Moonwell // SCA (Reserve + ERC20HoldingDeposit) Audit | Moonwell

Summary

100% of all REPORTED Findings have been addressed

About this report

Assessment Type

Assurance Assessment

Date of Engagement

February 3rd, 2025 - February 5th, 2025

Severity Breakdown

0Solved
1Acknowledged
1Risk Accepted
2All Findings

Critical0
High0
Medium0
Low1
- 1Risk A.
Informational1
- 1Ack.

Introduction#

Moonwell engaged Halborn to conduct a security assessment on their smart contracts beginning on February 3rd, 2025 and ending on February 5th. The security assessment was scoped to the smart contracts provided in the moonwell-fi/moonwell-contracts-v2 GitHub repository. Commit hash and further details can be found in the Scope section of this report.

Assessment Summary#

Halborn was provided three days for the engagement, and assigned one full-time security engineer to review the security of the smart contracts in scope. The engineer is a blockchain and smart contract security expert with advanced penetration testing and smart contract hacking skills, and deep knowledge of multiple blockchain protocols.

The purpose of the assessment is to:

Identify potential security issues within the smart contracts.
Ensure that smart contract functionality operates as intended.

In summary, Halborn identified some improvements to reduce the likelihood and impact of risks, which were acknowledged and accepted by the Moonwell team. The main ones are the following:

Implement validation checks for the returned oracle data when using the AggregatorV3Interface. Ensure that the latest returned timestamp is within the defined heartbeat interval for the requested asset.
Add an explicit check in the initiateSale() function to ensure that _miniAuctionPeriod > 1.
Create an access-controlled function, using SafeERC20 in order to allow the owner to withdraw unsold tokens after the sale.

Test Approach and Methodology#

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

Research into architecture and purpose.
Smart contract manual code review and walkthrough.
Graphing out functionality and contract logic/connectivity/functions (solgraph).
Manual assessment of use and safety for the critical Solidity variables and functions in scope to identify any arithmetic related vulnerability classes.
Manual testing by custom scripts.
Static Analysis of security for scoped contract, and imported functions (slither).
Testnet deployment (Foundry).

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 ( $m_e$ )	METRIC VALUE	NUMERICAL VALUE
Attack Origin (AO)	Arbitrary (AO:A)	1
Attack Origin (AO)	Specific (AO:S)	0.2
Attack Cost (AC)	Low (AC:L)	1
	Medium (AC:M)	0.67
	High (AC:H)	0.33
Attack Complexity (AX)	Low (AX:L)	1
	Medium (AX:M)	0.67
	High (AX:H)	0.33

Exploitability

E

is calculated using the following formula:

$E = \prod m_e$

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 ( $m_I$ )	METRIC VALUE	NUMERICAL VALUE
Confidentiality (C)	None (C:N)	0
	Low (C:L)	0.25
	Medium (C:M)	0.5
	High (C:H)	0.75
	Critical (C:C)	1
Integrity (I)	None (I:N)	0
	Low (I:L)	0.25
	Medium (I:M)	0.5
	High (I:H)	0.75
	Critical (I:C)	1
Availability (A)	None (A:N)	0
	Low (A:L)	0.25
	Medium (A:M)	0.5
	High (A:H)	0.75
	Critical (A:C)	1
Deposit (D)	None (D:N)	0
	Low (D:L)	0.25
	Medium (D:M)	0.5
	High (D:H)	0.75
	Critical (D:C)	1
Yield (Y)	None (Y:N)	0
	Low (Y:L)	0.25
	Medium (Y:M)	0.5
	High (Y:H)	0.75
	Critical (Y:C)	1

Impact

I

is calculated using the following formula:

$I = max(m_I) + \frac{\sum{m_I} - max(m_I)}{4}$

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 ( $C$ )	COEFFICIENT VALUE	NUMERICAL VALUE
Reversibility ( $r$ )	None (R:N)	1
	Partial (R:P)	0.5
	Full (R:F)	0.25
Scope ( $s$ )	Changed (S:C)	1.25
Scope ( $s$ )	Unchanged (S:U)	1

Severity Coefficient

C

is obtained by the following product:

$C = rs$

The Vulnerability Severity Score

S

is obtained by:

$S = min(10, EIC * 10)$

The score is rounded up to 1 decimal places.

Critical	High	Medium	Low	Informational
9 - 10	7 - 8.9	4.5 - 6.9	2 - 4.4	0 - 1.9

Scope#

Out-of-Scope: New features/implementations after the remediation commit IDs.

Assessment Summary & Findings Overview#

#	Title	Severity	Score	Status
HAL-01	Missing oracle data staleness check	Low	3.9	Risk Accepted02/12/2025
HAL-02	Division by zero	Informational	0.7	Acknowledged02/12/2025

Findings & Tech Details#

HAL-01Risk Accepted

Missing oracle data staleness check

Low

3.9AO:A/AC:L/AX:L/C:N/I:L/A:N/D:L/Y:N/R:N/S:CAO:A/AC:L/AX:L/C:N/I:L/A:N/D:L/Y:N/R:N/S:C

Description

Recommendation

Remediation Comment

HAL-02Acknowledged

Division by zero

Informational

0.7AO:A/AC:H/AX:H/R:N/S:C/C:N/A:N/I:M/D:N/Y:NAO:A/AC:H/AX:H/R:N/S:C/C:N/A:N/I:M/D:N/Y:N

Description

Recommendation

Remediation Comment

8. Automated Testing#

Disclaimer#

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.