🌐Security & AI Analysis

How Orbyte AI Ensures Security

Orbyte AI employs cutting-edge artificial intelligence and machine learning models to ensure smart contract security by:

• Pattern Recognition – Detecting known malicious contract patterns based on past scams and exploits.

• Static Code Analysis – Scanning contract source code for vulnerabilities such as reentrancy attacks, integer overflows, and unauthorized access controls.

• Behavioral Analysis – Identifying suspicious functions or logic that could enable rug pulls, hidden minting, or admin backdoors.

• Machine Learning & AI – Continuously learning from newly deployed contracts, refining its ability to detect emerging threats in the blockchain ecosystem.

• Blockchain Data Monitoring – Tracking on-chain activities to detect unusual interactions, liquidity changes, and abnormal transaction behaviors.

AI-Powered Contract Analysis Process

1. Contract Code Extraction – AI pulls the smart contract source code from blockchain nodes.

2. Deep Code Inspection – The AI scans and categorizes contract functions based on risk level.

3. Risk Assessment & Scoring – The AI assigns a security rating based on vulnerabilities, scam likelihood, and compliance with best practices.

4. Automated Report Generation – A detailed security report is generated, outlining potential risks, unsafe functions, and recommended fixes.

5. Continuous Learning & Updates – The AI model evolves as it analyzes new contracts, improving accuracy over time.

Examples of the codes

Example Security on a Smart Contract

This Python script scans Solidity smart contracts for example blacklist functions. It looks for common blacklist patterns such as:

• function blacklist(address user) – A function that adds users to a blacklist.

• mapping(address => bool) private _blacklist; – A private mapping for blacklisted addresses.

• require(!_blacklist[msg.sender]) – A restriction preventing blacklisted users from making transactions.

⚠️ If any of these patterns are found, the script flags the contract as potentially malicious.

import re

def detect_blacklist_function(contract_code):
    """
    Scans Solidity smart contract code to detect blacklist functions.
    """
    blacklist_patterns = [
        r'function\s+blacklist\(',  # Standard blacklist function
        r'mapping\s*\(address\s*=>\s*bool\)\s+private\s+_blacklist',  # Private blacklist mapping
        r'require\s*\(\!\s*_blacklist\[',  # Blacklist check in functions
    ]

    for pattern in blacklist_patterns:
        if re.search(pattern, contract_code, re.IGNORECASE):
            return "⚠️ Blacklist function detected! This contract may restrict certain addresses."
    
    return "✅ No blacklist function detected. Contract seems safe."

# Example Solidity contract snippet
contract_example = """
contract Example {
    mapping(address => bool) private _blacklist;
    
    function blacklist(address user) public {
        _blacklist[user] = true;
    }
    
    function transfer(address to, uint256 amount) public {
        require(!_blacklist[msg.sender], "You are blacklisted!");
        // Transfer logic here...
    }
}
"""

# Run the detector
print(detect_blacklist_function(contract_example))

Example AI Analysis on a Smart Contract

How the AI Analyzes the Contract:

1. Scans the contract code for high-risk patterns (e.g., blacklist(), mint(), onlyOwner transfer etc..).

2. Reduces the security score based on the detected vulnerabilities.

3. Assigns a risk level:

   • Low (Safe ✅)

   • Medium (Caution ⚠️)

   • High (Danger 🚨)

4. Generates a security report listing detected issues and the contract’s risk score.

This is a simplified example, but real AI models would use machine learning and deep code analysis for even more accurate results.

import re
import random

class SmartContractAnalyzer:
    def __init__(self, contract_code):
        self.contract_code = contract_code
        self.risk_score = 100  # Default safe score

    def detect_vulnerabilities(self):
        """
        Identifies suspicious patterns in the smart contract code.
        """
        vulnerabilities = {
            "Reentrancy Attack Risk": r"call\.value\(|transfer\(",
            "Blacklist Function Detected": r"function\s+blacklist\(",
            "Owner-Only Fund Withdrawal": r"onlyOwner.*transfer\(",
            "Hidden Minting Function": r"function\s+mint\("
        }

        detected_issues = []
        for issue, pattern in vulnerabilities.items():
            if re.search(pattern, self.contract_code, re.IGNORECASE):
                detected_issues.append(issue)
                self.risk_score -= random.randint(10, 30)  # Reduce risk score

        return detected_issues

    def generate_report(self):
        """
        Generates an AI-powered security report based on contract analysis.
        """
        issues = self.detect_vulnerabilities()
        risk_level = "Low" if self.risk_score > 70 else "Medium" if self.risk_score > 40 else "High"
        
        report = {
            "Contract Security Score": self.risk_score,
            "Risk Level": risk_level,
            "Detected Issues": issues if issues else ["No major risks found ✅"]
        }
        return report

# Example Solidity contract (simplified for demonstration)
sample_contract = """
contract Example {
    address private owner;
    function blacklist(address user) public { } 
    function mint(uint256 amount) public { } 
    function withdraw() public onlyOwner { msg.sender.transfer(address(this).balance); }
}
"""

# Run AI contract analysis
analyzer = SmartContractAnalyzer(sample_contract)
security_report = analyzer.generate_report()
print(security_report)