Prepared by:
HALBORN
Last Updated 03/18/2026
Date of Engagement: March 11th, 2026 - March 12th, 2026
No Reported Findings to Address
All findings
0
Critical
0
High
0
Medium
0
Low
0
Informational
0
Perle Labs engaged Halborn to conduct a security assessment on their PRL token beginning on March 11th, 2026 and ending on March 12th, 2026. The security assessment was scoped to the Token-2022 mint account deployed on Solana mainnet at address PERLEQKUNUp1dgFZ8EvyXHdN9d6ZQqfGxALDvfs6pDs, further details can be found in the Scope section of this report.
The Perle Labs team has deployed a Token-2022 token on Solana mainnet with a fixed supply of 1 billion tokens (8 decimals), using the Metadata Pointer and Token Metadata extensions for on-chain metadata management. The token's off-chain metadata is stored on Arweave for immutability.
Halborn was provided 2 business days for the engagement and assigned one full-time security engineer to review the security of the Solana Programs in scope. The engineer is a 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 no security issues in the token configuration. The Perle Labs team has correctly configured the PRL token with appropriate authority management, extension selection, and metadata setup.
Halborn performed a combination of manual review and security testing based on scripts 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.
Differences analysis using GitLens to have a proper view of the differences between the mentioned commits
Graphing out functionality and programs logic/connectivity/functions along with state changes
| EXPLOITABILITY METRIC () | METRIC VALUE | NUMERICAL 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 |
| IMPACT METRIC () | METRIC VALUE | NUMERICAL 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 |
| SEVERITY COEFFICIENT () | COEFFICIENT VALUE | NUMERICAL VALUE |
|---|---|---|
| Reversibility () | None (R:N) Partial (R:P) Full (R:F) | 1 0.5 0.25 |
| Scope () | Changed (S:C) Unchanged (S:U) | 1.25 1 |
| Severity | Score Value Range |
|---|---|
| Critical | 9 - 10 |
| High | 7 - 8.9 |
| Medium | 4.5 - 6.9 |
| Low | 2 - 4.4 |
| Informational | 0 - 1.9 |
Critical
0
High
0
Medium
0
Low
0
Informational
0
| Security analysis | Risk level | Remediation Date |
|---|
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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