Decentralized Hybrid Exchange System Featuring Automated Sniping, Anti-Rug Mechanisms, AI-Driven Trade Execution, and Revenue Sharing via Tokenized Architecture
Abstract
The present invention discloses a decentralized hybrid exchange system that combines advanced automated trading capabilities, AI-driven transaction logic, anti-rug safeguards, and token-based revenue distribution. Leveraging high-speed sniping bots integrated with mempool monitoring and machine learning algorithms, the invention identifies and executes trades on newly launched tokens with precision and minimal slippage.
A multi-tiered anti-rug framework is built into the core architecture to detect liquidity withdrawal anomalies in real-time, automatically halting suspicious transactions before execution. To address infrastructure scalability and performance, the system utilizes Microsoft Azure-based containerized services, enabling global distribution, load balancing, and API reliability across multiple failover zones.Smart contracts form the backbone of user interaction, governing liquidity pool contributions, revenue sharing mechanisms, and staking logic. Revenue generated from trading fees is distributed proportionally to users through a secure escrow system based on staking participation snapshots.
This invention provides a resilient, compliant, and performance-optimized alternative to traditional DEX platforms by merging ethical decentralized finance principles with enterprise-grade infrastructure and intelligent automation.
Background of the Invention
Existing decentralized exchanges (DEXs) have made significant strides in democratizing access to financial instruments; however, they suffer from fundamental vulnerabilities that compromise user trust, trading efficiency, and long-term viability. These limitations are particularly evident in three primary areas: platform security, economic alignment, and infrastructure performance.
DEX Vulnerabilities
One of the most prevalent issues in current DEX platforms is the susceptibility to rug pulls, where malicious actors deploy tokens, build liquidity, and later extract value suddenly, leaving users with worthless assets. Inadequate monitoring of on-chain liquidity and poor enforcement of locking mechanisms have made it difficult to detect or prevent such attacks in a timely fashion.Moreover, sandwich attacks, frontrunning, and bot-driven manipulation frequently compromise the fairness of token launches.
Lack of Incentive Alignment
Many decentralized platforms lack a sustainable reward structure that benefits both users and protocol operators. While liquidity providers may receive yield, average traders and token holders are often excluded from profit-sharing mechanisms. This misalignment reduces user retention and disincentivizes long-term engagement.Additionally, governance models are often opaque or dominated by early token whales, making it difficult for communities to shape protocol evolution.
Speed and Scalability Issues
Traditional DEX architectures operate directly on the blockchain without optimization for high-frequency trading or lowlatency execution. As a result, slippage and failed transactions remain common under congested conditions. Block confirmation delays and mempool processing limitations further exacerbate execution risks. Moreover, few projects have successfully integrated enterprise-grade infrastructure to mitigate these challenges through cloud-native technologies. There is a clear need for a hybrid decentralized exchange that addresses these shortcomings through AI-driven automation, real-time fraud prevention, robust infrastructure integration, and an equitable, smart contract-based revenue model. The present invention meets this need.
Summary of the Invention
The present invention provides a novel decentralized hybrid exchange platform that integrates AI-driven sniping bots, anti-rug pull protections, and an ethical, token-based revenue-sharing system deployed within scalable Microsoft Azure infrastructure.
Unlike traditional DEXs, this system features a tightly integrated automated trading module, capable of scanning blockchain mempools in real-time to identify new token listings. The AI-powered scoring engine analyzes token legitimacy using factors such as deployer history, liquidity structure, and contract behavior.Upon favorable scoring, the bot constructs and executes a trade with dynamic slippage tolerance, gas optimization, and safety validation.
To mitigate liquidity fraud, an embedded anti-rug engine continually monitors liquidity pools. When it detects anomalies, such as rapid withdrawals below configurable thresholds, it triggers a contract-level lock and halts execution, while simultaneously alerting users and governance systems.
The revenue model leverages smart contracts to accumulate transaction fees and distribute rewards to token stakers based on periodic wallet balance snapshots. These rewards are routed through an escrow smart contract, enabling non-custodial claiming via a user-friendly interface.
Biokript’s patented key security framework ensures non-custodial, institutional-grade protection while enabling advanced features like sessionbased trading, delegated strategies, and automation. Our architecture integrates with secure providers (e.g., Turnkey) to deliver air-gapped private key storage, client-side encryption, and zero centralized access. All keys remain under user control, with full exportability and multi-sig recovery options. To comply with our standards, integrated systems must encrypt keys client-side, store them offline, support 2FA/multi-sig, and allow complete user access control. This patented system offers the security of decentralized custody with the functionality of centralized platforms without compromising transparency or user sovereignty.
