How to Create a Multi-Chain Audit SaaS Like Halborn

As blockchain ecosystems keep expanding in 2025, with platforms like EVM, Solana, Cosmos, and Move-based chains leading the way, the conversation around security has never been more urgent. With the rapid growth of multi-chain applications in DeFi, GameFi, and enterprise blockchain, new vulnerabilities are cropping up all the time. On top of that, regulations are tightening, demanding real-time compliance and risk management. 

That’s why more and more companies are looking for multi-chain audit solutions to ensure their systems stay secure and compliant.

As the demand for multi-chain solutions skyrockets, we’ve seen how critical it is to provide real-time, automated security audits across various blockchains. With extensive experience in developing blockchain security systems, IdeaUsher has worked with numerous businesses to create scalable audit solutions that monitor cross-chain vulnerabilities and provide ongoing compliance management. That’s why we’ve put this blog together, to guide you on how to build a robust, real-time auditing system like Halborn, and how you can turn that into a successful SaaS business model.

Key Market Takeaways for Multi-Chain Audit SaaS

According to Technavio, the global auditing services market is set to grow by USD 113.4 billion between 2023 and 2028, driven by the increasing need for secure, scalable solutions that can manage the complexity of blockchain and digital assets. This growth emphasizes the demand for audit platforms that can handle the intricacies of blockchain networks, ensuring compliance and security across a wide range of industries.

Source: Technavio

As decentralized applications and cross-chain protocols continue to thrive, Multi-Chain Audit SaaS solutions are becoming essential for businesses in the Web3 space. These platforms provide the necessary tools to audit smart contracts and decentralized applications across multiple blockchains, offering businesses the security they need while maintaining trust and compliance. With the rise in blockchain vulnerabilities, these solutions are in high demand to protect against risks like DeFi exploits and smart contract failures.

Companies like CertiK, ChainSecurity, and KPMG are leading the way in multi-chain auditing. CertiK’s AI-driven verification process has helped audit thousands of projects, while ChainSecurity’s collaboration with PwC Switzerland boosts its institutional offerings. 

Meanwhile, KPMG’s Chain Fusion® bridges audit technology with blockchain services, offering tailored solutions for clients ranging from startups to major financial institutions, showcasing the growing importance of multi-chain audits in the Web3 ecosystem.

Understanding Multi-Chain Audit SaaS

As decentralized applications grow more complex and span across multiple blockchain ecosystems, EVM, Solana, Cosmos, Move, and others, the need for real-time, continuous security becomes critical. A multi-chain audit SaaS platform offers a cloud-based solution that delivers ongoing smart contract audits across these diverse networks.

Key Capabilities

This model integrates three essential layers of security:

• Automated Analysis: Runs static and dynamic scanning tools to detect common vulnerabilities and coding flaws.
• Red Team Testing: Security experts conduct manual penetration testing, and their findings are codified into detection rules to enhance automated scans.
• AI-Driven Anomaly Detection: Machine learning models monitor transaction behavior to flag potential exploits or abnormal patterns in real time.

How Halborn Approaches Multi-Chain Audit SaaS?

Halborn’s solution blends automation with human expertise, offering a scalable and effective platform for blockchain security:

• Automated Vulnerability Detection: Tools like Slither and MythX scan codebases to identify known risks early in development.
• Red Team Feedback Loops: Manual test results aren’t just documented, they’re transformed into reusable rules that strengthen automated detection.
• Predictive Threat Intelligence: AI models learn from past attack vectors to identify and mitigate emerging threats before they’re exploited.
• Unified Dashboard: One interface to monitor vulnerabilities across multiple chains, ideal for teams managing complex, multi-chain deployments.

Why Businesses Are Investing in Multi-Chain Audit SaaS?

Businesses are investing in multi-chain audit SaaS because security isn’t a one-time job, it’s a moving target. With smart contracts constantly evolving, they need real-time protection that keeps up. Plus, a single tool that works across chains just makes life easier.

1. Recurring Revenue & Scalability

Multi-Chain Audit SaaS unlocks predictable revenue for providers through tiered, subscription-based models. Premium features like zero-day exploit alerts add real value, making it easier to upsell while scaling across enterprise clients.

