Summary
100% of all REPORTED Findings have been addressed
- 0Acknowledged
- 0Risk Accepted
- 12Solved
- 12All Findings
- Critical1
- 1Solved
- High0
- Medium5
- 5Solved
- Low3
- 3Solved
- Informational3
- 3Solved
Introduction#
BlockDAG engaged Halborn to conduct a security assessment on smart contracts beginning on February 5th, 2025 and ending on February 7th, 2025. The security assessment was scoped to the smart contracts provided to the Halborn team. Commit hashes and further details can be found in the Scope section of this report.
Assessment Summary#
The team at Halborn dedicated 3 days for the engagement and assigned one full-time security engineer to evaluate the security of the smart contract.
The security engineer is a blockchain and smart-contract security expert with advanced penetration testing, smart-contract hacking, and deep knowledge of multiple blockchain protocols
The purpose of this assessment is to:
Ensure that smart contract functions operate as intended.
Identify potential security issues with the smart contracts.
In summary, Halborn identified some improvements to reduce the likelihood and impact of risks, which were all addressed by the BlockDAG team. The main ones were the following:
Implement Correct logic for token distributionEnsure accurate accounting for multi sig approvalsStrengthening validation during token allocationImplement proper access control on release functions.Add an expiry mechanism to time-lock operations.Add explicit category validation at the start of the executeAddCategory function.Disable the initializer in the implementation contract.
Test Approach and Methodology#
Halborn performed a combination of manual, semi-automated and automated security testing to balance efficiency, timeliness, practicality, and accuracy regarding 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 the code 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 and purpose.
Smart contract manual code review and walk-through.
Manual assessment of use and safety for the critical Solidity variables and functions in scope to identify any vulnerability classes
Manual testing by custom scripts.
Static Analysis of security for scoped contract, and imported functions. (
Slither)Local deployment and testing (
Foundry)
Risk Methodology#
4.1 EXPLOITABILITY
Attack Origin (AO):
Attack Cost (AC):
Attack Complexity (AX):
Metrics:
| EXPLOITABILITY METRIC () | METRIC VALUE | NUMERICAL VALUE |
|---|---|---|
| Attack Origin (AO) | Arbitrary (AO:A) | 1 |
| 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 |
4.2 IMPACT
Confidentiality (C):
Integrity (I):
Availability (A):
Deposit (D):
Yield (Y):
Metrics:
| IMPACT METRIC () | 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 |
4.3 SEVERITY COEFFICIENT
Reversibility (R):
Scope (S):
Metrics:
| SEVERITY COEFFICIENT () | COEFFICIENT VALUE | NUMERICAL VALUE |
|---|---|---|
| Reversibility () | None (R:N) | 1 |
| Partial (R:P) | 0.5 | |
| Full (R:F) | 0.25 | |
| Scope () | Changed (S:C) | 1.25 |
| Unchanged (S:U) | 1 |
| Critical | High | Medium | Low | Informational |
| 9 - 10 | 7 - 8.9 | 4.5 - 6.9 | 2 - 4.4 | 0 - 1.9 |
Scope#
Assessment Summary & Findings Overview#
# | Title | Severity | Score | Status |
|---|---|---|---|---|
| No Token Distribution in BatchRelease Due to Premature State Updates | Critical | 10.0 | Solved02/18/2025 | |
| Total Amount Limit Can Be Bypassed During Allocations | Medium | 6.3 | Solved02/12/2025 | |
| Missing Access Control on Token Release Functions | Medium | 6.3 | Solved02/12/2025 | |
| Cleanup Reverts for Pause/Unpause Approvals | Medium | 5.9 | Solved02/18/2025 | |
| Double-Counting in Multi-Signature Approval for Users with Multiple Roles | Medium | 5.9 | Solved02/18/2025 | |
| Operator Approvals Equal to Admin Approvals | Medium | 5.4 | Solved02/18/2025 | |
| Timelock Operations Without Expiry | Low | 3.1 | Solved02/12/2025 | |
| Missing Category Validation | Low | 2.8 | Solved02/12/2025 | |
| Initializer Not Disabled | Low | 2.8 | Solved02/12/2025 | |
| Insufficient Validation Of Vesting Duration | Informational | 1.7 | Solved02/12/2025 | |
| Centralization Risks | Informational | 1.7 | Solved02/12/2025 | |
| Redundant Constants | Informational | 0.0 | Solved02/18/2025 |
Findings & Tech Details#
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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.