Infrastructure-wise, the platform is hosted using Azure Kubernetes Service (AKS), containerized for elasticity and resilience. Load balancers, API gateways, automated failover, and encrypted key vaults ensure enterprisegrade reliability and security.
This invention provides a robust solution to common DEX problems, including lack of safety, slow execution, poor user incentives, and technical centralization. By combining on-chain smart contract automation with offchain AI intelligence and cloud infrastructure, it delivers a next-generation decentralized exchange optimized for speed, fairness, compliance, and profitability.
Brief Description of the Drawings
Figure 1 : Architecture Diagram of Biokript DEX Ecosystem shows the core exchange structure, including user wallets, sniper bot module, revenuesharing logic, smart contracts, liquidity pools, and cloud infrastructure hosted on Microsoft Azure.
Figure 2 :Flowchart of AI Sniper Bot Operation illustrates the sequential operation of the bot: mempool listener → token scoring engine → trade constructor → slippage validator → signed transaction execution.
Figure 3 : Anti-Rug Logic and Liquidity Threshold Alert System depicts the antirug mechanism, showing real-time liquidity monitoring → anomaly detection → execution lock → user/gov notification.
Figure 4 : Token Revenue-Sharing Distribution Mechanism outlines how fees are aggregated and distributed: wallet staking module → snapshot engine → profit aggregator → escrow contract → user claim interface.
Figure 5 : Azure Node Deployment and API Routing Diagram describes cloud architecture including AKS container clusters → load balancers → failover strategy → API Gateway → monitoring systems and key vault integration.
Figure 6 : Biokript’s Key Security Framework details air-gapped storage, clientside encryption, zero centralized access, and secure multi-signature recovery, ensuring full user control and protection of private keys at all times.
Detailed Description of the Invention
This section provides a comprehensive breakdown of the invention’s technical components and design logic, organized into the following subsections. Each section expands on core innovation principles with technical specifics, usage scenarios, and integration mechanisms.
System Architecture
The Biokript system architecture is designed to integrate decentralized finance (DeFi) protocols with enterprise-grade cloud computing. It employs a service-oriented architecture (SOA) combined with decentralized smart contract ecosystems to allow secure, scalable, and highly automated exchange operations. The system comprises six core layers:
Client Interaction Layer
- • Web3 wallets (MetaMask, Phantom, Trust Wallet)
- • Browser extensions and mobile apps
- • Multi-language support (React + i18n)
API & Gateway Layer
- • Azure API Gateway
- • GraphQL interfaces
- • Rate-limiting and IP blacklisting
Business Logic Layer
- • Liquidity router logic
- • Smart order routing (SOR)
- • Bot orchestration microservice
Smart Contract Layer
- • Sniping and staking contracts
- • Distribution and governance
- • Rug detection mechanisms
Data Management Layer
- • Azure Cosmos DB for user logs and statistics
- • PostgreSQL for admin reporting dashboards
- • Blob Storage for off-chain logs (e.g., slippage events, blocked TXs)
Infrastructure Layer
- • Sniping and staking contracts
- • Utilizes AKS (Azure Kubernetes Service), Azure Key Vault, Azure Monitor
Key Security Framework Layer
- • Air-Gapped Private Key Storage
- • User-Controlled Encryption
- • No Centralized Key Access
- • Secure Key Recovery Mechanisms
AI Sniper Bot Algorithms & Models
The AI sniper bot is designed as a real-time trading engine trained on token behavioral datasets. It performs predictive trade execution with built-in security and volatility filtering.
Key Components
Mempool Aggregator
- • Uses multiple RPC endpoints to prevent spoofing
- • Implements message queues to buffer bursty events
Scoring Algorithm
- • Token metadata: supply, renounced ownership, tax structure
- • Liquidity health: LP ratio, LP lock, burn address activity
- • Code vectorization: Bytecode embeddings using BERT-like transformer
- • Output: 0–1 score; min required: 0.87 for execution
Execution Control:
- • Multi-wallet concurrency engine (4–16 wallets/bot instance)
- • Flashbots RPC or Solana priority fees
- • Gas optimization module
Sample Pseudocode:
for token in new_tokens:
score = AI_model.predict(token.features)
if score > 0.87:
execute_trade(token)Anti-Rug Logic & Governance
This logic monitors pool behavior using:
Liquidity Feed:
- •: Real-time liquidity snapshots every 3 seconds
Anomaly Engine:
- • Rapid LP burn (30% in 1 minute)
- • Owner activity during freeze window
- • Code vectorization: Bytecode embeddings using BERT-like transformer
- •Price plunge detection via TWAP (Time-Weighted Average Price)
Scoring Algorithm:
- • Token metadata: supply, renounced ownership, tax structure
- • Liquidity health: LP ratio, LP lock, burn address activity
- • Code vectorization: Bytecode embeddings using BERT-like transformer
- •Output: 0–1 score; min required: 0.87 for execution
Smart Contract Logic:
if (lpBurnRatio > 30 && tx.origin == owner) {
lockTrading(token);
emit Alert(msg.sender, token);
}Governance Features: :
- • Token-level freeze vote
- • Minimum quorum: 20% staked BIOKRIPT
- • Admin override in emergencies
Smart Contract Revenue Sharing
Revenue is distributed through a staking and snapshot mechanism.