2. Solving Real, Ongoing Problems

DApp teams benefit from continuous audits without the hassle of rebooking experts for every update. Enterprises meet compliance demands without slowing innovation, and Layer 1/2 chains gain ecosystem trust through built-in, reliable security infrastructure.

3. Continuous Value Over One-Time Audits

This model shifts security from a one-off checkbox to a constant safeguard. It tracks vulnerabilities from discovery to fix and plugs directly into CI/CD pipelines to prevent risky deployments before they go live.

4. Rising Demand for Multi-Chain Coverage

With more projects operating across multiple blockchains, the need for unified security tools is growing fast. A single platform that covers EVM, Solana, Cosmos, and others simplifies security without sacrificing depth.

How Halborn’s Multi-Chain Audit SaaS Works?

Halborn’s multi-chain audit SaaS blends expert-led security testing with real-time automation, so you’re not just scanning, you’re staying ahead. It pulls data from chains like Ethereum, Solana, and Cosmos, normalizes it, and flags threats before they hit. Plus, it gives you fixes right in your dev tools, no extra friction.

1. Blending Human Expertise with Automation

Halborn isn’t just running scans, it embeds offensive security into a cloud-native, continuously evolving SaaS platform. The team operates like a hybrid between a Red Team and a software company.

How it works:

• Human-first discovery: Security engineers dig into contracts, infrastructure, and protocol logic—looking for novel, high-impact vulnerabilities (not just OWASP-level issues).
• Codifying knowledge: When the Red Team finds a new exploit vector—say, a governance manipulation in a DeFi protocol—it doesn’t just get logged. It’s turned into reusable rules that every client benefits from.
• Automated rule deployment: These rules are converted into signatures (e.g., YARA or static analysis templates) and rolled out to detect similar threats across all environments instantly.

This approach keeps the knowledge fresh, actionable, and scalable.

2. Multi-Chain Data Ingestion & Normalization

Security across multiple chains only works if you can make sense of fragmented, noisy data. Halborn tackles this by building a custom ingestion and normalization engine for every major blockchain family.

Data ingestion examples:

Why normalization matters:

Every chain emits data differently, Solana logs don’t look like EVM events, and Move bytecode requires deeper decoding. Halborn’s engine maps all of this into a standardized JSON format, allowing its detection engine to see threats that span across chains.

For example, if an attacker takes advantage of a price mismatch between Ethereum and a Cosmos-based liquidity pool, Halborn spots it by analyzing swap activity across both chains. Thanks to normalized multi-chain data, it can catch inconsistencies in real time that single-chain tools would miss entirely.

3. Red Team Intelligence → Automated Detection Rules

Security isn’t static. Halborn’s detection logic evolves with every discovery, feeding Red Team learnings directly into the platform.

Discovery Phase

Halborn’s engineers go beyond basic vulnerability scans by using fuzzing, symbolic execution, and chain-specific attack simulations. They examine the full attack surface, including governance mechanics, economic design, oracle behavior, and even validator dynamics, uncovering risks that typical audits often miss.

Rule Creation

Once a vulnerability is discovered, it’s converted into automated detection logic. Structural issues like missing access controls become static analysis rules, while unusual runtime behavior, like abnormal token minting, is tracked by AI models trained to recognize these anomalies in real time.

Continuous Deployment

After testing, detection rules are versioned and deployed to all client environments automatically. The platform also logs when and where each rule triggers, giving security teams a clear timeline of exposures and helping them respond with precision and speed.

For example, if a Cosmos-based protocol has a governance bug that allows voting with locked tokens, Halborn’s SaaS doesn’t just detect it—it acts. It flags similar logic in other chains, sends targeted alerts with fix recommendations, and activates real-time monitoring to prevent abuse before it spreads.

4. Specialized Cross-Chain Security Coverage

Halborn is built to handle the unique vulnerabilities that come from bridges, messaging layers (IBC, CCIP), and multi-chain apps.

What’s monitored:

• Bridges: Signature verification, oracle logic, and liquidity accounting.
• IBC/CCIP: Relayer trust models, message timeouts, and replay protections.

