Analyzing Ethereum Smart Contract VulnerabilitiesSAFE
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·
Overview
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·
6c59587be632OBSERVED · 2026-10-07Install
Commands as the repository documents them. They are shown, not run.
pip install slither-analyzer
pip install mythril
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- 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 mitre_attack: - T1190 - T1059 --- # 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 ### 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.
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
6c59587be632full audit observations/trust-audit/skill/mukul975__analyzing-ethereum-smart-contract-vulnerabilities.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-07 | 6c59587be632 | SAFE | B | 89 | first audit |
Questions
What does the Analyzing Ethereum Smart Contract Vulnerabilities skill do?
817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·
Is Analyzing Ethereum Smart Contract Vulnerabilities safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Analyzing Ethereum Smart Contract Vulnerabilities access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (6c59587be632), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.