Complete guide book for Cybersecurity and Digital Forensic Analysis on Ethereum-Based Blockchain

Ethereum Virtual Machine (EVM)-based blockchains, like Ethereum, Binance Smart Chain, and Polygon, are foundational to decentralized applications. Conducting cybersecurity and forensic analysis on these blockchains requires specialized techniques and tools to uncover malicious activities, ensure compliance, and provide evidence for legal proceedings.

Tracing transaction trails on the Ethereum blockchain for cybersecurity and forensic purposes involves a structured approach. Below is a step-by-step guide detailing the tools and techniques used:

Key Areas of Forensic Analysis on EVM-Based Blockchains

Transaction Trails

• Tracking the flow of funds across wallets.

• Identifying patterns of suspicious activity (e.g., money laundering or ransomware payments).

Smart Contract Audits

• Examining vulnerabilities in smart contracts used for fraud or exploitation.

Anomalous Behavior Detection

• Identifying unusually high transaction volumes, token movements, or contract interactions

DeFi Protocol Analysis

• Investigating exploits involving decentralized finance (DeFi) platforms like flash loan attacks.

Cross-Chain Activity

• Tracing transactions that involve bridging tokens across different EVM-compatible blockchains.

Step-by-Step Guide for Forensic Analysis

• Blockchain transactions are public, recorded on the blockchain, and accessible via block explorers or APIs.

• Transactions include sender/receiver addresses, gas fees, smart contract interactions, and timestamps.

Key Components to Monitor

• Wallet addresses

• Smart contract activities

• Token transfers (ERC-20, ERC-721, etc.)

• Anomalies in transaction behavior (e.g., unusual volumes, frequent activity)

Step 1: Data Collection

Identify the Blockchain

• Determine the target EVM-compatible blockchain network under investigation (e.g., Ethereum, BNB Chain, Polygon).

• Understand the network specifics, such as consensus mechanism, gas structure, and token standards.

Access Blockchain Data

• Use blockchain explorers to view and retrieve transaction-level data:Etherscan for Ethereum.BscScan for Binance Smart Chain.Polygonscan for Polygon.

Query blockchain nodes directly via APIs

• Infura: Offers scalable Ethereum and IPFS API access.

• Alchemy: Provides advanced features such as enhanced analytics and faster queries.

Extract Smart Contract Logs

• Analyze logs to identify relevant interactions:Track function calls (e.g., transfers, approvals).Decode event logs emitted by contracts to uncover patterns of activity.

Tools for smart contract log analysisz

• Tenderly: Simulate and debug smart contract transactions in-depth.

• Dune Analytics: Create custom queries to visualize on-chain data trends.

• Advanced: Utilize developer tools (e.g., Hardhat, Ganache) to simulate transactions for additional insights.

Step 2: Transaction Analysis

Trace Transaction Flows

• Follow the Money:Identify the origin and destination of funds within the blockchain network. Map transaction pathways to reveal how assets are moved and distributed.

• Token-Specific Movements:Trace activities involving ERC-20 tokens (e.g., Tether, USDC) and ERC-721 tokens (NFTs).

• Analyze token transfer events to uncover hidden links between addresses or suspicious transfers.

Tools for tracing

• Etherscan Token Tracker: For transaction-level token details.

• Chainalysis Reactor: For visualizing fund flows and connections.

Cluster Analysis

• Identify Linked Entities:Group addresses that exhibit similar transaction patterns, suggesting control by a single entity.Consider shared wallet usage, repeated fund transfers, or interaction with common smart contracts.

• Behavioral Indicators:Monitor clusters interacting with flagged wallets (e.g., those linked to ransomware or illicit marketplaces).

Recommended Tools:

• Chainalysis and Elliptic: Offer clustering algorithms to identify linked addresses.

• GraphSense: Provides entity resolution and clustering for on-chain activity.

Analyze Gas Usage

• Unusual Gas Patterns:High gas fees may indicate priority transactions (e.g., during arbitrage or liquidation events).Extremely low or highly fluctuating fees can hint at obfuscation tactics or experimental activity.