Detection logic includes:

• Origin verification: “Did this IBC message really come from the expected contract?”
• Liquidity consistency checks: “Is the token balance on Chain A consistent with what Chain B received?”
• Replay protection: “Is someone reusing valid bridge messages to double-spend?”

Custom tooling:

• WASM modules tailored for Move-based runtime environments.
• Deep EVM bytecode analyzers that track call stacks across transactions.

5. Predictive Threat Detection Using AI/ML

AI in Halborn’s system goes beyond just automating tasks, it actively identifies subtle, real-time threats that manual testing or static rules often miss. By learning the typical behavior of protocols, it can spot anomalies early, preventing potential exploits before they escalate.

Model design:

• Baseline modeling: Every protocol has its own behavioral fingerprint. AI models learn typical DEX volumes, governance vote patterns, and mint/burn ratios.
• Anomaly detection: If a sudden spike (e.g., 80% of total tokens withdrawn) occurs, the model flags it immediately.
• Risk scoring: Past exploit data trains models to score how “suspicious” each event is. Random forest classifiers and ensemble learners reduce noise.

Human-in-the-loop system: Low-confidence alerts are filtered out. Only high-likelihood, high-impact threats are passed to human analysts for review—ensuring teams aren’t spammed with false positives

6. Automated Remediation & Developer Workflow Integration

Security without fixes isn’t enough. Halborn closes the loop by feeding results directly into development tools.

Re-audit automation: After a fix is applied, the SaaS re-runs a targeted scan to confirm that the vulnerability is fully patched before shipping to production.

Benefits of Building a Multi-Chain Audit SaaS for Businesses

Building a multi-chain audit SaaS gives businesses steady, recurring revenue through subscription models, making cash flow more predictable. It also boosts customer retention with ongoing advisory services and proactive security. Plus, with regulatory compliance and transparency, it builds trust and sets you apart in a competitive market.

Technical Advantages

1. Real-Time Detection & Prevention

Unlike traditional audits, a Multi-Chain Audit SaaS provides continuous, proactive security by monitoring smart contracts and transactions in real time. AI-driven anomaly detection flags suspicious activity, such as flash loan attacks or bridge exploits, and automated alerts keep developers informed, helping prevent attacks before they escalate.

2. Seamless Integration with Developer Workflows

A well-integrated SaaS platform works directly with existing developer tools and CI/CD pipelines. This makes security a seamless part of the development process, with automated scans on pull requests, API-based vulnerability checks, and compatibility with DevOps tools like Jenkins and CircleCI.

3. Reduced Vulnerability Exposure Window

With a SaaS model, security vulnerabilities are detected and remediated instantly, reducing the risk exposure time compared to manual audits. Automated checks catch common issues (e.g., reentrancy, overflow bugs), and real-time remediation guidance ensures fast fixes before deployment.

Business Advantages

1. Predictable Recurring Revenue

A subscription-based model ensures steady and predictable revenue, unlike the one-time nature of traditional audits. With tiered pricing and options like pay-per-scan or monthly billing, businesses can create consistent cash flow, while upsell opportunities, like premium threat intelligence reports, add additional value.

2. Customer Retention via Advisory Models

Incorporating human-led consulting services into the SaaS offering helps to retain clients long-term. Security advisory services, penetration testing as a service (PTaaS), and regular compliance audits provide ongoing value and ensure customer trust and loyalty.

3. Competitive Differentiation 

Transparency and regulatory alignment set a platform apart in competitive markets. Offering BVSS dashboards for compliance, public audit logs, and regulatory adherence (e.g., SEC, MiCA, GDPR) help clients stay audit-ready, while building trust with users through verifiable security practices.

How to Build a Multi-Chain Audit SaaS Like Halborn?

Building a multi-chain audit SaaS platform is a strategic, step-by-step process designed to provide top-tier security for blockchain applications. Our focus is on creating an automated, scalable solution to monitor and detect vulnerabilities across multiple blockchain ecosystems. Here’s how we approach building this platform for our clients:

1. Defining the Security Surface

We begin by working with you to define the specific security surface you want to protect. Whether it’s DeFi protocols, gaming applications, DAOs, or general smart contracts, we tailor the platform to your needs, ensuring the security solution matches the unique challenges of your ecosystem.

