Beyond Static Analysis: Building Adaptive Security Intelligence for Polkadot Ecosystem
Beyond Static Analysis: Building Adaptive Security Intelligence for Polkadot Ecosystem
Date: June 26, 2025
Proponent: Dr. Mohammadreza Ashouri
Requested Amount: 9,900 DOT (equivalent to ~$32,670 at $3.3/DOT)
Project Category: Security Infrastructure
Timeline: 7 weeks
The Growing Threat: Why Blockchain Security Needs Intelligence?
The blockchain space is constantly under attack. In 2024 alone, cryptocurrency investors lost over $12.4 billion to scams and exploits, with 117,000+ fraudulent tokens created—a 41% increase from the previous year. These aren't simple copy-paste scams anymore. Modern attackers use sophisticated techniques: hidden smart contract functions, social engineering campaigns, fake development teams, and complex cross-chain manipulations that traditional security tools simply cannot detect.
The problem goes far beyond analyzing lines of code. A perfectly written smart contract can still be a scam if the team behind it plans to disappear with funds. Social signals, team behavior patterns, tokenomics design, and community manipulation tactics often reveal malicious intent before any code vulnerability does. This is why rule-based security scanners that only examine code miss the majority of real-world threats—they're fighting yesterday's battles with yesterday's tools.
amIrug.xyz presents an AI-based adoptive protecting solution. Instead of relying on static rules written once and never updated, our platform learns continuously from each new scam, building intelligence that adapts to evolving threat landscapes. We've been creating a system that any crypto user—from casual investors to experienced developers—can use with a simple web interface. No configuration, no technical expertise required. Just paste a contract address and get instant, intelligent risk assessment that considers not just code patterns, but team reputation, social signals, and behavioral anomalies.
Our success speaks volumes: 12,547+ contracts analyzed so far, $5.7M+ in potential losses prevented, 2,891+ scams identified with 98.5% accuracy. We're not just protecting individual investors—we're building cleaner, more trustworthy ecosystem that legitimates projects can thrive in.
Why Polkadot Needs This Now ?
The Security Gap in Polkadot's Ecosystem
While other major blockchains have evolved their security infrastructure, Polkadot faces a critical gap. The ecosystem currently relies on a handful of developer-focused tools that miss the bigger picture:
- No intelligent threat detection for ink! contracts and runtime vulnerabilities
- No cross-chain security analysis for XCMP/HRMP interactions
- No social signal analysis for team and project legitimacy assessment
- No accessible tools for non-technical users to assess project risks
- No real-time monitoring for governance attacks and treasury manipulation
This gap becomes more dangerous as Polkadot's DeFi ecosystem grows and attracts both legitimate projects and malicious actors.
Existing Tools vs. Modern Threats
Current Polkadot security tools serve specific niches but leave massive blind spots:
What's Missing: Intelligent, adaptive security that combines code analysis with behavioral patterns, social signals, and cross-chain risk assessment—accessible to everyone in the ecosystem.
amIrug.xyz: Intelligent Security for Polkadot
How We're Different?
Learning Intelligence: Our AI models don't just follow pre-written rules. They learn from every new scam pattern, team behavior, and attack vector, becoming smarter over time. When scammers evolve their tactics, our platform evolves faster.
Beyond Code Analysis: While others focus solely on smart contract code, we analyze the complete threat space—team reputation, social media signals, token distribution patterns, governance proposal behaviors, and cross-chain interactions.
Universal Accessibility: Anyone can use our platform. Paste a contract address, get instant results. No CLI commands, no IDE setup, no technical configuration. Security intelligence should be accessible to everyone, not just developers.
Real-Time Protection: We monitor contracts and governance activities continuously, detecting threats as they emerge rather than waiting for post-mortem analysis.
What We Will Build for Polkadot?
