RUJI Trade FIN v1.1 - THORChain


Prepared by:

Halborn Logo

HALBORN

Last Updated 12/08/2025

Date of Engagement: November 12th, 2025 - November 20th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

6

Critical

0

High

0

Medium

0

Low

2

Informational

4


1. Introduction

THORChain engaged Halborn to conduct a security assessment of the Rujira FIN contracts, beginning on November 10th, 2025 and ending on November 18th, 2025. This security assessment was scoped exclusively to the updates introduced in version 1.1.0 of Rujira FIN, as the core system had already been reviewed in a previous audit. Commit hashes and further details can be found in the Sources section of this report.


Rujira FIN is a decentralized order book protocol built on top of Thorchain, enabling spot trading of native assets without wrapped tokens. It handles order creation, matching, and settlement fully on-chain.


2. Assessment Summary

The team at Halborn assigned a full-time security engineer to verify the security of the updated smart contracts. 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 was to:

    • Ensure that the updated smart contract functions operate as intended

    • Identify potential security issues introduced or affected by the new logic in version 1.1.0


In summary, Halborn identified a few improvements to further harden the system and reduce the likelihood or impact of potential risks, which have been completely addressed by the Rujira development team. The most relevant ones were the following:

    • Forbid denom changes during migration unless the contract is fully shut down or enforce a pre-migration check ensuring no active orders or pools exist.

    • Deduplicate or reject repeated MarketMaker addresses during initialization before storing them.

    • Replace inv().unwrap() with a checked inversion that errors on zero or tiny prices, and validate MM price inputs before use.

    • Reject zero or negative tick values during configuration and validate ticks explicitly in Tick::new and Tick::validate.

    • Explicitly reject Fixed <= 0 before tick validation, add guards to prevent underflow in truncation, and ensure validation returns a contract error instead of panicking.

    • Replace the intermediate multiplication with amount.multiply_ratio(...) to avoid overflow and add tests with values near Uint128::MAX.


3. 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 essential to uncover flaws in logic, process, and implementation, automated techniques enhance coverage and quickly detect deviations from best practices.


The following phases and associated tools were used during the assessment:

    • Research into architecture, version 1.1.0 updates, and overall protocol purpose.

    • Manual code read and walkthrough of the updated Rust modules.

    • Manual assessment of critical arithmetic operations, rate handling, and overflow/underflow protections.

    • Logical review of order matching, bucket aggregation, and MarketMaker calculation flow.

    • Validation of safe handling for zero and invalid price conditions.

    • Review and verification of integration and unit tests covering the updated logic.


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)+mImax(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,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

5. SCOPE

REPOSITORY
(a) Repository: rujira
(b) Assessed Commit ID: 306dc1e
(c) Items in scope:
  • contracts/rujira-fin/src/events.rs
  • contracts/rujira-fin/src/market_makers.rs
  • contracts/rujira-fin/src/order.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

2

Informational

4

Security analysisRisk levelRemediation Date
Denoms can be changed during migrate with an active order bookLowSolved - 11/26/2025
Duplicate Market Makers addresses allow liquidity double-countingLowSolved - 11/26/2025
Zero Tick size collapses price grid and blocks non-zero fixed pricesInformationalSolved - 11/26/2025
Swap operation panics on zero or tiny MarketMaker pricesInformationalSolved - 11/26/2025
Accepting `Fixed(0) prices triggers unhandled panic during Tick validationInformationalSolved - 11/26/2025
Potential Uint128 overflow in EitherOrBoth proportional splitInformationalSolved - 11/26/2025

7. Findings & Tech Details

7.1 Denoms can be changed during migrate with an active order book

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.2 Duplicate Market Makers addresses allow liquidity double-counting

//

Low

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.3 Zero Tick size collapses price grid and blocks non-zero fixed prices

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.4 Swap operation panics on zero or tiny MarketMaker prices

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.5 Accepting `Fixed(0) prices triggers unhandled panic during Tick validation

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

7.6 Potential Uint128 overflow in EitherOrBoth proportional split

//

Informational

Description
BVSS
Recommendation
Remediation Comment
Remediation Hash

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.