2. Building Multi-Chain Indexers

Next, we set up or integrate multi-chain indexers that pull in data from the chains you’re focusing on. We use tools like The Graph, SubQuery, or custom-built indexers to create seamless data pipelines, giving you access to real-time, accurate blockchain data needed to detect threats.

3. Architecting the Detection Engine

We design the heart of the platform: a powerful detection engine that combines static code analysis, dynamic testing (fuzzing), and behavioral models. This approach ensures we catch everything, from simple code flaws to more complex vulnerabilities driven by transaction behavior across chains.

4. Integrating Red Team Intelligence

We integrate expert-led Red Team intelligence directly into your platform. By building a comprehensive threat intelligence database and an offensive security rules engine, we convert findings from manual penetration tests into automated detection rules that evolve with emerging threats.

5. Automating Remediation & Workflow

Security should never slow down development. We automate remediation by integrating secure IDE plugins, automated fix suggestions, and CI/CD hooks into your workflow. This way, your development teams can fix vulnerabilities in real time without disruption.

6. Designing Risk Scoring & Reporting

Finally, we create a risk scoring system, like BVSS, that provides clear, actionable insights into the health of your platform. With intuitive business-friendly dashboards, we ensure both your technical and non-technical teams can understand and act on the security insights, making compliance and risk management seamless.

Challenges to Create a Multi-Chain Audit SaaS like Halborn

After working with numerous clients, we’ve identified the common challenges in building a multi-chain audit SaaS. With our experience, we’ve developed effective solutions to address issues like blockchain diversity, scalability, and seamless integration, ensuring smooth and secure operations.

1. Handling Blockchain Heterogeneity

Different blockchains (EVM, Solana, Cosmos, Move-based) each have their own architectures, data formats, and security risks. This makes it tough to standardize and analyze data across chains. With such diversity, even basic tasks like logging and transaction tracking can vary drastically, creating potential integration headaches.

The Solution:

• Schema Translators: We normalize raw data from different chains into a unified format (e.g., Ethereum-style logs) to simplify analysis. This standardization makes it easier to compare and act on data from various blockchains.
• Modular Adapters: By building chain-specific adapters, we ensure each blockchain integrates smoothly with the core engine, maintaining efficiency and flexibility.
• Universal Abstraction Layer: Using tools like Chainlink CCIP or Axelar GMP, we standardize cross-chain interactions, making it easier to work with different ecosystems without compromising security.

2. Ensuring Scalability with High Transaction Volume

Handling high transaction volumes from multiple chains in real-time without lag, especially during traffic spikes like NFT drops or token launches, all while managing compute costs. As blockchain ecosystems grow, scaling these systems to handle larger transaction loads without slowing down is a constant concern.

The Solution:

• Stream Processing: We leverage technologies like Apache Flink and Spark Streaming to analyze data in real time without delay, ensuring that processing doesn’t bottleneck during peak activity.
• Message Queues: Kafka or RabbitMQ are used to decouple data ingestion from processing, allowing for more reliable and scalable data flow management.
• Edge Caching: Tools like Redis help store frequent queries, improving response times for repeated actions like contract calls and minimizing redundant processing.
• Auto-Scaling: With Kubernetes and AWS Lambda, we automatically scale resources to handle bursts efficiently, keeping costs under control while maintaining performance.

3. Minimizing False Positives in Threat Detection

Too many false positives overwhelm teams, while missing actual threats due to overly broad filters can leave you exposed. Balancing between too many alerts and undetected risks is a delicate task, and inaccurate filtering can lead to both wasted time and missed attacks.

The Solution:

• Unsupervised ML Models: We use models like Isolation Forest and Autoencoders to establish baselines for “normal” behavior, making threat detection more accurate by identifying outliers and anomalies.
• Hybrid Validation: Anomalies are flagged first and then sent for manual review, ensuring precision without overwhelming developers, leading to faster issue resolution.
• Feedback Loops: Users can mark false positives, which helps retrain models and improve future detection accuracy, creating a more adaptive security environment over time.

