By name: analyzing-ethereum-smart-contract-vulnerabilities description: Perform static and symbolic analysis of Solidity smart contracts using Slither and Mythril to detect reentrancy, integer overflow, access control, and other vulnerability classes before deployment to Ethereum mainnet. domain: cybersecurity subdomain: blockchain-security tags:
- ethereum
- solidity
- smart-contract
- slither
- mythril
- blockchain
- defi
- audit version: '1.0' author: mahipal license: Apache-2.0 nist_csf:
- PR.DS-01
- PR.DS-02
- ID.RA-01
Analyzing Ethereum Smart Contract Vulnerabilities
Overview
Smart contract vulnerabilities have led to billions of dollars in losses across DeFi protocols. Unlike traditional software, deployed smart contracts are immutable and handle real financial assets, making pre-deployment security analysis critical. Slither performs fast static analysis using an intermediate representation to detect over 90 vulnerability patterns in seconds, while Mythril uses symbolic execution and SMT solving to discover complex execution path vulnerabilities like reentrancy and integer overflows. This skill covers running both tools against Solidity contracts, interpreting results, triaging findings by severity, and generating audit reports.
When to Use
- When investigating security incidents that require analyzing ethereum smart contract vulnerabilities
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Python 3.10+ with pip
- Slither (pip install slither-analyzer) and solc compiler
- Mythril (pip install mythril) with solc-select for compiler version management
- Solidity source code or compiled contract bytecode
- Foundry or Hardhat development framework (optional, for project-level analysis)
Steps
- Scope the task — define objectives, boundaries, and success criteria
- Gather information — collect all necessary data and context before proceeding
- Execute the core workflow — follow the domain-specific steps methodically
- Validate results — verify outputs against expected outcomes or baselines
- Document findings — record results, anomalies, and recommendations
Step 1: Run Slither Static Analysis
Execute Slither against the contract codebase to identify vulnerability patterns, optimization opportunities, and code quality issues using its 90+ built-in detectors.
Step 2: Run Mythril Symbolic Execution
Run Mythril deep analysis to explore execution paths and discover reentrancy, unchecked external calls, and arithmetic vulnerabilities that require path-sensitive analysis.
Step 3: Triage and Correlate Findings
Combine results from both tools, deduplicate findings, assess severity based on exploitability and financial impact, and filter false positives.
Step 4: Generate Audit Report
Produce a structured audit report with vulnerability descriptions, affected code locations, exploit scenarios, and remediation recommendations.
Expected Output
JSON report listing vulnerabilities with SWC (Smart Contract Weakness Classification) identifiers, severity ratings, affected functions, and suggested fixes.
When NOT to Use
- You need to perform the attack, not analyze it (use performing-* skills)
- Task is about detection, not analysis (use detecting-* skills)
- You need to implement controls (use implementing-* skills)
- Task is about threat hunting, not post-incident analysis (use hunting-* skills)
- You don't have access to the artifacts/logs to analyze
- Task requires real-time monitoring (use SOC tools)
Red Flags
- Performing actions without explicit written authorization from the asset owner
- Testing against production systems without a defined scope and rules of engagement
- Sharing sensitive findings or credentials in unencrypted communications
- Failing to properly scope and contain the assessment before starting
Verification
- All steps executed successfully against a test environment before production use
- Output documented with screenshots or logs demonstrating expected behavior
- Results validated against known-good baselines or reference implementations
- Documentation complete enough for another analyst to reproduce findings