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Solana Agg Settlement Program - 0x Project

Prepared by:

Halborn Logo

HALBORN

Last Updated 04/10/2025

Date of Engagement: March 24th, 2025 - March 28th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

3

Critical

0

High

0

Medium

0

Low

0

Informational

3

Table of Contents

1. Introduction


ZeroEx engaged Halborn to conduct a security assessment on sol-settler program beginning on March 24th, 2025 and ending on March 28th, 2025. The security assessment was scoped to the smart contracts provided in the GitHub repository sol-settler, commit hashes and further details can be found in the Scope section of this report.


The ZeroEx team is releasing the sol-settler program, an onchain settlement program to support swap routes from an offchain aggregation service.


During the security assessment a new action was added, pumpswap_buy, which allows users to trade tokens directly from liquidity pools without intermediaries through Pump Swap, a decentralized exchange which relies on an automated market maker (AMM) system.

2. Assessment Summary

Halborn was provided 5 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 did not identify any significant security risks. However, some improvements were highlighted that were addressed by the ZeroEx team. The main ones were the following:

    • Add a check to ensure the provided wsol_mint_account corresponds to the native SOL mint.

    • Validate that amount_in is not lower than the actual balance of the sell account before processing any actions.

    • Replace expect() with structured error-handling mechanisms.


3. Test Approach and Methodology


Halborn performed a combination of a manual review of the source code and automated security testing to balance efficiency, timeliness, practicality, and accuracy in regard to the scope of the program assessment. While manual testing is recommended to uncover flaws in business logic, processes, and implementation; automated testing techniques help enhance coverage of programs 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, purpose, and use of the platform.

    • Manual program source code review to identify business logic issues.

    • Mapping out possible attack vectors

    • Thorough assessment of safety and usage of critical Rust variables and functions in scope that could lead to arithmetic vulnerabilities.

    • Scanning dependencies for known vulnerabilities (cargo audit).

    • Local runtime testing (cargo test)


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)+∑mI−max(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,EIC∗10)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

REPOSITORIES
(a) Repository: sol-settler
(b) Assessed Commit ID: 13410f6
(c) Items in scope:
  • sol-settler-main/program/Cargo.toml
  • sol-settler-main/program/src/constants.rs
  • sol-settler-main/program/src/cpi_utils.rs
↓ Expand ↓
Out-of-Scope: Third party dependencies and economic attacks.
(a) Repository: sol-settler
(b) Assessed Commit ID: 9f33067
(c) Items in scope:
  • program/src/cpi_utils.rs
  • program/src/dexes/mod.rs
  • program/src/dexes/pumpswap_amm/accounts.rs
↓ Expand ↓
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

3

Security analysisRisk levelRemediation Date
Lack of wsol mint validationInformationalSolved - 04/04/2025
Lack of amount in validation against sell account balanceInformationalSolved - 04/05/2025
Improper use of expect() after checked arithmetic leading to uncontrolled panicsInformationalSolved - 04/05/2025

7. Findings & Tech Details

7.1 Lack of wsol mint validation

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/0xProject/sol-settler/commit/3909555fad08fcb3e7aad0fd70301d9b8894a8df

7.2 Lack of amount in validation against sell account balance

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/0xProject/sol-settler/commit/3909555fad08fcb3e7aad0fd70301d9b8894a8df

7.3 Improper use of expect() after checked arithmetic leading to uncontrolled panics

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash
https://github.com/0xProject/sol-settler/commit/3909555fad08fcb3e7aad0fd70301d9b8894a8df

8. Automated Testing

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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Solana Agg Settlement Program

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