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QST Staking Protocol - QuStream

Prepared by:

Halborn Logo

HALBORN

Last Updated 10/07/2025

Date of Engagement: September 18th, 2025 - September 25th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

5

Critical

0

High

0

Medium

2

Low

1

Informational

2

Table of Contents

1. Introduction

QuStream team engaged Halborn to conduct a security assessment of the qst-staking program from September 18th to September 25th, 2025. The security assessment was scoped to the smart contracts provided in the GitHub repository QuStream; commit hashes and further details can be found in the Scope section of this report.


qst-staking program is a secure, time-locked staking system on Solana designed to incentivize long-term commitment and network participation. Users can stake QST tokens in 25-day lock periods, during which they earn node keys (at a rate of two keys per 200,000 QST, subject to minimum requirements) and may optionally enroll in a bonus program that extends their commitment by an additional 10 days in exchange for enhanced rewards. The protocol incorporates a penalty-sharing mechanism , redistributing penalties collected from early unstakers among bonus enrollees, thereby aligning incentives and reinforcing protocol security.


It should be noted that changes made during the remediation phase that do not directly address the identified issues are considered out of scope for this security assessment.


2. Assessment Summary


Halborn was provided 6 days for the engagement and assigned 1 full-time security engineer to review the security of the Solana Program in scope. The engineer is 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 Program.

    • Ensure that smart contract functionality operates as intended.


In summary, Halborn identified some improvements to reduce the likelihood and impact of risks, which have been addressed by the QuStream team. The main ones were the following:

    • Modify the participation window and add additional validation in unstake_tokens in order to prevent unstaking until the stake window has ended.

    • Decouple the withdrawal process into two distinct steps.

    • Remove the ability to restart a staking window or introduce a stake_window_idstored in both pool and user stake accounts.

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 runtime testing (anchor test and <solana-test-framework).


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: qst-staking
(b) Assessed Commit ID: 6b5385d
(c) Items in scope:
  • programs/qst-staking/src/lib.rs
  • programs/qst-staking/Cargo.toml
  • programs/qst-staking/src/lib_devnet.rs
Out-of-Scope: Third party dependencies and economic attacks.
Remediation Commit ID:
  • 40b0a25
  • a3ec342
Out-of-Scope: New features/implementations after the remediation commit IDs.

6. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

2

Low

1

Informational

2

Security analysisRisk levelRemediation Date
Restaking During Stake Window Enables Node Key Inflation and OverwriteMediumSolved - 10/07/2025
Potential Inconsistent Bonus Reward Distribution in Staking ProtocolMediumSolved - 10/07/2025
Stake Window Reset Leads to Bonus Enrollment and Early Unstaking BypassLowSolved - 10/04/2025
Lack of Zero Amount Validation in unstake_tokens InstructionInformationalSolved - 10/04/2025
Redundant or Duplicated Validation Checks in Staking InstructionsInformationalPartially Solved - 10/04/2025

7. Findings & Tech Details

7.1 Restaking During Stake Window Enables Node Key Inflation and Overwrite

//

Medium

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.2 Potential Inconsistent Bonus Reward Distribution in Staking Protocol

//

Medium

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.3 Stake Window Reset Leads to Bonus Enrollment and Early Unstaking Bypass

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.4 Lack of Zero Amount Validation in unstake_tokens Instruction

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.5 Redundant or Duplicated Validation Checks in Staking Instructions

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

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.

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QST Staking Protocol

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