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Mutuum Contracts - Mutuum Finance

Prepared by:

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HALBORN

Last Updated 12/18/2025

Date of Engagement: November 19th, 2025 - November 21st, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

6

Critical

0

High

1

Medium

0

Low

4

Informational

1

Table of Contents

1. Introduction

Mutuum Finance engaged Halborn to perform a security assessment of their EVM smart contracts from November 18th, 2025, to November 26th, 2025. The assessment scope was limited to the smart contracts provided to Halborn. Commit hashes and additional details are available in the Scope section of this report.


The Mutuum Finance codebase in scope consists of solidity smart contracts that implement an aave inspired staking mechanism with additional features like dynamic exchange rate, and revised slashing mechanism.


2. Assessment Summary

Halborn was allocated 7 days for this engagement and assigned 1 full-time security engineer to conduct a comprehensive review of the smart contracts within scope. The engineer is an expert in blockchain and smart contract security, with advanced skills in penetration testing and smart contract exploitation, as well as extensive knowledge of multiple blockchain protocols.

The objectives of this assessment were to:

    • Identify potential security vulnerabilities within the smart contracts.

    • Verify that the smart contract functionality operates as intended.


In summary, Halborn identified some areas for improvement to reduce the likelihood and impact of potential risks, which were mostly addressed by the Mutuum Finance team. The primary recommendations were as follows:

    • Consider modifying the stake function to make sure that zero shares should not be minted

    • Consider deriving totalStaked on-chain directly from the referenced staking token’s totalSupply wherever it is feasible.

    • Consider validating cooldownSeconds and unstakeWindow at pool creation time to ensure their sum stays within a safe bound.

    • Consider introducing bounds checks on the allowable range of expo + targetDecimals before computing the power of ten, reverting with a clear error if the combination would exceed a predefined maximum.


3. Test Approach and Methodology

Halborn performed a combination of manual code review and automated security testing to balance efficiency, timeliness, practicality, and accuracy in regard to the scope of this assessment. While manual testing is essential to uncover flaws in logic, process, and implementation, automated testing techniques enhance coverage of smart contracts and can quickly identify issues that do not follow security best practices.


The following phases and associated tools were used throughout the assessment:

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

    • Manual code review and walkthrough of the smart contracts to identify potential logic issues.

    • Manual testing of all core functions, including deposit, withdraw, repay, and borrow, to validate expected behaviour and identify edge-case vulnerabilities.

    • Local testing to simulate contract interactions and validate functional and security assumptions using custom scripts (Foundry).

    • 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: mutuum-contracts
(b) Assessed Commit ID: 67782fe
(c) Items in scope:
  • src/mutuum/interfaces/IATokenCompat.sol
  • src/mutuum/interfaces/IDistributionManager.sol
  • src/mutuum/interfaces/IFeeCollector.sol
↓ Expand ↓
Out-of-Scope: Third party dependencies and economic attacks.
Remediation Commit ID:
  • c6612eb
  • 8d0e32e
Out-of-Scope: New features/implementations after the remediation commit IDs.

6. Assessment Summary & Findings Overview

Critical

0

High

1

Medium

0

Low

4

Informational

1

Security analysisRisk levelRemediation Date
First Depositor Share Price Manipulation Allows Theft of Future DepositsHighSolved - 12/03/2025
Reward Distribution Depends on Externally Supplied ValueLowRisk Accepted - 12/03/2025
Cooldown Underflow Risk with Extreme ParametersLowSolved - 12/03/2025
Potential Overflow in Pyth Price Scaling for Extreme ExponentsLowSolved - 12/03/2025
No Explicit RewardToken Liquidity Check in TreasuryLowSolved - 12/03/2025
Ambiguity Around Units for Slashing AmountsInformationalSolved - 12/03/2025

7. Findings & Tech Details

7.1 First Depositor Share Price Manipulation Allows Theft of Future Deposits

//

High

Description
Proof of Concept
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.2 Reward Distribution Depends on Externally Supplied Value

//

Low

Description
BVSS
Recommendation
Remediation Comment

7.3 Cooldown Underflow Risk with Extreme Parameters

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.4 Potential Overflow in Pyth Price Scaling for Extreme Exponents

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.5 No Explicit RewardToken Liquidity Check in Treasury

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.6 Ambiguity Around Units for Slashing Amounts

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

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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Mutuum Contracts

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