• Gas Spikes and Malicious Actions:Investigate spikes in gas usage for potential manipulation of block space or contract vulnerabilities.

Tools for gas analysis

• Tenderly : Simulate and profile gas usage across transactions.

• ETH Gas Station: Monitor real-time gas trends.

Step 3: Smart Contract Security Assessment

The focus is on identifying vulnerabilities and ensuring the safety of smart contracts.

Review Source Code

• Decompiling Smart Contracts: Tools like Solidity Viewer and EthFiddle can be helpful to analyze the compiled bytecode or smart contract source code. You can identify potential issues by inspecting the contract’s logic and structure, comparing it against best practices.

Common Vulnerabilities to Watch For

• Reentrancy Attacks: Look for external function calls (like transfer()) before state changes, which can lead to reentrancy bugs, as seen in the DAO hack.

• Integer Overflows/Underflows: Check for unprotected mathematical operations (like addition, subtraction, multiplication, etc.). Use Solidity’s SafeMath library or similar libraries to mitigate this risk.

• Access Control Issues: Ensure that critical functions are protected with proper modifiers such as onlyOwner or require(msg.sender == owner) to prevent unauthorized access.

Audit Tools

• MythX : This platform performs a thorough security analysis of smart contracts by identifying potential vulnerabilities such as reentrancy attacks, integer overflows, and other issues. It also checks for issues like gas limits and optimization.

• slither.io : A static analysis tool that inspects Solidity code to uncover common vulnerabilities. It runs a set of predefined checks, covering known issues like reentrancy, uninitialized storage, and more.

• Securify : Another security analysis tool that focuses on verifying security properties and known issues in the code. Securify also checks for best practices related to access control and gas optimization.

Function Call Tracing

• Flash Loan Attacks: Analyze if the contract allows for borrowing funds without collateral (like in DeFi platforms). These loans can be used to manipulate prices or governance votes. Monitor external function calls and potential exploits.

• Rug Pulls: Investigate if the smart contract has the potential for the developers to withdraw all liquidity or funds, leaving users with nothing. Look for functions that allow owners or specific addresses to drain funds unexpectedly.

• Trace Function Calls: Use tools like Tenderly or Remix IDE to trace function calls in real-time. This allows you to analyze how functions interact with each other and detect suspicious behavior.

By combining manual code review with automated audits and tracing, you can ensure a thorough assessment of smart contract security.

Step 4: Data Visualization

The goal is to visually represent the relationships and behaviors within the blockchain network, which can help uncover suspicious activities, detect fraud, or gain insights into transaction patterns.

Graph Relationships

• Mapping Wallet Interactions:Tools like GraphSense and Neo4j can be used to create a graph network of wallets and their interactions. These tools allow you to visualize how different wallets are connected by transactions, which helps in identifying patterns and potential fraud.

• @GraphSense is particularly useful for on-chain analysis, providing a powerful framework to track and map cryptocurrency transactions, wallet interactions, and other blockchain data.

• Neo4j , a graph database, can be leveraged to visualize complex relationships in blockchain data. By importing transaction data into Neo4j, you can visualize wallet connections and create a clear map of transaction flows. The network graph can help highlight clusters of activity, such as potential Ponzi schemes, pyramid structures, or other malicious behaviors.

Key Use Cases for Mapping Wallet Interactions

• Identifying central hubs where transactions originate, which could indicate market makers or influential accounts.

• Detecting wallet clusters that interact frequently with each other, potentially revealing laundering or fraud rings.

• Tracking cross-chain transactions, especially if you're dealing with multi-chain environments.

Behavioral Insights Analysis

• Highlighting Outliers:Analyzing wallet behavior is crucial for detecting malicious or abnormal activity.

• Outliers are wallets or addresses that behave differently from the norm—such as making unusually large or rapid transactions or interacting with blacklisted addresses.Use visualization tools to highlight these outliers, often flagged for interacting with known malicious entities, like:Dark web addresses (associated with illegal activity).

• Scam or phishing addresses (often reported by blockchain security firms).

