Taiko DAO Contracts - Taiko


Prepared by:

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HALBORN

Last Updated 04/10/2025

Date of Engagement: February 19th, 2025 - February 24th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

13

Critical

0

High

0

Medium

0

Low

1

Informational

12


1. Introduction

Taiko Labs engaged Halborn to conduct a security assessment on their smart contracts beginning on February 19th, 2025 and ending on February 25th, 2025. The security assessment was scoped to the smart contracts provided to Halborn. Commit hashes and further details can be found in the Scope section of this report.


The Taiko Labs codebase in scope consists of a DAO protocol leveraged by Aragon.

2. Assessment Summary

Halborn was provided 5 days for the engagement and assigned 2 full-time security engineers to review the security of the smart contracts in scope. The engineers are blockchain and smart contract security experts 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 improvements to reduce the likelihood and impact of risks, which were mostly addressed by the Taiko Labs team. The main ones are the following::

    • Introduce require statements in the constructor or deployOnce to validate all parameters.

    • Provide an upgrade path for long-lived DAOs.

    • Capture the creator’s owner/agent and store the agent used for encryption.


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 this 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 architecture, purpose and use of the platform.

    • Smart contract manual code review and walkthrough to identify any logic issue.

    • Thorough assessment of safety and usage of critical Solidity variables and functions in scope that could led to arithmetic related vulnerabilities.

    • Local testing with custom scripts (Foundry).

    • Fork testing against main networks (Foundry).

    • Static analysis of security for scoped contract, and imported functions (Slither).


4. Static Analysis Report

4.1 Description

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 related to external dependencies are not included in the below results for the sake of report readability.

4.2 Output

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







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:
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

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 (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}

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

REPOSITORY
(a) Repository: taiko-contracts
(b) Assessed Commit ID: eed36d3
(c) Items in scope:
  • src/adapted-dependencies/ITaikoL1.sol
  • src/conditions/StandardProposalCondition.sol
  • src/factory/TaikoDaoFactory.sol
↓ Expand ↓
Out-of-Scope: Third party dependencies and economic attacks.
Remediation Commit ID:
Out-of-Scope: New features/implementations after the remediation commit IDs.

7. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

0

Low

1

Informational

12

Security analysisRisk levelRemediation Date
Inconsistent Snapshot for Encryption AgentsLowRisk Accepted - 03/13/2025
Unused componentsInformationalSolved - 03/13/2025
Public functions not invoked internallyInformationalSolved - 03/25/2025
Lack of account removal mechanism in registryInformationalSolved - 03/17/2025
Missing visibility modifierInformationalSolved - 03/14/2025
Missing input validationInformationalPartially Solved - 03/14/2025
Empty 'revert' statementInformationalSolved - 03/14/2025
Missing address validation in signer managementInformationalAcknowledged - 03/20/2025
Unhandled return valuesInformationalAcknowledged - 03/20/2025
Floating pragmaInformationalAcknowledged - 03/20/2025
Redundant use of `this` keywordInformationalSolved - 03/14/2025
Missing eventsInformationalAcknowledged - 03/20/2025
Typo in error nameInformationalSolved - 03/14/2025

8. Findings & Tech Details

8.1 Inconsistent Snapshot for Encryption Agents

//

Low

Description
BVSS
Recommendation
Remediation Comment
References

8.8 Missing address validation in signer management

//

Informational

Description
BVSS
Recommendation
Remediation Comment
References

8.9 Unhandled return values

//

Informational

Description
BVSS
Recommendation
Remediation Comment
References

8.12 Missing events

//

Informational

Description
BVSS
Recommendation
Remediation Comment
References

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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