MPT DEX Audit | Ripple | Halborn Audit Reports

Summary

100% of all REPORTED Findings have been addressed

About this report

Assessment Type

Assurance Assessment

Date of Engagement

July 21st, 2025 - August 5th, 2025

Source Code

rippled

Assessed Commit ID

03e46cd

Severity Breakdown

0Risk Accepted
2Not Applicable
3Solved
5All Findings

Critical0
High2
- 1Solved
- 1N/A
Medium1
- 1N/A
Low0
Informational2
- 2Solved

Introduction#

XRPL Foundation engaged Halborn to perform a focused security assessment with particular attention on the new XLS-82d feature set. The review ran from 21 July 2025 to 5 August 2025. The scope, of engagement can be obtained from the scope section.

The XRPL (XRP Ledger) is a decentralised network supporting payments, tokenisation and now, via XLS-82d, native AMM pools. XLS-33 introduces MPTokens fungible assets that can be transferred without establishing trust-lines. These upgrades aim to broaden DeFi capabilities while maintaining XRPL’s guarantees of safety, determinism and low-latency settlement.

Assessment summary#

Halborn assigned one full-time senior security engineer with deep expertise in C++ ledger code, consensus protocols and DeFi primitives. The objective was to:

• Verify that AMM and MPT logic enforce the intended business rules

• Uncover vulnerabilities that could lead to fund loss, state corruption or denial of service

During the engagement Halborn identified three previously unknown denial-of-service vectors, all enabled by the “trust-line-free” nature of MPTokens:

1. Unsolicited MPToken can permanently freeze an AMM pool (blocks last-LP withdrawal, claw-back and deletion).

2. A single MPToken prevents an account from ever being deleted.

3. A single MPToken blocks an issuer from enabling RequireAuth or AllowTrustLineClawback in AccountSet.

Each issue is low cost to exploit (one standard transaction fee) and requires no permissions. Full details and remediation guidance are provided in the Findings section.

Methodology#

Halborn followed its standard hybrid methodology:

• Architectural review of AMM/MPT amendments and transaction flow

• Manual source-code inspection of C++ ledger logic (owner-directory handling, flag gating, AMM helpers)

• Differential analysis against pre-amendment behaviour

• Custom fuzz utilities for unsolicited MPToken injection

• Reproduction in a private XRPL test-net built from the audited commit

Static tools (clang-tidy, cppcheck) and the project’s own unit-test suite complemented the manual work, but the vulnerabilities discovered were logic-level and surfaced only through directed testing.

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#

(a) Repository:rippled

(b) Assessed Commit ID:03e46cd02617b3d7ce32c1a6820f91e2a04b961c

efb1dd5bfba2d7eecff5844a233bc7226858f7cb https://github.com/gregtatcam/rippled/tree/feature/mpt-v2e

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

Assessment Summary & Findings Overview#

#	Title	Severity	Score	Status
HAL-01	std::sort Without Strict Weak Ordering in compareAccountCandidate	High	7.5	Solved07/31/2025
HAL-02	AccountSet Flag-Change DoS via MPToken	High	7.5	Not Applicable08/05/2025
HAL-03	Unsolicited MPToken Makes Any Account Permanently Undeletable	Medium	5.0	Not Applicable08/05/2025
HAL-04	MPT Flags With canClawback & canTrade in DEX	Informational	0.0	Solved07/31/2025
HAL-05	MPTAmount stability check may trigger division by zero	Informational	0.0	Solved08/05/2025

https://github.com/gregtatcam/rippled/tree/feature/mpt-v2e

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.