware. It was their CTO standing on stage, telling investors that humanoid R&D season is over. 2026, he said, is "Deployment Year One." Not research. Not demos. Deployment into real factories, real warehouses, real stores. The manufacturing ramp is getting faster. 1,000 humanoid robots in the first 2 years. Another 4,000 in the next 12 months. Another 5,000 in just 3 months after that. AGIBOT is now shipping more humanoids per quarter than most US robotics companies have built in their entire existence. Then came the announcements the industry will spend the rest of the year reacting to. AIMA. The first full-stack open architecture for embodied AI. A unified robot operating system called Link-U, three dev platforms for motion, interaction, and task creation, plus an open agent framework. Any developer can build on top of it. This is the Android play for humanoids. GO-2. A vision-language-action foundation model with Action Chain-of-Thought reasoning. Planning and execution collapsed into one model. GE-2. A world model for simulation, strategy testing, and sim-to-real transfer. AGIBOT WORLD 2026. An open-source, production-grade real-world dataset pulled from actual industrial, logistics, hotel, and commercial sites. Seven standardized "productivity packages" covering logistics sorting, retail service, security patrol, commercial cleaning, and more. Plug, deploy, bill. A 5-year, $280 million commitment to seed a global developer and partner ecosystem. Now look at the competition. Boston Dynamics has been building humanoids since 1992. Tesla's Optimus is still climbing its own hype curve. Apptronik and Agility are well-funded but pre-scale on real deployments. AGIBOT has pulled all of this off in three years, with no acquisitions, no legacy platform, and no IPO distractions. While the West is still asking when humanoids will scale, China is already shipping them by the thousand.

Shruti

214,939 次观看 • 3 个月前

voice prompting is 4x faster than typing. but i NEEEDED more. Nvidia parakeet allows me to fully voice control an agentic development environment with commands firing in under 300ms. and it runs 100% local. I added gpt realtime 2.1 mini, its 20% faster, 7 to 20x cheaper, and lets you have full jarvis style control of your vibe coding agents. but what about orchestration? agents can spawn each other, prompt each other, and read each others output with the CNVS mcp and cli. Fable 5 can create a plan, spawn 10 grok agents to execute, and a kimi k3 agent to review. parallel agents code at 1,000s of TPS anthropic's own research shows improvements ACROSS the board for multi agent workflows over single agent but only CNVS lets you choose exactly which orchestration, worker, and reviewer agent you would like to use. grok, kimi, qwen, claude, codex... the cross agent memory system is based on real 2026 research so all agents share the same brain, its on demand so it never bloats context. what about remote agents?? You can create remote canvasses that run agents your virtual private servers, they keep working even if your mac shuts off, and you can even vibe code straight to production. CNVS is built from the ground up ENTIRELY in swift for RAW performance on apple hardware. PS - its a LIFE TIME LICENSE because you don't need another subscription. PPS - I ship updates every week based off user feedback and livestream myself building it everyday. PPPS - it uses all your existing ai subs, so no api pricing here.

