← Back to Audits

Waterusdc and Vaultka Solana Programs - Vaultka

Prepared by:

Halborn Logo

HALBORN

Last Updated Unknown date

Date of Engagement: July 22nd, 2024 - August 19th, 2024

Summary

100% of all REPORTED Findings have been addressed

All findings

9

Critical

1

High

1

Medium

2

Low

3

Informational

2

Table of Contents

1. Introduction

Vaultka engaged Halborn to conduct a security assessment on their Waterusdc and Vaultka Solana programs beginning on July 22, 2024, and ending on August 19, 2024. The security assessment was scoped to the Solana Programs provided in vaultkarust GitHub repository. Commit hashes and further details can be found in the Scope section of this report.

The Waterusdc program is a single side lending pool program that allows whitelisted users or other programs to borrow USDC tokens from the lending pool. The Vaultkausdc program is a strategy program allowing users to borrow USDC tokens via the Waterusdc program and gain exposure to the Jupiter's JLP token. The program uses the Pyth oracle in order to fetch current JLP and USDC prices, and also allows users to use leverage up to certain limits to increase market exposure.

2. Assessment Summary

Halborn was provided 4 weeks for the engagement and assigned one full-time security engineer to review the security of the Solana Programs in scope. The engineer is a blockchain and smart contract security expert with advanced smart contract hacking skills, and deep knowledge of multiple blockchain protocols.

The purpose of the assessment is to:

    • Identify potential security issues within the Solana Programs.

    • Ensure that smart contract functionality operates as intended.

In summary, Halborn identified some security concerns that were addressed by Vaultka team. The main ones were the following:

    • Withdraw fee is transferred to the user instead of the fee vault

    • Inefficient slippage control

    • Incorrect token price conversion prevent withdrawal

    • Incorrect accounts mutability

Only informational issues were currently only acknowledged and not addressed.


3. Test Approach and Methodology

Halborn performed a combination of a manual review of the source code and automated security testing to balance efficiency, timeliness, practicality, and accuracy in regard to the scope of the program assessment. While manual testing is recommended to uncover flaws in business logic, processes, and implementation; automated testing techniques help enhance coverage of programs 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.

- Manual program source code review to identify business logic issues.

- Mapping out possible attack vectors

- Thorough assessment of safety and usage of critical Rust variables and functions in scope that could lead to arithmetic vulnerabilities.

- Scanning dependencies for known vulnerabilities (

cargo audit

- Local anchor testing (

anchor test

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: vaultkarust
(b) Assessed Commit ID: 6e81ea1
(c) Items in scope:
  • /vaultkarust/blob/fixes-tests/Anchor.toml
  • /vaultkarust/blob/fixes-tests/Cargo.toml
  • /vaultkarust/blob/fixes-tests/programs/vaultkausdc/Cargo.toml
↓ Expand ↓
Out-of-Scope: /vaultkarust/blob/fixes-tests/programs/watersol/Cargo.toml, /vaultkarust/blob/fixes-tests/programs/watersol/Xargo.toml, /vaultkarust/blob/fixes-tests/programs/watersol/src/lib.rs, /vaultkarust/blob/fixes-tests/migrations/deployUSDCStrategy.js, /vaultkarust/blob/fixes-tests/migrations/deployWaterUSDC.js, /vaultkarust/blob/fixes-tests/programs/vaultkasol/Cargo.toml, /vaultkarust/blob/fixes-tests/programs/vaultkasol/Xargo.toml, /vaultkarust/blob/fixes-tests/programs/vaultkasol/src/lib.rs, /vaultkarust/blob/fixes-tests/package.json, /vaultkarust/blob/fixes-tests/tsconfig.json
Out-of-Scope: New features/implementations after the remediation commit IDs.

6. Assessment Summary & Findings Overview

Critical

1

High

1

Medium

2

Low

3

Informational

2

Security analysisRisk levelRemediation Date
WITHDRAW FEE IS TRANSFERRED TO THE USER INSTEAD OF THE FEE VAULTCriticalSolved - 08/20/2024
INEFFICIENT SLIPPAGE CONTROLHighSolved - 08/25/2024
INCORRECT ACCOUNTS MUTABILITYMediumSolved - 08/22/2024
INCORRECT TOKEN PRICE CONVERSION PREVENTS WITHDRAWALMediumSolved - 08/20/2024
RISK OF OUTDATED PRICE FEEDLowSolved - 08/20/2024
SET_JLP_PRICE INSTRUCTION WILL ALWAYS FAILLowSolved - 08/20/2024
UNBOUNDED FEES CALCULATIONLowSolved - 08/20/2024
INABILITY TO CLOSE UNNEEDED ACCOUNTSInformationalAcknowledged
FORMAL ISSUES AND RECOMMENDATIONSInformationalAcknowledged

7. Findings & Tech Details

7.1 WITHDRAW FEE IS TRANSFERRED TO THE USER INSTEAD OF THE FEE VAULT

//

Critical

Description
Proof of Concept
BVSS
Recommendation
Remediation Comment

7.2 INEFFICIENT SLIPPAGE CONTROL

//

High

Description
Proof of Concept
BVSS
Recommendation
Remediation Comment

7.3 INCORRECT ACCOUNTS MUTABILITY

//

Medium

Description
Proof of Concept
BVSS
Recommendation
Remediation Comment

7.4 INCORRECT TOKEN PRICE CONVERSION PREVENTS WITHDRAWAL

//

Medium

Description
Proof of Concept
BVSS
Recommendation
Remediation Comment

7.5 RISK OF OUTDATED PRICE FEED

//

Low

Description
BVSS
Recommendation
Remediation Comment

7.6 SET_JLP_PRICE INSTRUCTION WILL ALWAYS FAIL

//

Low

Description
BVSS
Recommendation
Remediation Comment

7.7 UNBOUNDED FEES CALCULATION

//

Low

Description
BVSS
Recommendation
Remediation Comment

7.8 INABILITY TO CLOSE UNNEEDED ACCOUNTS

//

Informational

Description
BVSS
Recommendation
Remediation Comment

7.9 FORMAL ISSUES AND RECOMMENDATIONS

//

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.

// Download the full report

Waterusdc and Vaultka Solana Programs

* Use Google Chrome for best results

** Check "Background Graphics" in the print settings if needed