Phase 1: Core Polkadot Security Engine (Weeks 1-3)
Budget: 4,500 DOT (~$14,850)
- ink! v5+ Contract Analysis: Specialized scanning for reentrancy, storage collisions, weight abuse, and access control vulnerabilities within pallet-contracts environment
- Runtime Security Monitoring: Detection of malicious patterns in pallet-treasury, pallet-staking, and pallet-democracy configurations
- SS58 Identity Integration: Native address validation and cross-chain identity verification
- HRMP Message Analysis: Security assessment of cross-parachain communications
Phase 2: Advanced Threat Intelligence (Weeks 4-5)
Budget: 3,300 DOT (~$10,890)
- OpenGov Security Intelligence: AI-powered analysis of referendum proposals for hidden risks and manipulation attempts
- Cross-Chain Risk Assessment: Detection of dangerous XCM configurations and bridge vulnerabilities
- Social Signal Processing: Team reputation analysis using on-chain behavior patterns and governance participation
- Governance Attack Detection: Real-time monitoring for treasury manipulation and voting anomalies
Phase 3: Integration & Community Access (Weeks 6-7)
Budget: 2,100 DOT (~$6,930)
- Web Interface Deployment: Simple, accessible scanning platform requiring no technical expertise
- Polkadot.js API Integration: Seamless connectivity for wallet-based security checks
- Basic Developer API: RESTful endpoints for parachain teams to integrate security scanning
- Educational Resources: Security guides specifically for Polkadot's unique architecture
Total Budget: 9,900 DOT (~$32,670)
Competitive Advantage: Intelligence vs. Rules
amIrug.xyz vs. Existing Polkadot Tools
Capability | amIrug.xyz | Scout | ink! Analyzer | Phishing Lists |
---|---|---|---|---|
AI-Powered Detection | ✅ Learns from new threats | ❌ Static rules only | ❌ Static checks | ❌ Manual curation |
Social Signal Analysis | ✅ Team & community assessment | ❌ Code-only focus | ❌ Code-only focus | ❌ Limited scope |
Cross-Chain Security | ✅ XCMP/HRMP analysis | ❌ Single-chain focus | ❌ Single-chain focus | ❌ Address-level only |
Real-Time Monitoring | ✅ Continuous threat detection | ❌ Development-time only | ❌ Development-time only | ❌ Reactive updates |
User Accessibility | ✅ Web interface for everyone | ❌ CLI/developer-only | ❌ IDE/developer-only | ❌ Background protection |
Governance Security | ✅ OpenGov threat analysis | ❌ Limited scope | ❌ Not applicable | ❌ Not applicable |
Runtime Analysis | ✅ Planned pallet security | ✅ Strong capability | ❌ Not applicable | ❌ Not applicable |
Key Differentiator: amIrug.xyz provides the intelligence layer that existing tools lack—combining code analysis with behavioral patterns, social signals, and cross-ecosystem threat intelligence.
Team Background
Dr. Mohammadreza Ashouri (PhD) - Lead Developer & Security Researcher
-
Ph.D. in Software Security from University of Potsdam, Germany (2020)
-
Proven Blockchain Security Expertise: Creator of amIrug.xyz
-
Polkadot Ecosystem Experience:
- Active researcher with Polkadot Academy on Rust development and blockchain security
- Speaker on Polkadot security topics (Asia sub0 2024 Bangkok): "Blockchain Security, Rust, and Polkadot" technical presentation: https://www.youtube.com/watch?v=8w9s2Qnj9hI
- Deep understanding of Substrate framework and parachain architecture
- 2024 Polkadot Blockchain Academy Grant recipient for AI-based blockchain innovations
-
Industry Experience:
- SAP (2021-2023): Security audits for enterprise Java applications and JVM components
- Oracle Labs (2019): Advanced research internship on dynamic taint tracking for JVM security
-
Technical Speaking & Research:
- JavaZone 2024 (Oslo): "Enhancing Java Security with Rust" - https://2024.javazone.no/program/99bf5d46-d634-4c41-8ec2-4646ab8c84e2
- Web3 Amsterdam 2024: Intent-based blockchain architecture presentation - https://web3amsterdam.com/speakers/
- Multiple security conferences including DeepSec, Hacktivity, and ACSAC
- Published researcher with 20+ peer-reviewed papers
Arjun - AI Engineer & Machine Learning Specialist
- AI/ML Expertise: 5+ years developing machine learning models for security applications
- Blockchain AI Integration: Specialized in neural networks for transaction pattern analysis and anomaly detection
- Technical Skills: TensorFlow, PyTorch, advanced pattern recognition algorithms, and real-time data processing
- amIrug.xyz Contribution: Lead developer of the AI risk scoring algorithms achieving 92% accuracy in rugpull prediction
Zer0_Cipher - Security Engineer & Fullstack Developer
- Security Background: Active member of Germany's hacking conference circuit with deep knowledge of vulnerability research
- Academic Credentials: Master's in Software Engineering from University of Potsdam (2024)
- Technical Expertise: Advanced penetration testing, exploit development, and security architecture design
- amIrug.xyz Role: Architect of the security scanning engine and vulnerability detection algorithms
Current Platform Achievement:
- 12,547+ contracts scanned with 98.5% detection accuracy
- $5.7M+ in funds protected from potential scams
- 2,891+ scams and rugpulls identified across chains
- Straightforward, user-friendly interface requiring no technical expertise
Technical Approach
Intelligent Security Architecture
Machine Learning Core: Our platform extends existing AI models (trained on 8,000+ token datasets with 92% rugpull prediction accuracy) to Polkadot's unique architecture. Unlike static rule-based tools, our system learns from new attack patterns and adapts continuously.