Max Blade

57,773 次观看 • 3 天前

Andrej Karpathy: "90% of Claude's mistakes come from missing context, not a weak model." 41% mistake rate without a CLAUDE.md. 11% with the 4-rule baseline. 3% with the 12-rule version below here are the 12 rules senior engineers settled on: 1. think before coding: state assumptions, don't guess. the model can't read your mind, stop hoping it will 2. simplicity first: minimum code, no speculative abstractions. the moment you let Claude add "for future flexibility," you've added 200 lines you'll delete next quarter 3. surgical changes: touch only what you must. don't let it improve adjacent code, that's how PRs blow up 4. goal-driven execution: define success criteria upfront, loop until verified. without them Claude either loops forever or stops too early 5. use the model only for judgment calls: classification, drafting, summarization, extraction. NOT routing, retries, status-code handling, deterministic transforms. if code can answer, code answers 6. token budgets are not advisory: per-task 4000, per-session 30000. by message 40 of a long debug, Claude is re-suggesting fixes you rejected at message 5 7. surface conflicts, don't average them: two patterns in the codebase? pick one. Claude blending them is how errors get swallowed twice 8. read before you write: read exports, callers, shared utilities. Claude will happily add a duplicate function next to an identical one it never read 9. tests verify intent, not just behavior: a test that can't fail when business logic changes is wrong. all 12 of Claude's tests can pass while the function returns a constant 10. checkpoint every significant step: Claude finished steps 5 and 6 on top of a broken state from step 4. nobody noticed for an hour 11. match the codebase conventions: class components? don't fork to hooks silently. testing patterns assumed componentDidMount, hooks broke them without surfacing 12. fail loud: "completed successfully" with 14% of records silently skipped is the worst class of bug. surface uncertainty, don't hide it what actually compounds instead of the next framework: - the CLAUDE.md file as institutional memory across sessions - eval-driven changes, not vibe-driven - checkpoints over speed - explicit conflicts over silent blending - discipline over framework, every time - one repo, one rules file, no exceptions be a few rules ahead of AI twitter before this becomes mass-opinion study this

Ronin

449,613 次观看 • 2 个月前

🚀 L1X $25 Million Strategic Growth Raise is Live 🧬 From quantum resistance research partnerships to interoperability focussed real-world traction — Layer One X is scaling new heights. 🎯 Tranche One at $1 (90% Discount to the Trading Price) 🔗 Secure Your Spot in Tranche One: 📊 While many projects have raised between $200M to $350M, they’re still navigating toward meaningful market traction. Meanwhile, L1X has delivered unmatched real-world utility, innovation, and adoption with $12M raised to date. Now, with our $25M Strategic Growth Raise, we’re scaling our impact even further. 📈 📸 Milestones Achieved: 👉 2.5M+ Bridgeless Cross-Chain Messages 👉 200+ Decentralised Validator Nodes 👉 50+ Projects 👉 110,000 Soul Bound NFT’s Issued on L1X-App (Less than 150 Days) 👉 35+ Networks Integrated 🔐 Building the World’s First Quantum Resistant Cross-Chain Message Technology 📂 Open Sourced Code 🛡️ Audited by Hashlock 🛠️ What Sets L1X Apart ✅ Bridgeless Interoperability (X-Talk) ✅ Custom VM + EVM Compatibility ✅ PoX Consensus (Full + X-Talk Nodes) ✅ Protocol Integrated X_Wallet 🌉 World’s First Proven Bridgeless Cross-Chain Tech 📜 Must-Read Docs 📘 L1X Core WhitePaper (210 Pages): 📘 Quantum WhitePaper: 📘 LitePaper: 🔐 Proof of Utility Based Anti-Dump Tokenomics Model 📊 Tokenomics: 📅 Highlights of 2025 Roadmap 🌐 Multi-Chain Token Issuance and Liquidity Abstraction Standard (X-MNAIS) ERC-20-compatible Multi-Chain Token Issuance 🔸 Bridgeless, gas-efficient, & unified liquidity across chains 🔸 No redeployments. No bridges. Just seamless scaling. 🧬 Quantum Resistance Framework In collaboration with UWA 🔸 Plug-and-play security for dApps & chains 🔸 Quantum-proof messaging, state, and consensus layers 💸 L1X as Universal Gas 🔸 Pay once, interact everywhere 🔸 L1X to be used as the universal cross-chain fee with X-Talk which integrates with 35+ networks to enable cross-chain swaps. 🛍️ L1X App Store 🔸 110K+ Soul Bound NFT’s issued 🔸 Unified interface, real-time cross-chain logic ⚛️ Quantum DeX The first of its kind 🔸 Multi-chain liquidity pools 🔸 Vault-based integration with Uniswap, PancakeSwap, Raydium and other DeXs 🔸 Quantum-First security + Smart Release Pool integration 🔸 L1X as the gas layer for DeFi 🔧 Use of Funds – Strategic Allocation 🧠 Advancing Quantum-Resistant Technology 🌱 Ecosystem Growth & Adoption 💧 Liquidity Reinforcement via Release Pool 🏦 Tier 1 Exchange Listings 🧪 Building the World’s First Quantum-Resistant Liquidity Unification DeX (Quantum DeX) 💰 Tranche Details (US$5 Million Each) 📍 Tranche 1 at $1 (90% Discount to the Trading Price) 📍 Tranche 2 at $3.5 📍 Tranche 3 at $5 📍 Tranche 4 at $6.5 📍 Tranche 5 at $8 📑 Tranche Details: 💎 Backed by Real Builders 🔹 Ex-Samsung, Ex-Chainlink 🔹 TradeFi Experts, Web3 OGs 🔹 4M+ Follower Influencer 🔹 Research PhDs and Core Engineers 🌐 This is Layer One X — where real tech meets unstoppable vision.