• Rug pulls or exit scams (addresses involved in suspicious liquidity withdrawal actions).

Techniques for Behavioral Insights

• Anomaly detection: Use graph algorithms or machine learning models to automatically detect anomalous behavior, such as wallets that frequently move large amounts of funds in a short time span.

• Integration with Threat Intelligence: Cross-reference wallet interactions with threat intelligence feeds (like the Bitcoin Abuse Database or CryptoScamDB) to identify malicious actors and mark them in your graph for further investigation.

Examples of Outliers to Visualize

• Wallets interacting with high-risk addresses: Highlight wallets that have had transactions with wallets flagged for illicit activities, like those involved in ransomware, hacking, or money laundering.

• Multiple small transactions: A pattern of small transactions might indicate smurfing (splitting large transactions into small ones to avoid detection).

• Sudden changes in transaction behavior: A wallet that previously only made small, infrequent transactions but suddenly starts transferring large sums or interacting with multiple wallets in a short timeframe might indicate compromised activity or a rug pull.

Tools and Techniques for Visualization

• GraphSense: Use for mapping and tracking wallet interactions with blockchain analysis.

• Neo4j: Import blockchain transaction data for dynamic visualizations, create nodes for wallets, and edges for transactions.

• Gephi or Cytoscape: These are open-source platforms for visualizing large-scale networks, including blockchain data, to represent wallet interactions, trace behavior, and highlight outliers.

Step 5: Identify Anomalies

During the analysis phase of blockchain forensics, identifying anomalies is crucial to uncovering patterns indicative of malicious or illegal activity. This step often focuses on detecting red flags and using specialized tools to assess blockchain data effectively.

Red Flags to Watch For

• Frequent Small Transactions: These can indicate dusting attacks, where small amounts of cryptocurrency are sent to multiple wallets to compromise user privacy or assess potential targets.

• Interaction with Flagged Wallets: Wallets associated with darknet marketplaces, ransomware operations, or other illicit activities often serve as key points of interest in forensic investigations.

Tools for Detection

• TRM Labs: A leading blockchain intelligence platform that identifies high-risk wallets, monitors suspicious activities, and provides actionable insights into blockchain ecosystems.

• Crystal Blockchain: This tool offers risk scoring for cryptocurrency addresses, helping investigators evaluate the likelihood of an address being linked to illicit activities.

By leveraging these tools, investigators can pinpoint anomalies within vast amounts of blockchain data, enabling them to trace the flow of funds, identify participants, and build a comprehensive case.

Step 6: Cross-Chain Investigation

As blockchain ecosystems grow increasingly interconnected, forensic investigations must account for cross-chain activity. Criminals often use bridging mechanisms and wrapped tokens to obscure transactions or transfer assets across multiple blockchains.

Key Focus Areas

Track Bridged Assets

• Bridged assets involve tokens or cryptocurrencies moved between blockchains, often leveraging bridges between EVM-compatible networks (e.g., Ethereum, Binance Smart Chain, or Polygon).

• Investigators must trace these movements to understand how illicit funds flow across chains.

Tool Spotlight: Chainalysis Cross-Chain Investigation simplifies tracking these transactions by identifying connections and mapping activities across multiple chains.

Analyze Wrapped Tokens

• Wrapped tokens, such as Wrapped Ethereum (WETH), represent assets pegged to the value of another cryptocurrency but exist on a different blockchain.

• These tokens are frequently used in schemes to obfuscate transactions or in decentralized finance (DeFi) exploits.

• Analyzing their use in suspicious activities, including token swaps and liquidity pool interactions, can reveal patterns of misuse.

By incorporating cross-chain analysis, investigators can uncover schemes that exploit the interoperability of blockchain networks, closing critical gaps in forensic efforts.

Step 7: Documentation and Reporting

The focus is on creating comprehensive and actionable reports based on the findings from your security assessments, which can serve both internal purposes (like remediation) and external needs (such as legal or compliance actions).

