Privacy Smart Contract Security Audit - Inco Network
Budget: $3,000 – $5,000 USD
We have privacy-preserving smart contracts built on Inco Network (FHE-enabled blockchain) and need a thorough independent review before mainnet deployment. The main priorities are uncovering security vulnerabilities specific to encrypted state handling and verifying correct implementation of confidential computing patterns; gas optimization is secondary.
Here is what we need from you:
• Manual and automated analysis of Solidity source code using tools such as Slither, Foundry test suites, or similar — adapted for privacy-focused contract logic.
• Testing of edge cases related to encrypted variables, access control for confidential data, and proper handling of FHE operations.
• Verification that sensitive data remains encrypted throughout contract execution and cannot be leaked through transaction metadata or events.
• A concise PDF/Markdown report detailing every issue by severity, exact code locations, and practical remediation guidance.
• A summary document confirming the contract meets Inco Network's privacy standards and best practices.
All code and findings must remain strictly confidential. We're looking for someone who can work efficiently while maintaining thoroughness. Please share your relevant experience with privacy tech, ZK, or FHE-related projects if applicable.
Here is what we need from you:
• Manual and automated analysis of Solidity source code using tools such as Slither, Foundry test suites, or similar — adapted for privacy-focused contract logic.
• Testing of edge cases related to encrypted variables, access control for confidential data, and proper handling of FHE operations.
• Verification that sensitive data remains encrypted throughout contract execution and cannot be leaked through transaction metadata or events.
• A concise PDF/Markdown report detailing every issue by severity, exact code locations, and practical remediation guidance.
• A summary document confirming the contract meets Inco Network's privacy standards and best practices.
All code and findings must remain strictly confidential. We're looking for someone who can work efficiently while maintaining thoroughness. Please share your relevant experience with privacy tech, ZK, or FHE-related projects if applicable.