Batch (Re-Audit) Audit | Ripple | Halborn Audit Reports

Summary

100% of all REPORTED Findings have been addressed

About this report

Assessment Type

Assurance Assessment

Date of Engagement

March 27th, 2026 - April 7th, 2026

Severity Breakdown

0Acknowledged
2Risk Accepted
1Solved
3All Findings

Critical0
High0
Medium0
Low0
Informational3
- 2Risk A.
- 1Solved

Introduction#

This security assessment was commissioned by Ripple. The review was performed by Halborn Inc. as part of the (TCE) program re-audit engagement, spanning from March 27, 2026 to April 7, 2026.

The scope of this re-audit covers the full Batch transaction implementation within the XRP Ledger (XRPL) codebase, with the assessment targeting commit hash 36503b50178393e372d46f3be3aaeb71f30acd93 from the fix pull request submitted at https://github.com/XRPLF/rippled/pull/6446.

The reviewed code is written in C++ and forms part of the rippled reference implementation. The purpose of this engagement is to verify that previously identified vulnerabilities have been correctly remediated and to identify any residual or newly introduced security issues in the updated Batch transaction logic prior to production deployment.

Assessment Summary#

The re-audit was conducted over a period of approximately 8 calendar days by a specialized team of Halborn security engineers with deep expertise in distributed ledger protocols and C++ systems security. The engagement was executed under the TCE program, ensuring continuous and structured verification of the remediation applied to the XRPL Batch transaction feature.

The primary objectives of this assessment were to:

Confirm the correctness and completeness of fixes introduced in pull request #6446.
Identify any residual vulnerabilities or logic gaps introduced or left unresolved in the updated codebase.
Evaluate the security posture of the Batch transaction execution pipeline as a whole.

Test Approach and Methodology#

The assessment followed a structured, multi-phase methodology designed to provide comprehensive coverage of the Batch transaction execution logic within the rippled C++ codebase.

The review was organized into the following sequential phases:

Scoping and Reconnaissance: The target pull request and commit hash were confirmed with the Ripple engineering team. Relevant source files, amendment flags, and transactor entry points were identified to establish a clear attack surface boundary.
Manual Code Review: A thorough, line-by-line manual review of the Batch-related logic was performed, focusing on transaction application order, view merging, invariant enforcement, signing and authorization flows, and mode-flag handling (tfUntilFailure, tfAllOrNothing). This phase represented the primary and most consequential portion of the assessment.
Automated Static Analysis: Automated tooling was applied to the C++ source to surface common vulnerability classes including memory safety issues, undefined behavior, and logic errors at scale.
Differential Analysis: The changes introduced in PR #6446 were compared against the previously audited codebase to isolate net-new changes and confirm that prior findings were addressed.
Test Coverage Review: Existing test suites were evaluated for completeness against the identified risk areas, with gaps in coverage noted where found, particularly around delegation and batch composition edge cases.

The methodology was weighted heavily toward manual review, given the complexity of the stateful transaction application pipeline and the need to reason carefully about execution order, view layering, and amendment interactions. Automated tooling served as a complementary layer to extend coverage breadth.

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 ( $m_e$ )	METRIC VALUE	NUMERICAL VALUE
Attack Origin (AO)	Arbitrary (AO:A)	1
Attack Origin (AO)	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

Exploitability

E

is calculated using the following formula:

$E = \prod m_e$

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 ( $m_I$ )	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

Impact

I

is calculated using the following formula:

$I = max(m_I) + \frac{\sum{m_I} - max(m_I)}{4}$

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 ( $C$ )	COEFFICIENT VALUE	NUMERICAL VALUE
Reversibility ( $r$ )	None (R:N)	1
	Partial (R:P)	0.5
	Full (R:F)	0.25
Scope ( $s$ )	Changed (S:C)	1.25
Scope ( $s$ )	Unchanged (S:U)	1

Severity Coefficient

C

is obtained by the following product:

$C = rs$

The Vulnerability Severity Score

S

is obtained by:

$S = min(10, EIC * 10)$

The score is rounded up to 1 decimal places.

Critical	High	Medium	Low	Informational
9 - 10	7 - 8.9	4.5 - 6.9	2 - 4.4	0 - 1.9

Scope#

https://github.com/XRPLF/rippled/pull/6446/changes/fd6326d114108c00e4f409b0667b9b7dcc02c12f

Out-of-Scope: New features/implementations after the remediation commit IDs.

Assessment Summary & Findings Overview#

#	Title	Severity	Score	Status
HAL-01	UntilFailure: tec inners merge into the batch view before the stop	Informational	—	Risk Accepted08/31/2026
HAL-02	No second invariant pass on the merged batch view	Informational	—	Risk Accepted08/19/2026
HAL-03	Delegation on inner batch transactions	Informational	—	Solved08/19/2026

Findings & Tech Details#

HAL-01Risk Accepted

UntilFailure: tec inners merge into the batch view before the stop

Informational

Description

Recommendation

Remediation Comment

HAL-02Risk Accepted

No second invariant pass on the merged batch view

Informational

Description

Recommendation

Remediation Comment

HAL-03Solved

Delegation on inner batch transactions

Informational

Description

Recommendation

Remediation Comment

Addressed in:

https://github.com/XRPLF/rippled/pull/6446/changes/fd6326d114108c00e4f409b0667b9b7dcc02c12f

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.