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Lucid Contracts - LucidLabs

Prepared by:

Halborn Logo

HALBORN

Last Updated 11/25/2025

Date of Engagement: November 4th, 2025 - November 5th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

4

Critical

0

High

0

Medium

0

Low

3

Informational

1

Table of Contents

1. INTRODUCTION

LucidLabs engaged Halborn to conduct a security assessment on their smart contracts beginning on November 4th, 2025 and ending on November 6th, 2025. The security assessment was scoped to smart contracts in the GitHub repository provided to the Halborn team. Commit hashes and further details can be found in the Scope section of this report.

2. ASSESSMENT SUMMARY

The team at Halborn assigned a full-time security engineer to assess the security of the smart contracts. The security engineer is a blockchain and smart-contract security expert with advanced penetration testing, smart-contract hacking, and deep knowledge of multiple blockchain protocols.

The purpose of this assessment is to:

    • Ensure that smart contract functions operate as intended.

    • Identify potential security issues with the smart contracts.

 

In summary, Halborn identified some improvements to reduce the likelihood and impact of risks, which were addressed by the LucidLabs team. The main recommendations were the following:

    • Reset the existing token spending authorization to zero before assigning a new value, or adopt an incremental authorization pattern, so that future deposit operations remain functional even if the downstream component does not consume the entire approved amount.

    • Capture the interest bearing balance immediately before and after supplying liquidity to the external pool and base the internal principal update on the actual balance increase, or abort the operation when the increase is smaller than expected, so that the accounting layer never reflects more principal than what was effectively deployed.

    • Abort the operation whenever the external pool returns fewer tokens than requested, or decrease the internal principal tracker by the originally requested amount instead of the returned amount, so the recorded withdrawable balance cannot drift above what is actually recoverable.


3. TEST APPROACH AND METHODOLOGY

Halborn performed a combination of manual review of the code and automated security testing to balance efficiency, timeliness, practicality, and accuracy in regard to the scope of the smart contract assessment. While manual testing is recommended to uncover flaws in logic, process, and implementation; automated testing techniques help enhance coverage of smart contracts and can quickly identify items that do not follow security best practices. The following phases and associated tools were used throughout the term of the assessment:

    • Research into the architecture, purpose, and use of the platform.

    • Smart contract manual code review and walkthrough to identify any logic issue.

    • Thorough assessment of safety and usage of critical Solidity variables and functions in scope that could lead to arithmetic related vulnerabilities.

    • Manual testing by custom scripts.

    • Graphing out functionality and contract logic/connectivity/functions (solgraph).

    • Static Analysis of security for scoped contract, and imported functions. (Slither).

    • Local or public testnet deployment (Foundry, Remix IDE).


4. RISK METHODOLOGY

Every vulnerability and issue observed by Halborn is ranked based on two sets of Metrics and a Severity Coefficient. This system is inspired by the industry standard Common Vulnerability Scoring System.
The two Metric sets are: Exploitability and Impact. Exploitability captures the ease and technical means by which vulnerabilities can be exploited and Impact describes the consequences of a successful exploit.
The Severity Coefficients is designed to further refine the accuracy of the ranking with two factors: Reversibility and Scope. These capture the impact of the vulnerability on the environment as well as the number of users and smart contracts affected.
The final score is a value between 0-10 rounded up to 1 decimal place and 10 corresponding to the highest security risk. This provides an objective and accurate rating of the severity of security vulnerabilities in smart contracts.
The system is designed to assist in identifying and prioritizing vulnerabilities based on their level of risk to address the most critical issues in a timely manner.

4.1 EXPLOITABILITY

Attack Origin (AO):
Captures whether the attack requires compromising a specific account.
Attack Cost (AC):
Captures the cost of exploiting the vulnerability incurred by the attacker relative to sending a single transaction on the relevant blockchain. Includes but is not limited to financial and computational cost.
Attack Complexity (AX):
Describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability. Includes but is not limited to macro situation, available third-party liquidity and regulatory challenges.
Metrics:
EXPLOITABILITY METRIC (mem_e)METRIC VALUENUMERICAL 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
Exploitability EE is calculated using the following formula:

E=∏meE = \prod m_e

4.2 IMPACT

Confidentiality (C):
Measures the impact to the confidentiality of the information resources managed by the contract due to a successfully exploited vulnerability. Confidentiality refers to limiting access to authorized users only.
Integrity (I):
Measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of data stored and/or processed on-chain. Integrity impact directly affecting Deposit or Yield records is excluded.
Availability (A):
Measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability. This metric refers to smart contract features and functionality, not state. Availability impact directly affecting Deposit or Yield is excluded.
Deposit (D):
Measures the impact to the deposits made to the contract by either users or owners.
Yield (Y):
Measures the impact to the yield generated by the contract for either users or owners.
Metrics:
IMPACT METRIC (mIm_I)METRIC VALUENUMERICAL 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
Impact II is calculated using the following formula:

I=max(mI)+∑mI−max(mI)4I = max(m_I) + \frac{\sum{m_I} - max(m_I)}{4}

4.3 SEVERITY COEFFICIENT

Reversibility (R):
Describes the share of the exploited vulnerability effects that can be reversed. For upgradeable contracts, assume the contract private key is available.
Scope (S):
Captures whether a vulnerability in one vulnerable contract impacts resources in other contracts.
Metrics:
SEVERITY COEFFICIENT (CC)COEFFICIENT VALUENUMERICAL VALUE
Reversibility (rr)None (R:N)
Partial (R:P)
Full (R:F)		1
0.5
0.25
Scope (ss)Changed (S:C)
Unchanged (S:U)		1.25
1
Severity Coefficient CC is obtained by the following product:

C=rsC = rs

The Vulnerability Severity Score SS is obtained by:

S=min(10,EIC∗10)S = min(10, EIC * 10)

The score is rounded up to 1 decimal places.
SeverityScore Value Range
Critical9 - 10
High7 - 8.9
Medium4.5 - 6.9
Low2 - 4.4
Informational0 - 1.9

5. SCOPE

REPOSITORY
(a) Repository: lucid-contracts
(b) Assessed Commit ID: d955aeb
(c) Items in scope:
  • contracts/modules/chain-abstraction/yield-strategies/AaveYieldStrategy.sol
  • contracts/modules/chain-abstraction/LockReleaseAssetController.sol
Out-of-Scope: Third party dependencies and economic attacks.
Remediation Commit ID:
Out-of-Scope: New features/implementations after the remediation commit IDs.

6. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

0

Low

3

Informational

1

Security analysisRisk levelRemediation Date
Fragile allowance handling in yield componentsLowSolved - 11/12/2025
Inconsistent deposit accounting under non standard token behaviorLowSolved - 11/12/2025
Overoptimistic principal balance after withdrawalsLowSolved - 11/21/2025
Token amount is trusted on lock and release without verifying actual transferInformationalSolved - 11/12/2025

7. Findings & Tech Details

7.1 Fragile allowance handling in yield components

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/LucidLabsFi/lucid-contracts/commit/25652e80a9d3c05807a0f009eb07c15ad6beb846

7.2 Inconsistent deposit accounting under non standard token behavior

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/LucidLabsFi/lucid-contracts/commit/25652e80a9d3c05807a0f009eb07c15ad6beb846

7.3 Overoptimistic principal balance after withdrawals

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/LucidLabsFi/lucid-contracts/commit/f4e6bfe0ef08575281c80c577b5b5d8e3b86bfc7

7.4 Token amount is trusted on lock and release without verifying actual transfer

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/LucidLabsFi/lucid-contracts/commit/25652e80a9d3c05807a0f009eb07c15ad6beb846

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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