1. Capture Evidence

Document Transaction Hashes, Smart Contract Details, and Logs:

Each transaction hash (TxID) should be logged for traceability. These are unique identifiers for blockchain transactions, which you can use to track specific events in the blockchain ledger. Smart contract details are crucial for tracing the exact behavior of contracts during an exploit or attack. You’ll want to include the contract address, any specific function calls made, and relevant contract parameters that are part of the issue.

Logs provide a detailed history of operations within the smart contract or blockchain system. Tools like Remix IDE or Tenderly can be useful to capture logs that provide real-time insights into function execution and errors.

Best Practices for Capturing Evidence

• Transaction hashes: Include in your reports the full trace of any malicious or suspicious transactions.

• Smart contract addresses: If the issue stems from a smart contract vulnerability, capture the full contract address, including the relevant function calls that led to the exploit.

• Logs & Events: Record any events emitted by the contract (e.g., Transfer events in ERC20 tokens or custom events), which can be useful for tracking the sequence of actions taken by the attacker.

Tools to Help Capture Evidence:

• Belkasoft Evidence Center: This tool is excellent for digital forensics and capturing evidence related to blockchain activity. It can extract detailed logs, transaction hashes, and other blockchain-specific data to be used in forensic analysis.

• Blockchair or Etherscan: Use these tools to search and document transaction hashes, and retrieve details about transactions and smart contracts for easy reporting.

2. Prepare Case Reports

• Graphical Visualizations:Visualizations are vital for illustrating the complexity of an attack or issue. Use Neo4j or GraphSense to create network maps of wallet interactions and transaction flows. These visuals can clearly show how funds were moved, where they originated from, and the interactions between different entities.

• Timeline Diagrams: Create visual timelines that map out key events, such as when a transaction occurred, when a contract function was triggered, and when suspicious activities or anomalies were detected.

• Flagged Activities: Highlight the most critical activities flagged during your assessment, such as wallet interactions with known malicious addresses, unusual behavior patterns, or detected exploits.

Tools for Case Reporting:

• Belkasoft Evidence Center: For forensic reporting and to ensure that all captured evidence (transaction hashes, logs, and details) is well-organized for further analysis.

• MS Word or Google Docs: These can be used for structuring detailed case reports, especially when supplemented with embedded visuals like graphs or screenshots.

• Power BI or Tableau: These platforms are ideal for creating detailed, interactive dashboards or timelines, where you can dynamically present transaction data, wallet interactions, and security findings.

By creating a detailed, organized, and visually comprehensive report, you ensure that all critical evidence is captured and communicated effectively, which aids in both internal analysis and any external legal or compliance processes.

Cybersecurity Tools for EVM-Based Blockchain Forensics

Blockchain Explorers

• Etherscan, BscScan, Polygonscan (for real-time data).

Transaction Monitoring Tools

• Chainalysis, Elliptic, TRM Labs, Crystal Blockchain.

Smart Contract Analysis

• MythX, Slither, Securify, Tenderly.

Visualization Platforms

• Maltego, GraphSense, Neo4j.

Cross-Chain Analysis

• Chainalysis Reactor, Merkle Science.

Threat Intelligence

• CipherTrace, CertiK (focused on blockchain security).

How to Leverage These Tools for EVM-Based Blockchain Forensics

• Tracking Malicious Actors: Use Transaction Monitoring Tools (e.g., Chainalysis, Elliptic) and Threat Intelligence (CipherTrace, CertiK) to track wallets that engage in suspicious behavior and flag high-risk addresses.

• Smart Contract Security Audits: Before deploying smart contracts, run them through MythX, Slither, or Securify for security analysis to ensure vulnerabilities like reentrancy or gas inefficiencies are caught early.

• Cross-Chain Transaction Monitoring: When assets are moved between blockchains, utilize Chainalysis Reactor and Merkle Science to monitor and trace cross-chain activities.

• Visualization: Use Neo4j or GraphSense to create a visual representation of wallet interactions and transaction flows. This helps in identifying patterns or clusters of malicious activity.

Real-Time Data Monitoring

• Leverage Blockchain Explorers (Etherscan, Polygonscan) for real-time tracking and Visualization Platforms like Maltego to investigate relationships between entities.