Tools & Frameworks for Building a Multi-Chain Audit SaaS

Building a powerful multi-chain audit platform requires selecting the right tools and technologies. Here’s a breakdown of the essential components needed at each stage of development to ensure your SaaS solution is secure, efficient, and scalable.

1. Data Indexing & Chain Integration

The foundation of any blockchain audit platform is the ability to gather and organize data from multiple networks. Aggregating data across various blockchains with different consensus mechanisms, transaction structures, and security models is a challenge that requires specialized tools.

Core Tools

• The Graph: Indexes and queries blockchain data through GraphQL, providing easy access to on-chain information.
• SubQuery: An alternative indexing protocol supporting multi-chain aggregation for decentralized data.
• Chainlink: A decentralized oracle network used for secure cross-chain data verification.

Chain-Specific Infrastructure

For blockchain integration, Alchemy and QuickNode provide reliable access to EVM chains, while Helius RPC and Triton ensure low-latency access to Solana. Cosmos SDK and Tendermint RPC are used for efficient Cosmos chain integration, and full node integrations with custom indexers support Aptos and Sui Move chains.

Cross-Chain Solutions

LayerZero enables cross-chain message verification and interoperability, while Axelar and Wormhole provide secure bridges for seamless value transfer across chains. Chainlink CCIP further enhances cross-chain communication by offering a reliable protocol for safe and efficient interoperability.

2. Audit Automation & Security Analysis

Smart contract auditing is essential to prevent exploits and vulnerabilities. Automating this process ensures that no contract is overlooked, providing more security in less time.

3. Machine Learning & Data Processing

As threats become more sophisticated, leveraging machine learning for predictive threat detection is becoming an essential part of a multi-chain Audit SaaS. Here’s how we use machine learning to stay ahead of potential attacks.

Data Pipeline Infrastructure

Apache Kafka is used for real-time event streaming, ensuring reliable data processing and event handling, while Apache Flink serves as a powerful stream processing engine to analyze blockchain data in real time. Redis acts as a low-latency caching layer, storing frequently accessed data to improve system performance and reduce response times.

ML Frameworks

PyTorch and TensorFlow help build machine learning models to detect anomalies and predict threats, while Hugging Face Transformers enable natural language processing for smart contract audit summaries. Feast ensures consistency across these models, improving overall performance and accuracy in threat detection.

Behavioral Analysis

Network Graphs track fund flows to identify unusual patterns or anomalies, while Time-Series Forecasting detects abnormal trends over time, helping to spot potential security threats. Ensemble Models combine multiple detection models to minimize false positives and improve the accuracy of threat detection.

4. CI/CD Integration & Developer Tools

For seamless adoption of the audit platform, developers need the tools to integrate security checks directly into their workflows.

Workflow Integration

• GitHub Actions/GitLab CI: Automates scan triggers and integrates security checks directly into the development pipeline.
• VS Code Plugins: In-IDE vulnerability alerts to ensure real-time feedback for developers working on contracts.
• Truffle/Hardhat Plugins: Tools for seamless integration with popular Ethereum development environments, making audits part of the workflow.

Collaboration Tools

• Jira API: Automates ticket creation for discovered vulnerabilities, helping teams stay on top of remediation tasks.
• Slack Webhooks: Real-time alerts sent directly to your team for immediate action on vulnerabilities.
• Linear/ClickUp: Task tracking tools that help manage vulnerability remediation and progress.

5. Dashboards & Risk Scoring

To provide actionable insights and ensure compliance, having a solid risk scoring system and visualization tools is essential.

Risk Scoring Engines

• BVSS (Blockchain Vulnerability Scoring System): A scoring system designed specifically for blockchain vulnerabilities.
• CVSS Adaptation: A version of the Common Vulnerability Scoring System adapted for smart contracts.
• Custom Scoring Models: Tailored risk scores that account for specific factors in different blockchain ecosystems.

Visualization Tools

• Grafana: Real-time monitoring dashboards to track the health of your platform and vulnerabilities.
• Apache Superset: A business intelligence layer to provide deeper insights into data across chains.
• Custom React Dashboards: White-labeled solutions that allow you to customize dashboards for your platform’s needs.