Multi-Layer Analysis:
- Code Layer: ink! contract vulnerability detection (reentrancy, storage issues, weight abuse)
- Runtime Layer: Pallet security analysis for governance, treasury, and staking functions
- Social Layer: Team reputation assessment using on-chain behavior and governance participation
- Cross-Chain Layer: HRMP/XCMP security validation and bridge risk assessment
Real-Time Intelligence: Continuous monitoring using Substrate RPC endpoints and event streams provides immediate threat detection upon contract deployment or governance proposal submission.
Analysis Coverage:
- ink! Contracts: Reentrancy, storage collision, access control gaps, arithmetic overflows
- Runtime Pallets: Governance attacks, treasury manipulation, staking vulnerabilities
- Cross-Chain Security: HRMP message analysis with XCMP forward compatibility
- Social Signals: Team legitimacy assessment, community manipulation detection
- Governance Security: OpenGov proposal analysis for hidden risks and attack vectors
Future Expansion (Beyond This Grant)
While this proposal focuses on core security functionality, our roadmap includes:
- Developer Tools: CLI interface and IDE extensions for seamless development integration
- Advanced APIs: Enterprise-grade endpoints for exchange and wallet integration
- Open Source Components: Community-driven security libraries and educational resources
- Cross-Ecosystem Intelligence: Enhanced threat sharing across blockchain ecosystems
Expected Impact
Immediate Benefits (Months 1-3)
- Developer Protection: 500+ Substrate developers gain access to intelligent security analysis
- User Safety: Non-technical users can assess project risks before investing
- Ecosystem Reputation: Polkadot positions itself as the most security-conscious blockchain ecosystem
Long-term Vision (Months 3-12)
- Security Leadership: Polkadot becomes the benchmark for proactive blockchain security
- Community Growth: 1,000+ developers and users trained on security best practices
- Threat Prevention: Significant reduction in successful scams and exploits
Why This Investment Matters?
Market Timing: Security consciousness is at an all-time high after recent industry losses exceeding $2B in Q1 2025 alone. Polkadot can lead by example.
Competitive Position: While other ecosystems rely on reactive security measures, Polkadot can offer proactive, intelligent threat detection.
Ecosystem Growth: Security infrastructure enables institutional adoption and enterprise confidence—critical for Polkadot's next growth phase.
Community Protection: Every prevented scam strengthens trust in the entire ecosystem, attracting more legitimate projects and users.
Conclusion
The blockchain industry stands at a crossroads. We can continue accepting massive losses to increasingly sophisticated scams, or we can build intelligent defenses that evolve with the threat landscape.
amIrug.xyz shows proven technology that has already protected millions in value across other ecosystems. With this funding, Polkadot can join the ranks of security-first blockchains while gaining a competitive advantage that attracts both developers and users seeking a safer environment.
We're not asking for research funding—we're asking for integration funding to bring working, battle-tested security intelligence to Polkadot. The platform exists, the AI models work, and the community needs protection.
Note that the question isn't whether Polkadot needs better security tools—it's whether Polkadot wants to lead the industry in intelligent threat prevention in the blockchain space.