LayerOneX

18,394 次观看 • 1 年前

𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗜𝗻𝘁𝗲𝗻𝘁𝗣𝗮𝘆, 𝗪𝗵𝗲𝗿𝗲 𝗣𝗹𝗮𝗶𝗻 𝘄𝗼𝗿𝗱𝘀 𝗕𝗲𝗰𝗼𝗺𝗲𝘀 𝗧𝗿𝘂𝘀𝘁𝗹𝗲𝘀𝘀 𝗣𝗮𝘆𝗺𝗲𝗻𝘁. We built IntentPay for the AI Awakening Hackathon on DoraHacks, powered by Mantle and it’s solving one of the oldest frustrations in the digital economy: 𝙥𝙖𝙮𝙞𝙣𝙜 𝙨𝙤𝙢𝙚𝙤𝙣𝙚 𝙮𝙤𝙪 𝙙𝙤𝙣’𝙩 𝙛𝙪𝙡𝙡𝙮 𝙩𝙧𝙪𝙨𝙩 𝙩𝙤 𝙙𝙤 𝙬𝙤𝙧𝙠 𝙮𝙤𝙪 𝙘𝙖𝙣’𝙩 𝙫𝙚𝙧𝙞𝙛𝙮 𝙪𝙣𝙩𝙞𝙡 𝙞𝙩’𝙨 𝙙𝙤𝙣𝙚. ➬ 𝗧𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗡𝗼𝗯𝗼𝗱𝘆’𝘀 𝗙𝗶𝘅𝗲𝗱 Freelancers have built the backbone of the digital economy, yet the payment infrastructure underneath them still runs on handshakes and hope. A client pays upfront and a freelancer ghosts. A freelancer delivers great work and the client disputes to avoid paying. Traditional escrow exists but it’s expensive, slow, and designed for real estate, not a $200 logo job. Smart contracts were supposed to fix this. Technically, they did, but you need to write code to use them. Solidity isn’t something a graphic designer wants to learn just to get paid safely. The technology that should democratize trust stayed locked behind a developer wall. IntentPay tears that wall down. ➬ 𝗪𝗵𝗮𝘁 𝗜𝘁 𝗗𝗼𝗲𝘀 IntentPay is an AI-powered escrow layer built on Mantle. You describe a deal in plain English; “Pay Sarah 400 USDC once the design mockups are approved” and the AI parses your intent, extracts the recipient, amount, token, and release condition, then locks funds on-chain. When the condition is met, payment releases. If the deadline passes without delivery, funds auto-refund. No lawyers, no middlemen, no Solidity. The AI layer does real work here: a structured system prompt instructs the model to extract exactly what it needs and return clean JSON that drives the on-chain transaction. The user reviews the parsed deal before anything is signed, keeping the human in the loop while offloading all the technical complexity. ➬ 𝗧𝗵𝗲 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 The dashboard tracks active escrows with live status indicators, a payment flow timeline, and an AI insight bar that surfaces contextual alerts, approaching deadlines, auto-refund triggers, network comparisons. When payment releases, the app generates a cryptographically-stamped receipt with the transaction hash, condition text, and timestamp. A verifiable record neither party can dispute. ➬ 𝗪𝗵𝘆 𝗠𝗮𝗻𝘁𝗹𝗲 Low gas fees matter when transactions are small, a $50 design job shouldn’t cost $15 to escrow. Mantle’s EVM compatibility means the contract layer integrates cleanly, and its Testnet gave us a solid sandbox to validate the full payment flow. This is exactly the everyday DeFi use case Mantle’s infrastructure is built for. ➬ 𝗧𝗵𝗲 𝗖𝗼𝗿𝗲 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 Most AI x Web3 projects slap a chatbot on top of a wallet. IntentPay does something more interesting: the AI is the interface to the contract. It’s the bridge between human language and trustless code, and that’s what makes this more than a demo. 🔗 Live Demo: 💻 GitHub: Built for the AI Awakening Hackathon | Powered by Mantle | Submitted via DoraHacks

