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Moonwell - MToken Fixes - Moonwell


Prepared by:

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HALBORN

Last Updated 04/02/2024

Date of Engagement by: March 12th, 2024 - March 19th, 2024

Summary

100% of all REPORTED Findings have been addressed

All findings

3

Critical

0

High

0

Medium

0

Low

0

Informational

3


1. Introduction

Moonwell engaged Halborn to conduct a security assessment on their smart contracts beginning on March 12th and ending on March 19th. The security assessment was scoped to the smart contracts provided in the moonwell-fi/mtoken-fixes GitHub repository. Commit hashes and further details can be found in the Scope section of this report.

2. Assessment Summary

Halborn was provided 1 week for the engagement and assigned 1 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 informational, non-critical issues as described in this report.

3. 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).


4. Manual Testing

The contracts in scope were thoroughly and manually analyzed for potential vulnerabilities and bugs, as well as known optimizations and best practices when developing Smart Contracts in Solidity.

While no major vulnerabilities were found within the scope and time frame provided, it's always important to highlight good practices that were identified during the assessment, which contribute positively to the security maturity of the contracts in-scope, such as:

- Thorough documentation using NatSpec.

- Correct handling of legacy Solidity versions, including using SafeMath and applying verifications to avoid arithmetic errors such as overflow and underflow.

- Access controls in functions that should only be called by the Governance are well-structured and provide an additional layer of security.

These security practices are applied industry-wide and should be considered in future implementations and developments.

5. 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.

5.1 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:
EXPLOITABILIY 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

5.2 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 (I:N)
Low (I:L)
Medium (I:M)
High (I:H)
Critical (I: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)+mImax(mI)4I = max(m_I) + \frac{\sum{m_I} - max(m_I)}{4}

5.3 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,EIC10)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

6. SCOPE

Files and Repository
(a) Repository: mtoken-fixes
(b) Assessed Commit ID: 7fb5569
(c) Items in scope:
  • src/MErc20DelegateFixer.sol
  • src/MErc20DelegateMadFixer.sol
  • src/proposals/mips/mip-m17/mip-m17.sol
Out-of-Scope:
Out-of-Scope: New features/implementations after the remediation commit IDs.

7. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

0

Low

0

Informational

3

Security analysisRisk levelRemediation Date
Events Are Missing `indexed` AttributeInformationalAcknowledged - 03/19/2024
Function not used internally can be marked `external`InformationalAcknowledged - 03/19/2024
Use custom errorsInformationalAcknowledged - 03/19/2024

8. Findings & Tech Details

8.1 Events Are Missing `indexed` Attribute

// Informational

Description

Indexed event fields make the data more quickly accessible to off-chain tools that parse events, and add them to a special data structure known as “topics” instead of the data part of the log. A topic can only hold a single word (32 bytes) so if you use a reference type for an indexed argument, the Keccak-256 hash of the value is stored as a topic instead.

Each event can use up to three indexed fields. If there are fewer than three fields, all of the fields can be indexed. It is important to note that each index field costs extra gas during emission, so it's not necessarily best to index the maximum allowed fields per event (three indexed fields).

This is specially recommended when gas usage is not particularly of concern for the emission of the events in question, and the benefits of querying those fields in an easier and straight-forward manner surpasses the downsides of gas usage increase.


- src/MErc20DelegateFixer.sol [Line: 12]

	    event UserFixed(address, address, uint256);

- src/MErc20DelegateFixer.sol [Line: 15]

	    event BadDebtRepayed(uint256);

- src/MErc20DelegateFixer.sol [Line: 18]

	    event BadDebtRepayedWithReserves(

Score
Recommendation

It is recommended to add the indexed keyword when declaring events, considering the following example:

    event Indexed(
        address indexed from,
        bytes32 indexed id,
        uint indexed value
    );

Remediation Plan

ACKNOWLEDGED: The Moonwell team acknowledged this issue.

8.2 Function not used internally can be marked `external`

// Informational

Description

In the mip-m17.sol contract, the description() function has its visibility set to public. Considering it is not called in the context of the smart contract, the function visibility can be changed to external, in order to enhance gas consumption.

- src/proposals/mips/mip-m17/mip-m17.sol [Line: 28]

	    function description() public view override returns (string memory) {

As public functions have wider access, they inherently are less gas-effective than external functions.

Score
Recommendation

It is recommended to change the function visibility from public to external, as follows:

	    function description() external view override returns (string memory) {


Remediation Plan

ACKNOWLEDGED: The Moonwell team acknowledged this issue.

8.3 Use custom errors

// Informational

Description

In Solidity smart contract development, replacing hard-coded revert message strings with the Error() syntax is an optimization strategy that can significantly reduce gas costs. Hard-coded strings, stored on the blockchain, increase the size and cost of deploying and executing contracts.

The Error() syntax allows for the definition of reusable, parameterized custom errors, leading to a more efficient use of storage and reduced gas consumption. This approach not only optimizes gas usage during deployment and interaction with the contract but also enhances code maintainability and readability by providing clearer, context-specific error information.

Score
Recommendation

It is recommended to replace hard-coded revert strings in require statements for custom errors, which can be done following the logic below.

1. Standard require statement (to be replaced):

require(condition, "Condition not met");

2. Declare the error definition to state

error ConditionNotMet();

3. As currently is not possible to use custom errors in combination with require statements, the standard syntax is:

if (!condition) revert ConditionNotMet();

More information about this topic in Official Solidity Documentation.



Remediation Plan

ACKNOWLEDGED: The Moonwell team acknowledged this issue.

9. Review Notes

I won't add Outdated compiler version issue as this constraint is inherent to the use of CompoundV2 and its dependencies as base.

10. Automated Testing

Introduction

Halborn used automated testing techniques to enhance the coverage of certain areas of the smart contracts in scope. Among the tools used was Slither, a Solidity static analysis framework. After Halborn verified the smart contracts in the repository and was able to compile them correctly into their abis and binary format, Slither was run against the contracts. This tool can statically verify mathematical relationships between Solidity variables to detect invalid or inconsistent usage of the contracts' APIs across the entire code-base.

The security team assessed all findings identified by the Slither software, however, findings with severity Information and Optimization are not included in the below results for the sake of report readability.


slither(01)
slither(02)
slither(03)
slither(04)

The findings obtained as a result of the Slither scan were reviewed, and they were not included in the report because they were determined false positives.

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.