zkPass Token Contract - ZKPass


Prepared by:

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HALBORN

Last Updated 11/26/2025

Date of Engagement: November 25th, 2025 - November 25th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

7

Critical

0

High

0

Medium

0

Low

0

Informational

7


1. INTRODUCTION

ZKPass engaged Halborn to conduct a security assessment on their smart contracts beginning and ending on November 25th, 2025. The security assessment was scoped to the smart contracts provided in the zkPass-Token-Contract GitHub repository, provided to the Halborn team. Commit hash and further details can be found in the Scope section of this report.


The reviewed contracts implement a fixed-supply omnichain ERC20 token that uses LayerZero OFT to burn on the source chain and mint on the destination chain during transfers. It also supports ERC20Permit for gasless approvals and ERC20Votes for governance.

2. ASSESSMENT SUMMARY

Halborn was provided with 1 day for this engagement and assigned a full-time security engineer to assess the security of the smart contracts in scope. The assigned engineer possesses deep expertise in blockchain and smart contract security, including hands-on experience with multiple blockchain protocols.


The objective of this assessment is to:

    • Identify potential security issues within the ZKPToken protocol smart contracts.

    • Ensure that smart contract of ````ZKPToken protocol functions operate as intended.


In summary, Halborn identified several areas for improvement to reduce the likelihood and impact of risks, which were mostly addressed by the ZKPass team. The main ones were:

    • Implementing a mechanism to invalidate outstanding permit signatures prior to their expiry.

    • Configuring the SUPPLY_CAP on non-mint chains to reflect the global supply and avoid ambiguity.

    • Preventing bridging to address(0), as such transfers will reduce the actual circulating supply.

    • Enforcing the global supply cap via the ERC20Votes supply guard.

    • Preventing renouncement of ownership to avoid locking essential OFT configuration.

3. TEST APPROACH AND METHODOLOGY

Halborn performed a combination of manual review of the code and automated security testing to balance efficiency, timeliness, practicality, and accuracy in regard to the scope of the smart contract assessment. While manual testing is recommended to uncover flaws in logic, process, and implementation, automated testing techniques help enhance coverage of smart contracts 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 and purpose of the ZKPToken protocol.

    • Manual code review and walkthrough of the ZKPToken in-scope contracts.

    • Manual assessment of critical Solidity variables and functions to identify potential vulnerability classes.

    • Manual testing using custom scripts.

    • Static Analysis of security for scoped contracts and imported functions. (Slither).

    • Local deployment and testing with (Foundry, Remix IDE).


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)+mImax(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,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

5. SCOPE

REPOSITORY
(a) Repository: zkPass-Token-Contract
(b) Assessed Commit ID: 5abbef5
(c) Items in scope:
  • src/Factory.sol
  • src/ZKPToken.sol
Out-of-Scope: Third party dependencies and economic attacks.
Remediation Commit ID:
Out-of-Scope: New features/implementations after the remediation commit IDs.

6. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

0

Low

0

Informational

7

Security analysisRisk levelRemediation Date
No mechanism to invalidate outstanding permit signatures before expiryInformationalSolved - 11/25/2025
SUPPLY_CAP not reflecting global supply on non-mint chains may lead to incorrect assumptionsInformationalSolved - 11/25/2025
Bridging to address(0) mints tokens to an irrecoverable sink, reducing actual circulating supplyInformationalSolved - 11/25/2025
Global supply cap is not enforced by ERC20Votes supply guardInformationalSolved - 11/25/2025
Checkpoint clock mode unclear and may not match intended governance designInformationalAcknowledged - 11/26/2025
Renouncing ownership can permanently lock essential OFT configurationInformationalSolved - 11/25/2025
Single-step ownership transfer increases risk of misconfigured or lost ownershipInformationalAcknowledged - 11/26/2025

7. Findings & Tech Details

7.1 No mechanism to invalidate outstanding permit signatures before expiry

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.2 SUPPLY_CAP not reflecting global supply on non-mint chains may lead to incorrect assumptions

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.3 Bridging to address(0) mints tokens to an irrecoverable sink, reducing actual circulating supply

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.4 Global supply cap is not enforced by ERC20Votes supply guard

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.5 Checkpoint clock mode unclear and may not match intended governance design

//

Informational

Description
BVSS
Recommendation
Remediation Comment

7.6 Renouncing ownership can permanently lock essential OFT configuration

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.7 Single-step ownership transfer increases risk of misconfigured or lost ownership

//

Informational

Description
BVSS
Recommendation
Remediation Comment

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.