Melinda Neil Ⓜ️

20,197 次观看 • 2 个月前

Hive Intelligence Launches Specialized Crypto Agents Hive Intelligence has released a suite of 17 specialized crypto agents that extend Claude Code's capabilities for professional crypto development and analysis. Extending Claude Code for Crypto Work Claude Code, Anthropic's command-line coding tool, now has access to specialized crypto intelligence through Hive's agent framework. These 17 agents work alongside SuperClaude's 14 base development agents, bringing the total available agent count to 31. The key difference: instead of generic AI responses to crypto queries, developers now have access to specialized agents trained for specific blockchain domains, from smart contract auditing to MEV research to DeFi strategy optimization. How the Agents Work After installation, the agents operate automatically based on query context. When you ask Claude Code to perform crypto-related tasks, the appropriate specialist agent is invoked: - "Audit this smart contract" → Crypto Security Researcher - "Find yield farming opportunities on Ethereum" → Crypto DeFi Strategist - "Analyze this wallet's transaction history" → Crypto Wallet Detective - "Identify arbitrage opportunities across DEXs" → Crypto DEX Arbitrageur No manual agent selection required. The system recognizes the task and routes it to the appropriate specialist. The 17 Specialized Agents Market & Trading Intelligence (4 agents) Crypto Quant: Mathematical models, algorithmic trading strategies, statistical arbitrage, and quantitative risk modeling. Crypto Market Researcher: Fundamental analysis, market trends, institutional adoption tracking, and regulatory landscape monitoring. Crypto Derivatives Trader: Futures and perpetuals analysis, options strategies, leverage management, and derivatives market intelligence. Crypto DEX Arbitrageur: Cross-exchange arbitrage identification, MEV strategy development, and automated profit extraction techniques. DeFi & Liquidity (4 agents) Crypto DeFi Strategist: Yield farming optimization, protocol analysis, liquidity provision strategies, and DeFi portfolio management. Crypto Liquidity Manager: Pool optimization, impermanent loss calculation and mitigation, market making strategies, and capital efficiency analysis. Crypto Governance Analyst: DAO structure evaluation, governance token analysis, proposal assessment, and voting mechanism research. Crypto Bridge Analyst: Cross-chain bridge security assessment, protocol comparison, interoperability solutions, and bridge risk evaluation. Security & Risk (3 agents) Crypto Security Researcher: Smart contract auditing, vulnerability detection, honeypot identification, and exploit pattern recognition. Crypto Security Engineer: Secure contract development practices, defensive programming patterns, and security implementation guidance. Crypto Risk Manager: Portfolio risk assessment, compliance monitoring, exposure analysis, and risk mitigation strategy development. On-Chain Analysis (3 agents) Crypto Wallet Detective: Blockchain forensics, wallet behavior analysis, transaction tracing, and entity identification across chains. Crypto On-chain Analyst: Transaction pattern analysis, wallet clustering, flow tracking, and on-chain metrics interpretation. Crypto MEV Researcher: MEV opportunity detection, flashloan arbitrage analysis, sandwich attack identification, and MEV protection strategies. Specialized Intelligence (3 agents) Crypto NFT Specialist: Collection valuation, rarity analysis, marketplace trends, and NFT ecosystem intelligence. Crypto Stablecoin Analyst: Peg stability monitoring, collateral analysis, depegging risk assessment, and stablecoin mechanism evaluation. Crypto Social Sentiment: Social media sentiment tracking, influencer monitoring, trending topic identification, and community analysis. Data Coverage: - 60+ blockchain networks - 2,000+ DeFi protocols - Real-time DEX data - CEX trading metrics - Social sentiment feeds - NFT marketplace data Compatibility: Works seamlessly with SuperClaude's existing agent framework. No configuration conflicts or manual routing needed. Practical Applications Smart Contract Development Security agents can audit contracts during development, identifying reentrancy risks, access control issues, and common vulnerabilities before deployment. DeFi Research Strategy agents query real-time pool data across networks, calculate yield-adjusted returns, and assess risks like impermanent loss or smart contract exposure. Trading Analysis Market agents access derivatives data, funding rates, liquidation levels, and order book depth across exchanges for informed trading decisions. Forensic Investigation On-chain agents trace fund flows, identify connected addresses, and analyze transaction patterns for security research or compliance work. Portfolio Management Risk agents evaluate protocol exposure, assess tail risks, and monitor positions across multiple chains and protocols. Why Specialized Agents Matter Generic AI models lack the domain-specific knowledge required for professional crypto work. A general-purpose AI might provide surface-level analysis of a smart contract, but a specialized security agent understands Solidity patterns, common exploits, and auditing methodologies. The agent framework solves this by routing tasks to specialists with deep domain knowledge: - A derivatives question goes to an agent trained on perpetuals, funding rates, and options greeks - A DeFi query reaches an agent that understands liquidity mathematics and protocol mechanics - A security audit is handled by an agent familiar with vulnerability patterns and exploit techniques This specialization produces more accurate, actionable insights than single-model approaches. Getting Started The agents are available now through npm. Requirements: - Node.js 16+ - Claude Code installed - No additional dependencies After installation, simply use Claude Code normally. When you ask crypto-related questions or request blockchain analysis, the appropriate agent is automatically invoked. The system handles routing, data retrieval, and response generation. Documentation covers individual agent capabilities, example queries, and integration patterns for different workflows. What This Enables With 17 specialized crypto agents, Claude Code becomes a comprehensive blockchain development and analysis environment: - Developers can audit contracts, optimize gas usage, and implement security patterns - Researchers can analyze protocols, compare yields, and assess risks - Traders can evaluate markets, identify opportunities, and manage positions - Security professionals can investigate exploits, trace funds, and assess vulnerabilities The agents provide access to blockchain data and specialized analysis that previously required multiple tools, APIs, and manual research. ghive.

