How QA Engineers Detect BOLA and Sensitive Data Exposure in API Security Testing
Introduction
API security is a critical aspect of modern applications. One of the most common and severe issues is improper authorization, often categorized under Broken Object Level Authorization (BOLA).
This vulnerability can lead to unintended exposure of sensitive user data if access controls are not correctly implemented, making it a key risk area in API testing.
What is the Issue?
In many applications, APIs return user-related data based on identifiers such as user IDs. If authorization checks are weak or incomplete, users may gain access to data that does not belong to them.
This becomes a serious problem when sensitive information is exposed without proper filtering.
Example Scenario
Consider an API that returns user profile data.
A logged-in user requests their own profile → expected behaviour
The same user modifies the request to access another user’s data → should be restricted
However, in poorly implemented systems:
The API may still return full data
Sensitive fields may not be filtered
This can include:
Email addresses
Phone numbers
Authentication-related tokens
Internal identifiers
Why QA Engineers Should Prioritize BOLA Testing
BOLA vulnerabilities can lead to serious data leaks, impacting user privacy and system security.
For QA engineers, this type of issue is critical because APIs may appear functionally correct while still exposing unauthorized data.
Testing for BOLA ensures that sensitive information is properly protected and that access controls are correctly enforced across different user roles.
Why This Happens
This issue typically occurs when:
Authorization checks are only partially implemented
Role-based access control is inconsistent
APIs return the same response structure for all users
Even if some restrictions exist, incomplete filtering can still expose critical data.
How to Test for This
QA engineers can identify such issues by:
Modifying user identifiers in API requests
Testing access across different user roles
Comparing responses for owner vs non-owner access
Checking whether sensitive fields are filtered properly
Tools like Postman or REST Assured can be used to simulate these scenarios.
QA Checklist for Detecting Sensitive Data Exposure
Modify user identifiers (IDs) in API requests
Compare responses between authorized and unauthorized users
Check for presence of sensitive fields (email, phone, tokens)
Validate role-based data filtering
Ensure unnecessary fields are not returned
Verify API responses for least-privilege access
Best Practices
To prevent such issues:
Enforce strict authorization checks on every request
Filter sensitive fields based on user role
Avoid returning unnecessary data in API responses
Conclusion
Sensitive data exposure through APIs is a critical security risk. Even when partial access control exists, improper filtering can lead to unintended data leaks.
QA engineers should actively test for these scenarios as part of API validation to ensure secure and reliable systems.
About the Author
Asrar Bala (Asrar Ahmad Bala)
QA Engineer focused on automation and API testing
Portfolio: https://sites.google.com/view/asrarbala