Staking Contract
- • Lock-in options: 7d, 30d, 90d
- • Rewards: Scaled by duration and amount
Snapshot Engine:
- • Snapshots Every 1,000 blocks
- • Snapshot ID hashed for immutability
Reward Aggregator:
function aggregateFees() public onlyOperator {
for each snapshot in cycle {
distributeProportionally(snapshot.id);
}
}Claim Ui:
- • Connected via Web3 modal
- • Supports Ledger, Trezor
Azure Deployment Design
The system is hosted across 3 Azure regions with the following architecture:
AKS Cluster:
- • Node pools for bot, API, and monitor
- • Horizontal scaling with autoscaler
Key Vault:
- • RBAC access control
- • Secrets for bots signed with HSM
Monitoring:
- • Azure Monitor integration
- • Alerts integrated with Slack/Telegram bot
Disaster Recovery:
- • DNS failover across regions
- • Terraform-based auto redeploy
Biokript Patented Key Security Framework
As part of Biokript’s commitment to non-custodial security and institutionalgrade functionality, we have developed a patented key security mechanism to support advanced features such as session-based trading, delegated strategies, and automated execution, all without compromising user control.
Key Security Architecture
Biokript’s system integrates with specialized infrastructure providers (e.g., Turnkey) to offer a zero-custody, fully decentralized key management solution, designed for high-security, high-availability DeFi use cases.
Core Requirements
- • Air-Gapped Private Key Storage: All private keys are stored in physically isolated, fully offline environments to eliminate remote access vulnerabilities.
- • User-Controlled Encryption: Keys are encrypted on the client side before any interaction with the platform. Biokript never sees or stores unencrypted key material.
- • No Centralized Key Access: Built on zero-knowledge architecture, no single party, including Biokript, can access or decrypt user keys.
- • Secure Key Recovery Mechanisms: Backup and multi-signature recovery options ensure safe access restoration in case of device loss or compromise.
Compliance Requirements for Integrated Key Systems
- • Encrypt all keys client-side prior to transmission
- • Store encrypted keys in isolated, offline vaults or HSMs
- • Enable two-factor or multi-signature access control for signing
- • Allow full user control, exportability, and revocation of key access
This patented approach ensures that Biokript users retain absolute control of their digital assets, while enabling advanced features typically reserved for centralized platforms — all within a secure, decentralized, and verifiable environment.
Tokenomics & Compliance
Token Specifications
- • Fixed supply: 1 billion BIOKRIPT
- • No inflation: Deflationary model
- • Rewards vault: 2% locked for distribution
Use Cases
- • Fee discounts (up to 50%)
- • Voting on new token listings
- • Access tiers for sniper bot
Compliance Features
Optional KYC via zk-SNARKS
Geo-blocking via Cloudflare Workers
API for Koinly, TokenTax
Simulated Use Case Scenarios
Scenario 1: Token Launch Sniping
• Token XYZ launches on Solana
• Mempool listener captures LP add
• AI bot scores it 0.91
• TX constructed and executed in 1st block
Scenario 2: Rug Prevention
• Token ABC shows 40% LP withdrawal
• System flags anomaly
• Bot disables trade engine
• Governance vote confirms lock
Scenario 3: User Reward Cycle
• User stakes 50,000 BIOKRIPT
• Receives 1.2% of $13,000 revenue pool
• Claims via dApp after 14 days
Claims
1. A decentralized hybrid exchange system comprising:
- a mempool monitoring engine configured to detect token deployment events in real-time;
- an AI-based token scoring module that evaluates token legitimacy using machine learning models trained on historical fraud patterns;
- a slippage validator designed to assess and prevent unfavorable price movements during trade execution;
- an automated trade execution engine that operates without manual input, capable of constructing and submitting signed transactions;
- smart contracts for handling transaction routing, staking, reward calculation, and revenue distribution;
- a containerized cloud infrastructure deployed using Microsoft Azure services, enabling scalability, redundancy, and secure operation; wherein the system executes autonomous, intelligent token trades at the moment of deployment, subject to safety validations.
2. The system of claim 1, wherein the mempool monitoring engine:
- continuously listens to blockchain pending transaction pools;
- filters for token deployment and liquidity addition events;
- uses gas analysis and timestamping to prioritize signals;
- initiates token scoring only for tokens meeting predefined launch conditions.
