Android SDK - Infatica


Prepared by:

Halborn Logo

HALBORN

Last Updated 08/26/2025

Date of Engagement: July 15th, 2025 - July 17th, 2025

Summary

100% of all REPORTED Findings have been addressed

All findings

3

Critical

0

High

0

Medium

2

Low

1

Informational

0


1. Introduction

Infatica engaged Halborn to conduct a code review assessment on their repository, beginning on July 15th 2025 and ending on July 17th 2025. The security assessment was scoped to the private repository that Infatica shared with the Halborn team.

2. Assessment Summary


The Halborn Team was allocated three days for this engagement, during which one full-time security engineer — expert in blockchain and security — conducted a comprehensive audit of the in-scope components related to Infatica repository. This engineer possesses advanced skills in penetration testing, web application security assessments, and an in-depth understanding of multiple blockchain protocols.

The primary objectives of this audit were to:

    • Verify that each component performs its intended functions accurately and reliably.

    • Identify and assess potential security issues within the source code, particularly those that could impact the privacy and protection of PII (Personally Identifiable Information).

Additional objectives included evaluating adherence to industry best practices, ensuring robust security measures are in place, and identifying opportunities for further strengthening the security posture.


The source code review of Infatica repository revealed several weaknesses demanding attention.

In the course of a comprehensive source code review of the Infatica SDK, four distinct security shortcomings were identified that merit prompt attention. First, the SDK’s Android test application was configured to permit cleartext traffic, thereby exposing user data and control communications to interception on untrusted networks. Second, numerous third‑party libraries were found to be outdated or comprised known vulnerabilities, potentially undermining the overall security posture of any integrating application. Third, the release build configuration omitted code minification and obfuscation, leaving internal implementation details readily accessible to reverse engineering and intellectual property theft. Finally, the SDK’s logging routines were observed to record network configuration information, such as DNS server addresses, which could inadvertently disclose network infrastructure data.

It is recommended that these areas be addressed holistically to elevate the security baseline of the Infatica SDK. Enforcement of encrypted communications, regular dependency management, activation of build‑time obfuscation, and adoption of secure logging practices will collectively ensure that the SDK remains robust against emerging threats and integrations uphold the highest standards of confidentiality and integrity.


Finally, based on the review of Infatica SDK, it can be confirmed that the code did not collect, process, or store any end‑user personal data (PII - Personally Idenfiable Information) beyond IP addresses and an anonymized UUID used solely for routing.

3. Test Approach and Methodology


Halborn combined manual and automated security testing to strike the right balance between speed, thoroughness, and precision within the scope of the penetration test. Manual techniques were employed to reveal nuanced logical, procedural, and implementation-level flaws, while automated tools broadened the assessment’s reach—rapidly pinpointing common vulnerabilities across the entire solution.

Throughout the engagement, we progressed through, among the following —but not limited to— phases (when applied), leveraging both targeted tools and bespoke techniques:

    • Content & Functionality Mapping
      Cataloging every feature and endpoint exposed by the application.

    • Technology-Stack & Public Code Review
      Identifying known vulnerabilities in frameworks, libraries, and any publicly accessible source repositories.

    • Software Version Analysis
      Detecting outdated or unpatched components.

    • Sensitive Data Exposure
      Hunting for leaks of critical or private information.

    • Business-Logic Testing
      Uncovering flaws in workflows, transaction flows, and access controls.

    • Access Control Assessment
      Verifying correct enforcement of permissions and role-based restrictions.

    • Authentication & Authorization
      Stress-testing login flows, token handling, and privilege escalation paths.

    • Input Validation & Handling
      Ensuring all user inputs are properly sanitized and parsed.

    • Fuzzing & Parameter Injection
      Applying randomized and structured payloads—SQL, JSON, HTML, command-line, directory path injections—to provoke unexpected behavior.

    • Brute-Force & Rate-Limiting Tests
      Validating defenses against credential stuffing, account-lockout bypass, and throttling evasion.

