Ripple - Smart Contract Audit - Credentials - Ripple


Prepared by:

Halborn Logo

HALBORN

Last Updated 06/27/2025

Date of Engagement: January 6th, 2025 - January 30th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

8

Critical

0

High

0

Medium

2

Low

2

Informational

4


1. Introduction

Ripple engaged Halborn to conduct a security assessment on XRP Ledger (XRPL) feature amendments beginning on January 6th, 2025 and ending on January 30th, 2025, focusing on modifications to the codebase between the commit 4c2e6a3 and the commit cd9b5c9. The review specifically targets changes introduced during these commits, assuming the validity of the pre-existing logic and excluding verification of its security, e.g., input validation of previously existing parameters.


The Credentials feature introduced new transaction validation mechanisms and structures that allow credential-based authorization within the Ripple network. This feature enables accounts to issue, manage, and verify credentials for transaction approval, adding an additional layer of security and control.

2. Assessment Summary

The team at Halborn assigned a full-time security engineer to assess the security of the node. The security engineer is a blockchain and smart-contract security expert in advanced penetration testing, smart-contract hacking, and deep knowledge of multiple blockchain protocols.

The purpose of this assessment is to:

    • Ensure that the new features operate as intended.

    • Identify potential security issues with the new features.


In summary, Halborn identified some improvements to reduce the likelihood and impact of risks, which were mostly acknowledged by the Ripple team. The main ones were the following: 

    • Ensure that expired NFT offers and credentials are handled separately by using distinct error codes.

    • Explicitly reject transactions signed with a disabled Master Key, even if it is also set as the Regular Key.

    • Replace assertions with explicit error handling that operates in all build configurations.

    • Include a check that confirms whether the recipient has configured Deposit Auth before invoking verifyDepositPreauth.

3. Test Approach and Methodology

Halborn performed a combination of manual review of the code and automated security testing to balance efficiency, timeliness, practicality, and accuracy in regard to the scope of the node security assessment. While manual testing is recommended to uncover flaws in logic, process, and implementation; automated testing techniques help enhance coverage 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 code review and walkthrough to identify any logic issue.

    • Graphing out functionality and contract logic/connectivity/functions.


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: rippled
(b) Assessed Commit ID: cd9b5c9
(c) Items in scope:
  • src/libxrpl/protocol/ErrorCodes.cpp
  • src/libxrpl/protocol/Indexes.cpp
  • src/libxrpl/protocol/InnerObjectFormats.cpp
↓ Expand ↓
Out-of-Scope: The review specifically targets changes introduced during the commit 4c2e6a3 and the commit cd9b5c9, assuming the validity of the pre-existing logic and excluding verification of its security, e.g., input validation of previously existing parameters.
Out-of-Scope: New features/implementations after the remediation commit IDs.

6. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

2

Low

2

Informational

4

Security analysisRisk levelRemediation Date
Incorrect handling of expired Credentials and NFT offersMediumRisk Accepted - 02/18/2025
Master Key persistence allows transactions despite being disabledMediumRisk Accepted - 01/28/2025
Assertions may lead to inconsistent behavior in productionLowRisk Accepted - 02/18/2025
Inconsistent credential handling when Deposit Auth is not configuredLowRisk Accepted - 02/18/2025
Incorrect error code for duplicate credential entriesInformationalAcknowledged - 03/16/2025
Misleading error handling for invalid ledger index valuesInformationalSolved - 03/11/2025
Expiration validation in doApply rather than preclaimInformationalAcknowledged - 02/18/2025
Inability to replace an expired credential due to duplicate checksInformationalAcknowledged - 02/26/2025

7. Findings & Tech Details

7.1 Incorrect handling of expired Credentials and NFT offers

//

Medium

Description
BVSS
Recommendation
Remediation Comment

7.2 Master Key persistence allows transactions despite being disabled

//

Medium

Description
BVSS
Recommendation
Remediation Comment

7.3 Assertions may lead to inconsistent behavior in production

//

Low

Description
BVSS
Recommendation
Remediation Comment

7.4 Inconsistent credential handling when Deposit Auth is not configured

//

Low

Description
BVSS
Recommendation
Remediation Comment

7.5 Incorrect error code for duplicate credential entries

//

Informational

Description
BVSS
Recommendation
Remediation Comment

7.6 Misleading error handling for invalid ledger index values

//

Informational

Description
BVSS
Recommendation
Remediation Comment

7.7 Expiration validation in doApply rather than preclaim

//

Informational

Description
BVSS
Recommendation
Remediation Comment

7.8 Inability to replace an expired credential due to duplicate checks

//

Informational

Description
BVSS
Recommendation
Remediation Comment

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.