3. The system of claim 1, wherein the AI-based token scoring module utilizes:
- feature vectors derived from on-chain contract metadata;
- known fraud signatures such as honeypot code patterns, blacklist conditions, or zero-tax mirroring traps;
- a model selection engine that switches between decision trees, neural networks, and ensemble classifiers based on accuracy metrics;
- an output confidence threshold that must be met for a token to be eligible for trade.
4. The system of claim 1, wherein the slippage validator includes:
- a predictive estimator that compares simulated vs. expected trade outcomes;
- logic to adjust slippage dynamically based on gas congestion or liquidity depth;
- user-defined safety thresholds for maximal price deviation;
- a fallback rejection path for failing slippage conditions.
5. The system of claim 1, further comprising an anti-rug module that:
- continuously calculates liquidity deltas in token-paired pools;
- detects anomalies such as sudden LP token burn or transfer to deployer wallet;
- flags such behaviors and automatically freezes trading activities involving the flagged token;
- sends real-time notifications to off-chain systems, including a governance dashboard;
- offers governance-based override where community members can vote to unlock the token.
6. The system of claim 1, wherein the smart contract layer includes:
- a staking contract that records lock durations and staking weights for users holding the BIOKRIPT token;
- a snapshot engine that periodically records wallet balances;
- a profit aggregation module that calculates proportional rewards using on-chain data;
- an escrow contract from which users may claim earned rewards, with optional timelock.
7. The system of claim 1, wherein the backend is deployed across multiple Microsoft Azure services, comprising:
- Azure Kubernetes Service (AKS) clusters running bot agents and APIs;
- Azure Load Balancer for evenly distributing traffic across endpoints;
- Azure Key Vault configured to manage signing keys and credentials securely;
- Azure Monitor and Application Insights for telemetry and uptime assurance;
- regionally redundant storage and failover plans to ensure availability.
8. The system of claim 1, wherein the utility token BIOKRIPT is:
- required for participating in sniper bot features;
- used as collateral for governance voting weight;
- utilized for transaction fee discounts or access privileges on the platform;
- subject to a deflationary model wherein a portion of distributed revenue is periodically burned.
9. The system of claim 5, wherein the anti-rug module includes both:
- on-chain enforcement via smart contract state changes;
- off-chain anomaly detection pipelines that incorporate AI-generated liquidity volatility scores;
- and integration with blocklist registries maintained on-chain for community reference.
10. The system of claim 6, wherein the staking and revenue-sharing smart contracts:
- are upgradable using a transparent proxy pattern;
- support multi-chain execution through standardized bridge contracts;
- log all reward calculations to the blockchain for auditability;
- enforce minimum staking duration and cooldown intervals to reduce abuse.
11. The system of claim 1, wherein the compliance subsystem comprises:
- automatic IP geofencing to restrict access based on jurisdiction;
- built-in support for third-party identity verification services;
- ability to issue zero-knowledge proofs of compliance for regulated access;
- configurable modes for optional KYC depending on token project classification.
8. Abstract Reference Numbers and Figures
The following figures illustrate the components and operational flow of the decentralized hybrid exchange system:
Figure 1: Architecture Diagram of Biokript DEX Ecosystem: Illustrates user wallets, sniper bot module, revenue module, smart contracts, Azure-hosted infrastructure, and liquidity pools. Demonstrates the interconnectivity between the cloud infrastructure and on-chain components.
Figure 2: Flowchart of AI Sniper Bot Operation: Outlines the logical flow: mempool listener → token scoring engine → trade constructor → slippage validator → signed transaction execution. Each step is annotated with reference numerals to corresponding submodules.
Figure 3: Anti-Rug Logic and Liquidity Threshold Alert System: Shows how liquidity monitoring leads to anomaly detection and transaction lock. Includes triggers for user alerts and contract-based freeze protocols.
Figure 4: Token Revenue-Sharing Distribution Mechanism: Depicts wallet staking module, time-based snapshot mechanism, profit aggregator, escrow smart contract, and user claim UI. Each element is linked via directional flow arrows and assigned numerical references.
Figure 5: Azure Node Deployment and API Routing Diagram: Details the backend infrastructure, including AKS container clusters, load balancers, failover strategies, API Gateway, monitoring components, and Azure Key Vault. Node references are numbered and routed according to deployment topology.
Figure 6: Biokript’s Key Security Framework: Details air-gapped storage, client-side encryption, zero centralized access, and secure multi-signature recovery, ensuring full user control and protection of private keys at all times.
Each figure includes numeric markers that correspond to elements described in the Detailed Description of the Invention, allowing cross-referencing between visual diagrams and textual sections for enhanced understanding and clarity.