    • Response Manipulation
      Tampering with server replies to detect insecure assumptions or client-side vulnerabilities.

    • Deep Source-Code Review
      Manually inspecting critical modules for hidden flaws and backdoors.


4. Caveats

5. Scope

The initial commit ID was 90abe642305d4e9d141c3eb4324ea9e41aa3858b

However, after two days of the engagement, the commit was updated to 89afb4413271db462a729201af63a0b2128fbdb0 because there were many issues during the compilation process.

6. Constrains & Limitations

It was not possible to compile the provided source code due to persistent build errors encountered during the assessment. Although the Infatica team kindly supplied an updated version on the second day of our three‑day review, the revised code likewise failed to compile. Consequently, Halborn was unable to execute or test a functional, compiled SDK during this engagement.

7. RISK METHODOLOGY

Halborn assesses the severity of findings using either the Common Vulnerability Scoring System (CVSS) framework or the Impact/Likelihood Risk scale, depending on the engagement. CVSS is an industry standard framework for communicating characteristics and severity of vulnerabilities in software. Details can be found in the CVSS Specification Document published by F.I.R.S.T.
Vulnerabilities or issues observed by Halborn scored on the Impact/Likelihood Risk scale are measured by the LIKELIHOOD of a security incident and the IMPACT should an incident occur. This framework works for communicating the characteristics and impacts of technology vulnerabilities. The quantitative model ensures repeatable and accurate measurement while enabling users to see the underlying vulnerability characteristics that were used to generate the Risk scores. For every vulnerability, a risk level will be calculated on a scale of 5 to 1 with 5 being the highest likelihood or impact.
RISK SCALE - LIKELIHOOD
  • 5 - Almost certain an incident will occur.
  • 4 - High probability of an incident occurring.
  • 3 - Potential of a security incident in the long term.
  • 2 - Low probability of an incident occurring.
  • 1 - Very unlikely issue will cause an incident.
RISK SCALE - IMPACT
  • 5 - May cause devastating and unrecoverable impact or loss.
  • 4 - May cause a significant level of impact or loss.
  • 3 - May cause a partial impact or loss to many.
  • 2 - May cause temporary impact or loss.
  • 1 - May cause minimal or un-noticeable impact.
The risk level is then calculated using a sum of these two values, creating a value of 10 to 1 with 10 being the highest level of security risk.
Critical
High
Medium
Low
Informational
  • 10 - CRITICAL
  • 9 - 8 - HIGH
  • 7 - 6 - MEDIUM
  • 5 - 4 - LOW
  • 3 - 1 - VERY LOW AND INFORMATIONAL

8. SCOPE

REPOSITORIES
(b) Assessed Commit ID: 90abe64
(b) Assessed Commit ID: b0abd19
(b) Assessed Commit ID: 89afb44
Remediation Commit ID:
Out-of-Scope: New features/implementations after the remediation commit IDs.

9. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

2

Low

1

Informational

0

Security analysisRisk levelRemediation Date
CLEARTEXT TRAFFIC ALLOWEDMediumRisk Accepted - 08/11/2025
RELEASE BUILD WITHOUT CODE OBFUSCATIONMediumSolved - 08/11/2025
SENSITIVE INFORMATION DISCLOSURE VIA LOGGINGLowSolved - 08/11/2025

10. Findings & Tech Details

10.1 CLEARTEXT TRAFFIC ALLOWED

//

Medium

Description
Proof of Concept
Score
CVSS:3.1/AV:A/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N(5.7)
Recommendation
Remediation Comment

10.2 RELEASE BUILD WITHOUT CODE OBFUSCATION

//

Medium

Description
Proof of Concept
Score
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N(4.7)
Recommendation
Remediation Comment
Remediation Hash

10.3 SENSITIVE INFORMATION DISCLOSURE VIA LOGGING

//

Low

Description
Proof of Concept
Score
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:L/I:N/A:N(3.8)
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.