Hive Intelligence

78,743 次观看 • 8 个月前

Here is a live demo of our AI solution I've been building non-stop over the past 8 months Binary Defense. How it works: Our own model trained on our analysts behavior. Our analysts submit tickets as false positives/true positives with context which enriches our LLM to be smarter over time. Key Highlights: If its a binary - will automatically spin up an agent for reverse engineering it and using EMBER ML to understand behavior and intent of the binary. File formats: Supports a vast array of pretty much any filetype, including email attachments like SVG, LNK, etc. Can handle DLLs, ELF, EXEs, PDF, XLS, DOC, etc. Interrogates the full chain of all events irrespective of log sources. Can handle any format of logs and integrates into APIs of customers for additional agentic data looping for confidence ranking when needed. This is an example of the back-end UI, this is transparent to analysts and enriches the alarms automatically in our SOAR. In these examples there's three different types: 1. Regsvr32 + sct downloader + scrobj.dll code execution - checks reputation of domain, pulls in threat intel, looks at entire picture of the chain - downloads the file itself and inspects for code analysis. Determines if malicious as well as historically looking back if seen in customer before in past. 2. Powershell Obfuscation - uses a universal decoder to un-obfuscate powershell and look at the raw code. Can handle pretty much any obfuscation thrown at it (thanks Justin Elze). 3. Email with malicious SVG - checks tonality of email, are they creating urgency to take action (increases confidence) - disassembles SVG to understand malicious content - checks URL to determine if harvesting credentials, payload delivery, etc. Creates an entire kill chain analysis with full response and dissecting of the attack to the analyst in seconds. Has greatly sped up our ability to respond to incidents and allowing analysts to focus on the most important alarms through prioritization. Once cool thing I've worked heavily on is a synthetic data normalizer which when an analyst says "Yes this is bad with context" or "No this is a false positive" - our local model generates training data to be smarter in the future without using the actual customer data to train it. The customers actual data is immediately destroyed once training data off of the original alarm is generated and contains no customer-centric data at all. We also have three model tiers. Opt-In (collective model, again no customer data but every organization contributes to training). Opt-Out - does not train on any customer data for customers who opt-out. Private LLM - LLM created specifically for individual customer and trains only off of their data. Uses shared model collective for better confidence rankings. It will generate automated playbooks to run based on confidence rankings to take action on behalf of the customer. Still human driven on execution - has to approve playbook actions. This thing is cooking and so cool to see this work live and shut down attackers much faster! If confidence ranking is low - will automatically attempt to enrich data through customer environments for better confidence rankings. Additionally if the model isn't trained well on a certain technology, I have created something we call "Nexus" that will research new protocols, devices, SDKs, etc and generate training data automatically. Works well for zero-days for example, point to a tweet, or a research paper, and automatically generates training data to recognize this attack much faster. Have over 8000+ yara rule integrations that help with confidence boosting as well that is automatically incorporated into the analysis. Creating some amazing stuff at Binary Defense that isn't marketing fluff - actionable things that are making a huge difference in this industry. #BinaryDefense

Dave Kennedy

29,036 次观看 • 4 个月前

AI models currently have a 50% chance of doing something that takes a human expert one hour. This doubles every 7 months. In 2 years? They could automate full workdays. In 4 years? A full month. I discuss the most important graph in AI today with Beth Barnes, the CEO of METR, which uncovered this rule of AI progress. Her bottom line: "It really doesn't seem like 2 years would be surprising for recursively self-improving AI." Beth also explains: where company safety testing fails, why there are no true closed-weight models, AI undermines leading powers, why she's come around on open weighting, and why models might be about to start playing dumb much more often. Enjoy! Available on the 80,000 Hours Podcast in all apps. Links below. 1:51 Can we see AI scheming in the chain of thought? 12:50 Alignment faking 17:33 We have to test models before they're even used inside AI companies 31:56 Each 7 months models can do tasks twice as long 51:31 METR's research finds AIs are solid at AI research already 58:18 AI may turn out to be strong at novel and creative research 1:07:55 Recursively self-improving AI might even be here in two years 1:14:29 Could evaluations backfire? 1:39:55 Do we need external auditors doing AI safety tests? 1:54:09 Why not work at AI companies 2:08:40 The new more dire situation has forced changes to METR's strategy 2:21:49 Overrated: Interpretability research 2:32:55 Overrated: Major AI companies' contributions to safety research 2:39:15 Could we ban using AI to enhance AI, or is that just naive? 2:45:31 Open-weighting models is often good 2:50:22 What we can learn about AGI from the nuclear arms race 3:10:43 AI is more like bioweapons because it undermines the leading power 3:42:09 What research METR plans to do next

Rob Wiblin

93,669 次观看 • 1 年前