Prepared by:
HALBORN
Last Updated 05/15/2025
Date of Engagement: April 22nd, 2025 - May 1st, 2025
100% of all REPORTED Findings have been addressed
All findings
4
Critical
0
High
0
Medium
0
Low
0
Informational
4
LucidLabs engaged our security analysis team to conduct a comprehensive security assessment of their smart contract ecosystem. The primary aim was to meticulously assess the security architecture of the smart contracts to pinpoint vulnerabilities, evaluate existing security protocols, and offer actionable insights to bolster security and operational efficacy of their smart contract framework. Our assessment was strictly confined to the smart contracts provided, ensuring a focused and exhaustive analysis of their security features.
Our engagement with LucidLabs spanned a 1-week period, during which we dedicated one full-time security engineer equipped with extensive experience in blockchain security, advanced penetration testing capabilities, and profound knowledge of various blockchain protocols. The objectives of this assessment were to:
- Verify the correct functionality of smart contract operations.
- Identify potential security vulnerabilities within the smart contracts.
- Provide recommendations to enhance the security and efficiency of the smart contracts.
Our testing strategy employed a blend of manual and automated techniques to ensure a thorough evaluation. While manual testing was pivotal for uncovering logical and implementation flaws, automated testing offered broad code coverage and rapid identification of common vulnerabilities. The testing process included:
- A detailed examination of the smart contracts' architecture and intended functionality.
- Comprehensive manual code reviews and walkthroughs.
- Functional and connectivity analysis utilizing tools like Solgraph.
- Customized script-based manual testing and testnet deployment using Foundry.
This executive summary encapsulates the pivotal findings and recommendations from our security assessment of LucidLabs smart contract ecosystem. By addressing the identified issues and implementing the recommended fixes, LucidLabs can significantly boost the security, reliability, and trustworthiness of its smart contract platform.
| EXPLOITABILITY METRIC () | METRIC VALUE | NUMERICAL VALUE |
|---|---|---|
| Attack Origin (AO) | Arbitrary (AO:A) Specific (AO:S) | 1 0.2 |
| Attack Cost (AC) | Low (AC:L) Medium (AC:M) High (AC:H) | 1 0.67 0.33 |
| Attack Complexity (AX) | Low (AX:L) Medium (AX:M) High (AX:H) | 1 0.67 0.33 |
| IMPACT METRIC () | METRIC VALUE | NUMERICAL VALUE |
|---|---|---|
| Confidentiality (C) | None (C:N) Low (C:L) Medium (C:M) High (C:H) Critical (C:C) | 0 0.25 0.5 0.75 1 |
| Integrity (I) | None (I:N) Low (I:L) Medium (I:M) High (I:H) Critical (I:C) | 0 0.25 0.5 0.75 1 |
| Availability (A) | None (A:N) Low (A:L) Medium (A:M) High (A:H) Critical (A:C) | 0 0.25 0.5 0.75 1 |
| Deposit (D) | None (D:N) Low (D:L) Medium (D:M) High (D:H) Critical (D:C) | 0 0.25 0.5 0.75 1 |
| Yield (Y) | None (Y:N) Low (Y:L) Medium (Y:M) High (Y:H) Critical (Y:C) | 0 0.25 0.5 0.75 1 |
| SEVERITY COEFFICIENT () | COEFFICIENT VALUE | NUMERICAL VALUE |
|---|---|---|
| Reversibility () | None (R:N) Partial (R:P) Full (R:F) | 1 0.5 0.25 |
| Scope () | Changed (S:C) Unchanged (S:U) | 1.25 1 |
| Severity | Score Value Range |
|---|---|
| Critical | 9 - 10 |
| High | 7 - 8.9 |
| Medium | 4.5 - 6.9 |
| Low | 2 - 4.4 |
| Informational | 0 - 1.9 |
Critical
0
High
0
Medium
0
Low
0
Informational
4
| Security analysis | Risk level | Remediation Date |
|---|---|---|
| Vesting schedule duration not validated | Informational | Solved - 05/08/2025 |
| Inaccurate vesting schedule total amount tracking | Informational | Not Applicable |
| Assumed fixed-point precision in price oracle | Informational | Solved |
| Redundant logic in tier amount calculation | Informational | Not Applicable - 05/05/2025 |
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Halborn strongly recommends conducting a follow-up assessment of the project either within six months or immediately following any material changes to the codebase, whichever comes first. This approach is crucial for maintaining the project’s integrity and addressing potential vulnerabilities introduced by code modifications.
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