Master Role Misconfig with AI: Web3 Yield Aggregator Case Study

Master Role Misconfig with AI: Web3 Yield Aggregator Case Study

This AI agent skill enables developers to apply a comprehensive methodology for identifying role misconfigurations in yield aggregator protocols. Utilizing a targeted case study approach, it demonstrates the application of access control bug detection within a specific Web3 environment.

What this skill does

The skill guides users through a structured process of uncovering potential role misconfiguration issues in a yield aggregator protocol. Specifically, it:

• Provides a detailed walkthrough of a real-world example focusing on role misconfiguration within a yield aggregator.
• Demonstrates how to apply a 10-class bug methodology to identify critical access control vulnerabilities.
• Assists in analyzing prior audit findings to discover overlooked issues in newly launched programs.
• Includes insights on evaluating risk acceptance and bounty potential, highlighting critical vulnerabilities with high payout ranges.

Who it is for

This skill is designed for developers and security teams utilizing AI coding agents such as Claude Code, Cursor, and Codex. It is particularly advantageous for professionals involved in Web3 security assessments and yield aggregator protocol development.

Use cases

• Security researchers applying methodical bug-hunting strategies to new Web3 projects.
• Development teams seeking to enhance their protocols’ security by preemptively identifying access control issues.
• Organizations looking to train their teams on practical security testing methodologies using real-life case studies.

Technical details

• Leverages a comprehensive case study of yield aggregator protocols focusing on role misconfiguration.
• Applicable in Web3 environments with core contracts like Vault.sol and RewardsDistributor.sol.
• Analyzes scenarios within a structured fund flow architecture involving stablecoin deposits and rewards distributions.

For authorised security testing, defensive research, and educational use only. This skill does not guarantee the identification of all vulnerabilities; however, it provides a structured method to identify critical access issues.

Source & Licence

This package is built on open-source work published by Olaradiallysymmetrical491 (Olaradiallysymmetrical491/web3-bug-bounty-hunting-ai-skills) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.