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Background

// Security Assessment

01.02.2025 - 01.14.2025

Account Abstraction Schnorr Signatures SDK

InFlux Technologies

Halborn logotext
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Account Abstraction Schnorr Signatures SDK - InFlux Technologies


Prepared by:

Halborn Logo

HALBORN

Last Updated Unknown date

Date of Engagement: January 2nd, 2025 - January 14th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

10

Critical

0

High

0

Medium

0

Low

0

Informational

10


Table of Contents

  • 1. Introduction
  • 2. Assessment summary
  • 3. Test approach and methodology
  • 4. Risk methodology
  • 5. Scope
  • 6. Assessment summary & findings overview
  • 7. Findings & Tech Details
    1. 7.1 Lack of external calls validation
    2. 7.2 Predictable salt (colission attack risk)
    3. 7.3 Unspecified default hash function
    4. 7.4 Sensitive information in env vars
    5. 7.5 Vulnerable third-party dependencies
    6. 7.6 Lack of key validation
    7. 7.7 Hardcoded transaction cost
    8. 7.8 Not-used insecure method
    9. 7.9 Potential nonce reusage (key leakage risk)
    10. 7.10 Library usage recommendation

1. Introduction

InFlux Technologies engaged Halborn to conduct a security assessment on their web application beginning on 01/02/2025 and ending on 01/15/2025. The security assessment was scoped to the source code files provided to the Halborn team.

2. Assessment Summary

The team at Halborn was provided one week and a half for the engagement and assigned a full-time security engineer to verify the security of the scoped source code application files. 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 security assessment identified multiple critical areas requiring attention in the analyzed codebase, involving several issues and misconfigurations that the InFlux Technologies should address to enhance the application's security.

The lack of proper validation for external calls raised concerns about unchecked interactions with third-party contracts, potentially leading to unintended execution of malicious code.

Several medium-severity issues were also observed. The use of predictable salts during contract deployments could expose the system to collision attacks, jeopardizing address uniqueness. Additionally, the default hash function was not clearly specified, which could create inconsistencies or weaken the cryptographic integrity of the system. Sensitive information, including private keys, was potentially being stored within environment variables without sufficient protection, amplifying the risk of unauthorized access. The codebase also relied on third-party dependencies with known vulnerabilities, potentially exposing the entire project to inherited security flaws. Moreover, hardcoded transaction cost parameters may limit flexibility and could be exploited if not carefully controlled.

Furthermore, the absence of public key validation could allow unauthorized entities to submit invalid keys, increasing the likelihood of malicious transactions being accepted.

Lower-risk findings included the presence of insecure methods, which, although not actively used, could become a risk if reintroduced or overlooked in future development cycles.

Some other low severity issues involved cryptographic key handling and transaction integrity. Specifically, the potential reuse of nonces in the Schnorr signature scheme presented a substantial risk of private key leakage, compromising the overall integrity of the signing process.

Finally, an informational observation was also noted regarding the library usage, emphasizing the importance of clearly documenting and maintaining external code integrations.

Overall, while the project demonstrates solid foundations in many areas, these identified issues highlight the need for a more comprehensive approach to input validation, cryptographic hygiene, and dependency management to ensure long-term security and resilience.

It is recommended to resolve all the security issues listed in the document to improve the security health of the application and its underlying infrastructure.

3. Test Approach and Methodology

Halborn performed a combination of manual and automated security testing to balance efficiency, timeliness, practicality, and accuracy regarding the scope of the penetration test... While manual testing is recommended to uncover flaws in logic, process and implementation; automated testing techniques assist enhance coverage of the solution and can quickly identify flaws in it.

The following phases and associated tools were used throughout the term of the assessment:

    • Research about the scoped source code

    • Technology stack-specific vulnerabilities and public source code assessment

    • Vulnerable or outdated software

    • Exposure of any critical information

    • Application logic flaws

    • Access Handling

    • Authentication / Authorization flaws

    • Lack of validation on inputs and input handling

    • Brute force protections

    • Sensitive information disclosure

    • Source code review

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_eme​)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 EEE is calculated using the following formula:

E=∏meE = \prod m_eE=∏me​

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_ImI​)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 III is calculated using the following formula:

I=max(mI)+∑mI−max(mI)4I = max(m_I) + \frac{\sum{m_I} - max(m_I)}{4}I=max(mI​)+4∑mI​−max(mI​)​

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 (CCC)COEFFICIENT VALUENUMERICAL VALUE
Reversibility (rrr)None (R:N)
Partial (R:P)
Full (R:F)
1
0.5
0.25
Scope (sss)Changed (S:C)
Unchanged (S:U)
1.25
1
Severity Coefficient CCC is obtained by the following product:

C=rsC = rsC=rs

The Vulnerability Severity Score SSS is obtained by:

S=min(10,EIC∗10)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

REPOSITORY
(a) Repository: account-abstraction
(b) Assessed Commit ID: 588c582
Out-of-Scope: aa-schnorr-multisig-sdk/src/generated/typechain/*, OpenZeppelin files, Third party libraries
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

10

Security analysisRisk levelRemediation Date
LACK OF EXTERNAL CALLS VALIDATIONInformationalRisk Accepted - 02/04/2025
PREDICTABLE SALT (COLISSION ATTACK RISK)InformationalNot Applicable
UNSPECIFIED DEFAULT HASH FUNCTIONInformationalSolved - 02/04/2025
SENSITIVE INFORMATION IN ENV VARSInformationalRisk Accepted - 02/04/2025
VULNERABLE THIRD-PARTY DEPENDENCIESInformationalRisk Accepted - 02/04/2025
LACK OF KEY VALIDATIONInformationalSolved - 02/04/2025
HARDCODED TRANSACTION COSTInformationalNot Applicable
NOT-USED INSECURE METHODInformationalRisk Accepted - 02/04/2025
POTENTIAL NONCE REUSAGE (KEY LEAKAGE RISK)InformationalSolved - 02/04/2025
LIBRARY USAGE RECOMMENDATIONInformationalAcknowledged - 02/04/2025

7. Findings & Tech Details

7.1 LACK OF EXTERNAL CALLS VALIDATION

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.2 PREDICTABLE SALT (COLISSION ATTACK RISK)

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.3 UNSPECIFIED DEFAULT HASH FUNCTION

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.4 SENSITIVE INFORMATION IN ENV VARS

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.5 VULNERABLE THIRD-PARTY DEPENDENCIES

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.6 LACK OF KEY VALIDATION

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.7 HARDCODED TRANSACTION COST

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.8 NOT-USED INSECURE METHOD

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.9 POTENTIAL NONCE REUSAGE (KEY LEAKAGE RISK)

//

Informational

Description
Proof of Concept
Score
(0.0)
Recommendation
Remediation Comment

7.10 LIBRARY USAGE RECOMMENDATION

//

Informational

Description
Score
(0.0)
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.

Table of Contents

  • 1. Introduction
  • 2. Assessment summary
  • 3. Test approach and methodology
  • 4. Risk methodology
  • 5. Scope
  • 6. Assessment summary & findings overview
  • 7. Findings & Tech Details
    1. 7.1 Lack of external calls validation
    2. 7.2 Predictable salt (colission attack risk)
    3. 7.3 Unspecified default hash function
    4. 7.4 Sensitive information in env vars
    5. 7.5 Vulnerable third-party dependencies
    6. 7.6 Lack of key validation
    7. 7.7 Hardcoded transaction cost
    8. 7.8 Not-used insecure method
    9. 7.9 Potential nonce reusage (key leakage risk)
    10. 7.10 Library usage recommendation

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Account Abstraction Schnorr Signatures SDK

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