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BTCFi Lending Vault - Coredao

Prepared by:

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HALBORN

Last Updated 09/16/2025

Date of Engagement: August 28th, 2025 - September 4th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

7

Critical

0

High

0

Medium

3

Low

1

Informational

3

Table of Contents

1. Introduction

CoreDAO engaged Halborn to conduct a security assessment of the BTCFi Lending Vault contracts developed by the b14g team from August 28th to September 4th, 2025. The scope of this assessment was limited to the smart contracts provided to the Halborn team. Commit hashes and additional details are documented in the Scope section of this report.

2. Assessment Summary

The Halborn team dedicated a total of five days to this engagement, deploying one full-time security engineer to evaluate the smart contracts’ security posture.

The assigned security engineer is an expert in blockchain and smart contract security, with advanced skills in penetration testing, smart contract exploitation, and a comprehensive understanding of multiple blockchain protocols.

The objectives of this assessment were to:

    • Verify that the smart contract functions operate as intended.

    • Identify potential security vulnerabilities within the smart contracts.


In summary, Halborn identified several areas for improvement to reduce both the likelihood and impact of potential risks, which were partially addressed by the b14g team. The primary suggestions included:

    • Implement comprehensive oracle data validation with staleness and confidence checks before using prices in calculations.

    • Establish proper historical reward state tracking to prevent exploitation of uninitialized mapping slots.

    • Add health factor validation after pool withdrawals to prevent liquidation risk.

    • Implement proper error handling for external contract calls with try-catch blocks.

    • Add event emissions for all administrative parameter changes to enhance transparency.

    • Make critical addresses configurable instead of hardcoded to support network flexibility.

3. Test Approach and Methodology

Halborn employed a combination of manual, semi-automated, and automated security testing methods to ensure effectiveness, efficiency, and accuracy within the scope of this assessment. Manual testing was vital for uncovering issues related to logic, processes, and implementation details, while automated techniques enhanced code coverage and helped identify deviations from security best practices. The assessment involved the following phases and tools:

    • Research into the architecture and purpose of the smart contracts.

    • Manual review and walkthrough of the smart contract code.

    • Manual evaluation of critical Solidity variables and functions to identify potential vulnerability classes.

    • Manual testing using custom scripts.

    • Static security analysis of the scoped contracts and imported functions utilizing Slither.

    • Local deployment and testing with Foundry.


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: BTCFiLendingVaultContract
(b) Assessed Commit ID: 8fb8301
(c) Items in scope:
  • contracts/utils/WBTCSwap.sol
  • contracts/marketplace/LendingVaultV2.sol
  • contracts/marketplace/MergeMarketplaceStrategyV2.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

3

Low

1

Informational

3

Security analysisRisk levelRemediation Date
Stale Oracle Data Enables Slippage Protection BypassMediumSolved - 09/05/2025
Historical Data Loss Enables Reward TheftMediumSolved - 09/05/2025
Pool Withdrawal Without Health Factor ValidationMediumSolved - 09/05/2025
Unchecked External Call Return ValuesLowRisk Accepted - 09/10/2025
Operator Role Centralization RiskInformationalSolved - 09/10/2025
Silent Changes Reduce TransparencyInformationalAcknowledged - 09/10/2025
Hardcoded Network Addresses Reduce FlexibilityInformationalAcknowledged - 09/10/2025

7. Findings & Tech Details

7.1 Stale Oracle Data Enables Slippage Protection Bypass

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Medium

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/b14glabs/BTCFiLendingVaultContract/commit/e2a2da3fb2d17f6761164d2009715816b23e24fb

7.2 Historical Data Loss Enables Reward Theft

//

Medium

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/b14glabs/BTCFiLendingVaultContract/commit/05c7f274c6fb4ee8f197cd86799e81c7089a54ee

7.3 Pool Withdrawal Without Health Factor Validation

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Medium

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/b14glabs/BTCFiLendingVaultContract/commit/a9f2e4b61014b037bebdbbbe349904cb1c6a3bdc

7.4 Unchecked External Call Return Values

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Low

Description
BVSS
Recommendation
Remediation Comment

7.5 Operator Role Centralization Risk

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Informational

Description
BVSS
Recommendation
Remediation Comment

7.6 Silent Changes Reduce Transparency

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Informational

Description
BVSS
Recommendation
Remediation Comment

7.7 Hardcoded Network Addresses Reduce Flexibility

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Informational

Description
BVSS
Recommendation
Remediation Comment

8. Automated Testing

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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