Summary
100% of all REPORTED Findings have been addressed
- 0Acknowledged
- 0Risk Accepted
- 2Solved
- 2All Findings
- Critical0
- High0
- Medium0
- Low1
- 1Solved
- Informational1
- 1Solved
Introduction#
The Rarimo team engaged Halborn to conduct a security assessment on their zero knowledge circuits and the verifier, beginning on 23/02/2024 and ending on 08/03/2024. The security assessment was scoped to the circuits provided to the Halborn team.
Assessment Summary#
The team at Halborn was provided two weeks for the engagement and assigned a full-time security engineer to verify the security of the zero knowledge circuits and the verifier. The security engineer is a blockchain, smart-contract, and ZK security expert with advanced penetration testing, smart-contract hacking, and deep knowledge of multiple blockchain protocols.
The purpose of this assessment is to achieve the following :
- Ensure that the circuits operate as intended.
- Identify potential security issues within the circuits.
- Ensure that the verifier operate as intended.
- Identify potential security issues within the verifier contracts.
In summary, Halborn identified some security risks that were successfully addressed by the Rarimo team.
Test Approach and Methodology#
Halborn performed a combination of manual 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 the code and can quickly identify items that do not follow the security best practices. The following phases and associated tools were used during the assessment:
Research into architecture and purpose.
Manual code review and walkthrough.
Graphing out functionality and contract logic/connectivity/functions.
Manual testing by custom scripts.
Used circomspect, a static analyzer and linter.
Used Picus, which checks for under-constrained bugs.
Out-of-scope#
External libraries and financial-related attacks.
New features/implementations after/with the remediation commit IDs.
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#
Findings & Tech Details#
Description
Recommendation
Description
Recommendation
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.