References
Platform & Technical Documentation
- amIrug.xyz Platform: https://amirug.xyz
- GitHub Repository: https://github.com/mohammadreza-ashouri/amIrug
- Personal Website: https://ashouri.online
- Technical Blog: https://ashourics.medium.com/
- YouTube Channel: https://www.youtube.com/c/Heapzip/videos
- X: https://x.com/ashouri777
Polkadot Ecosystem References
- ink! Alliance Progress Update: https://forum.polkadot.network/t/ink-alliance-six-month-progress-update
- PolkaVM Technical Documentation: https://docs.polkadot.com/polkavm/
- Substrate Security Guidelines: https://github.com/substrate-developer-hub/security-guidelines
- OpenGov Documentation: https://wiki.polkadot.network/docs/learn-polkadot-opengov
- HRMP & XCMP Technical Specifications: https://wiki.polkadot.network/docs/learn-xcm
Security Research & Vulnerability Analysis
- CoinFabrik Substrate Security Research: https://coinfabrik.com/blog/
- QuillAudits Polkadot Security Reports: https://quillaudits.com/
- Web3 Foundation Security Guidelines: https://github.com/w3f/General-Grants-Program/blob/master/grants/security_guidelines.md
- Scout Security Tool: https://github.com/CoinFabrik/scout
- ink! Smart Contract Security Best Practices: https://use.ink/security
Comments (2)

Decision Deposit
Voting has Started
2
of 3Decision Period
0 / 28 days
Confirmation Period
0 / 2 days
Summary
0%
Aye
0%
Nay
Aye (2)0.0 DOT
Support0.0 DOT
Nay (7)0.0 DOT
Comments (2)
Hi Mo,
Thank you for your proposal and for contributing your expertise to the Polkadot ecosystem. The concept of a proactive, AI-driven blockchain security tool is compelling, and the need for improved threat detection is clear.
That being said, I believe there are several points that require clarification before this proposal can be properly evaluated by the community.
Some of the claims regarding platform usage and impact such as number of contracts scanned and funds protected are difficult to verify from the referenced public materials. It would be very helpful if you could provide some additional evidence to support their validity (e.g., usage dashboards, case studies, or endorsements from projects that have used the platform).
The 92% rugpull prediction accuracy is impressive but needs transparency:
-Is there a whitepaper or benchmark comparison available that explains the dataset, methodology, model performance, and limitations?
-Has any third-party auditor or security researcher validated the detection model?
The GitHub repository linked appears to contain mainly research or demo code, with limited recent activity and community engagement. For a platform that claims to protect millions in value, it would be reassuring to see a more active, mature codebase with clear documentation and ongoing maintenance.
The identities and credentials of team members beyond yourself are unclear. Given the nature of the work and the focus on security, it is reasonable to ask for some form of verification, such as public profiles or references to past projects.
Finally, references to Polkadot ecosystem involvement would be stronger with more specific information. If your work has been used by teams or acknowledged by the Polkadot Blockchain Academy or Web3 Foundation, please consider including direct feedback or endorsements.
This proposal may indeed offer value to the ecosystem but I think more transparency and detail are needed.
Cheers,
TS
onchain identity not available
Hi Mo,
Thank you for your proposal and for contributing your expertise to the Polkadot ecosystem. The concept of a proactive, AI-driven blockchain security tool is compelling, and the need for improved threat detection is clear.
That being said, I believe there are several points that require clarification before this proposal can be properly evaluated by the community.
Some of the claims regarding platform usage and impact such as number of contracts scanned and funds protected are difficult to verify from the referenced public materials. It would be very helpful if you could provide some additional evidence to support their validity (e.g., usage dashboards, case studies, or endorsements from projects that have used the platform).
The 92% rugpull prediction accuracy is impressive but needs transparency:
-Is there a whitepaper or benchmark comparison available that explains the dataset, methodology, model performance, and limitations?
-Has any third-party auditor or security researcher validated the detection model?
The GitHub repository linked appears to contain mainly research or demo code, with limited recent activity and community engagement. For a platform that claims to protect millions in value, it would be reassuring to see a more active, mature codebase with clear documentation and ongoing maintenance.
The identities and credentials of team members beyond yourself are unclear. Given the nature of the work and the focus on security, it is reasonable to ask for some form of verification, such as public profiles or references to past projects.
Finally, references to Polkadot ecosystem involvement would be stronger with more specific information. If your work has been used by teams or acknowledged by the Polkadot Blockchain Academy or Web3 Foundation, please consider including direct feedback or endorsements.
This proposal may indeed offer value to the ecosystem but I think more transparency and detail are needed.
Cheers,
TS
onchain identity not available