Challenges in EVM-Based Forensics

Challenges in EVM-Based Blockchain Forensics are a significant concern when it comes to identifying illicit activities, securing assets, and ensuring compliance. Let’s explore the challenges you mentioned:

1. Pseudonymity

Challenge

• Ethereum addresses are pseudonymous, meaning that transactions are tied to an address (or wallet), but these addresses don't directly correlate to a specific individual or entity in the real world. This can create hurdles when attempting to link transactions to a person or group, especially when attackers take steps to hide their identity.

Mitigation Strategies

• Transaction Analytics: Tools like Chainalysis or Elliptic can track patterns in transactions and attempt to link pseudonymous addresses to known entities based on behavioral analysis or clustering.

• KYC/AML Compliance: Crypto exchanges and platforms that comply with Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations can provide valuable metadata about user identities, which can be cross-referenced with pseudonymous addresses.

• Cross-Referencing with Off-Chain Data: Investigators may combine on-chain data with off-chain data (like social media, public records, and exchange account details) to unmask identities.

2. Obfuscation Techniques

Challenge

• Attackers often use various techniques, like mixers (e.g., Tornado Cash), to obfuscate the origin and destination of funds. These tools break the transaction chain, making it difficult to trace the flow of assets, especially in the context of money laundering or fraud.

Mitigation Strategies:

• Advanced Analysis Tools: Platforms like Chainalysis Reactor, CipherTrace, and Elliptic offer features to trace funds through mixers and identify potential risks, even when transactions are obfuscated.

• Monitoring Cross-Chain Activity: Cross-chain forensics tools like Merkle Science help trace funds that move across different blockchains, even when mixers are involved.

• Tornado Cash Blacklisting: Some mixers like Tornado Cash have been blacklisted by regulators or integrated into some forensics platforms. Identifying funds that interact with sanctioned or blacklisted addresses can provide actionable insights.

3. High Volume of Data

Challenge:

Ethereum and other blockchain networks handle a massive amount of transaction data. With the increase in decentralized finance (DeFi) platforms, NFTs, and smart contract interactions, the amount of on-chain data grows exponentially. Analyzing this data manually is infeasible, and it becomes essential to use robust tools to process and interpret the data.

Mitigation Strategies:

• Big Data Tools: Use blockchain forensics platforms like Chainalysis, Elliptic, and Crystal Blockchain that are specifically designed to handle large datasets. These tools can efficiently parse through transaction histories, identify patterns, and flag suspicious activities.

• Machine Learning: Some forensics platforms use machine learning to detect anomalies and patterns in the data, helping to identify potentially malicious transactions amidst high volumes of data.

• Data Aggregation: Platforms like Neo4j or GraphSense offer ways to aggregate and visualize data, making it easier to detect relationships and visualize trends even within large datasets.

4. Regulatory Uncertainty

Challenge:

Different jurisdictions have varying laws and regulations surrounding blockchain forensics, crypto transactions, and data privacy. The lack of a unified global regulatory framework makes it difficult to conduct cross-border investigations and enforce consistent legal standards.

Mitigation Strategies:

• Compliance Tools: Utilize compliance tools such as CipherTrace and TRM Labs, which help businesses adhere to local regulations by offering real-time monitoring and identifying transactions that violate regulations.

• Multi-Jurisdictional Cooperation: Building strong cooperation between international law enforcement agencies and regulators can help standardize the approach to blockchain forensics. Platforms like Chainalysis Reactor support multi-jurisdictional investigations by providing insights that align with various regional compliance standards.

• Public Awareness and Advocacy: Engaging with regulatory bodies to establish clearer legal frameworks around blockchain forensics can help shape the future of investigations. Public-facing reports and best practices may help encourage legal harmonization.

Conclusion

Forensic analysis on EVM-based blockchains is a critical aspect of cybersecurity in the crypto world. By leveraging the right tools, techniques, and a structured approach, investigators can uncover illicit activities, secure the ecosystem, and support regulatory compliance. As blockchain technology evolves, so must the methods used to ensure its integrity.