Reporting Features

• Automated PDF Reports: Easily generate compliance reports for auditors and regulators.
• Executive Summaries: Simplified, non-technical overviews of platform security for stakeholders.
• Remediation Playbooks: Step-by-step guides to help teams fix identified vulnerabilities effectively.

Use Case Example: A Cross-Chain DeFi Platform

A fast-growing DeFi startup came to us with a pressing requirement: build a cross-chain liquidity bridge connecting Ethereum, Solana, and Aptos to enable seamless asset swaps across networks. Here’s how we helped them tackle their security challenges.

The Challenge

The project faced several critical issues:

• Smart contract risks: The complex bridge logic was vulnerable to potential exploits.
• No continuous monitoring: One-time audits left gaps between deployments, leaving the platform exposed.
• Cross-chain threats: Bridge relayers, message verification, and liquidity pool risks were a major concern.
• Developer friction: Security checks were slowing down CI/CD pipelines, delaying deployments.

The Solution: A Halborn-Style Multi-Chain Audit SaaS

To address these challenges, IdeaUsher designed and deployed a custom security SaaS platform with the following key features:

Smart Contract Audit Automation

Slither and Move Prover were integrated into GitHub Actions for automated vulnerability checks, while Foundry and Echidna tested edge cases in bridge contracts. A Red Team validation layer was added to manually review critical functions and complex logic for extra security.

Real-Time Threat Monitoring

Cross-Chain Data Feeds

The Graph and Alchemy RPC were integrated for real-time data on Ethereum, while Helius provided low-latency transaction streaming for Solana. For Aptos, a custom indexer was developed to monitor Move-based events, ensuring comprehensive cross-chain monitoring.

Anomaly Detection

The ML model flagged abnormal withdrawal patterns, while threshold-based alerts were triggered for sudden changes in Total Value Locked, ensuring real-time detection and proactive monitoring of potential security risks.

Remediation Workflow

• Auto-Generated Tickets: Vulnerabilities detected during audits were automatically routed to Jira and Slack for quick resolution.
• CI/CD Blocking: Unsafe deployments were automatically rejected in GitLab pipelines, preventing risky code from going live.
• Fix Suggestions: AI-powered code patches provided developers with automated solutions to common security flaws.

The Results: $5M Exploit Prevented

During staging tests, the platform detected a critical relayer flaw that could have allowed fake cross-chain messages. The issue was patched before the mainnet launch, preventing a potential $5M+ exploit risk to the Total Value Locked.

By integrating automation, real-time monitoring, and proactive security features, the platform avoided a major security breach, enhancing trust and stability within the ecosystem.

Conclusion

Building a multi-chain audit SaaS like Halborn presents a significant opportunity to address the growing demand for secure, cross-chain solutions in the blockchain space. By integrating AI for smart contract analysis, leveraging cross-chain logic, and focusing on developer-friendly workflows, such platforms can streamline auditing processes and enhance security for decentralized ecosystems. At Idea Usher, we specialize in helping enterprise teams design, build, and deploy scalable, tailored audit platforms that meet the specific needs of their projects, ensuring long-term reliability and trust.

Looking to Develop a Multi-Chain Audit SaaS Like Halborn?

At IdeaUsher, we specialize in helping you build a robust, scalable, and AI-powered audit SaaS that proactively detects vulnerabilities and secures your blockchain platforms. Here’s how we can help:

• Automate Vulnerability Detection – Seamlessly scan across EVM, Solana, Move, and more, with powerful AI tools.
• Integrate Real-Time Monitoring – Keep vulnerabilities in check by integrating automated monitoring into your CI/CD pipelines.
• Combine AI + Human Expertise – Leverage both AI-powered scans and Red Team tactics to detect and mitigate potential threats.

Why Choose Us?

• 500,000+ Hours of Coding Expertise – Our team is made up of ex-FAANG/MAANG engineers who’ve built and scaled cutting-edge security tools.
• Proven Blockchain Experience – We’ve delivered secure solutions for everything from DeFi bridges to enterprise-grade SaaS applications.
• Full-Stack Delivery – From smart contracts to ML models and intuitive dashboards, we take care of it all.

Don’t wait for the next cross-chain exploit to put your clients at risk. Let us help you build the secure, scalable audit platform you need to stay ahead.

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