Rebalance Contract Audit | FortunaFi

Summary

100% of all REPORTED Findings have been addressed

About this report

Assessment Type

Assurance Assessment

Date of Engagement

August 6th, 2025 - August 6th, 2025

Source Code

rebalance

Assessed Commit ID

8e11a72

Severity Breakdown

0Solved
2Acknowledged
3Risk Accepted
5All Findings

Critical0
High0
Medium0
Low3
- 3Risk A.
Informational2
- 2Ack.

Introduction#

FortunaFi engaged Halborn to conduct a security assessment of their smart contract on August 6th, 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.

Assessment Summary#

The Halborn team dedicated a total of one day to this engagement, deploying one full-time security engineer to evaluate the smart contract’s 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 a limited number of issues that were acknowledged by the FortunaFi team. The key recommendations included:

Restrict access to the refill() function to prevent unauthorized or malicious usage.
Prevent arithmetic underflow in _maxRebalance() caused by unsafe decimal scaling operations.
Add zero address validation to the contract constructor to avoid deployment with an unusable admin account.
Implement input validation in rebalance() to reject zero-amount operations and avoid unnecessary gas costs.

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.

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#

(a) Repository:rebalance

(b) Assessed Commit ID:8e11a7290bd47649f47b27ad143c9f785db28b2f

1 files

src

1 file

Rebalance.sol

solidity

Out-of-Scope:Third Party Dependencies and Economic Attacks

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

Assessment Summary & Findings Overview#

#	Title	Severity	Score	Status
HAL-01	Missing Access Control on Refill Function	Low	4.2	Risk Accepted11/05/2025
HAL-02	Decimal Scaling Arithmetic Underflow	Low	3.4	Risk Accepted11/05/2025
HAL-03	Constructor Accepts Zero Address Admin	Low	2.0	Risk Accepted11/05/2025
HAL-04	Multiple PSMs with Same Token Causes Data Corruption	Informational	1.5	Acknowledged11/05/2025
HAL-05	Missing Zero Amount Validation	Informational	0.5	Acknowledged11/05/2025

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.