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Introduction:
In the world of Bug Bounty hunting, a “duplicate” report often feels like a defeat, but for seasoned pentesters, it represents validation of methodology. This article dissects a real-world Broken Object Level Authorization (BOLA) vulnerability discovered in a healthcare application. The flaw allowed an attacker to bypass strict “Private Profile” settings by exploiting a silent JSON request, exposing not only Personally Identifiable Information (PII) but also sensitive internal infrastructure metadata, proving that if the data travels to the client, it is already at risk.
Learning Objectives:
- Understand the mechanics of BOLA (Broken Object Level Authorization) and how it differs from traditional IDOR.
- Learn how to analyze duplicate findings to refine penetration testing methodology.
- Identify and exploit insecure direct object references in modern JavaScript frameworks (Next.js).
You Should Know:
1. Reconnaissance and Identifying the Vulnerability
The initial discovery began with standard web application reconnaissance. The target was a healthcare platform where users could set their profiles to “Private.” However, during active browsing, the pentester noticed silent network requests occurring when viewing profiles.
Step‑by‑step guide explaining what this does and how to use it.
To replicate this recon phase on a similar target, you would use browser Developer Tools (F12) to monitor the Network tab.
- Open Developer Tools: Press `F12` or right-click and select “Inspect.”
- Navigate to Network Tab: Clear the existing log to reduce noise.
- Trigger the Feature: Visit a user profile page.
- Filter for XHR/Fetch: Look for requests ending in `.json` or containing data structures. In this case, the request pattern was:
`GET /_next/data/
/es/profile/[bash].json`</h2>
<ol>
<li>Analyze the Response: Click on the request and view the "Response" or "Preview" tab.</li>
</ol>
- Linux/macOS Command (cURL): Copy the request as cURL from the browser and run it in the terminal to inspect headers and data flow.
[bash]
curl -X GET 'https://target-health-app.com/_next/data/abc123build/es/profile/victim_user.json' \
-H 'User-Agent: Mozilla/5.0' \
-H 'Accept: application/json' \
-v
– Windows PowerShell: Use `Invoke-WebRequest` to fetch the data.
$response = Invoke-WebRequest -Uri 'https://target-health-app.com/_next/data/abc123build/es/profile/victim_user.json' $response.Content | ConvertFrom-Json | ConvertTo-Json
This revealed that the server was dumping the entire database object for the user, not just the public-facing fields.
2. Exploitation and Impact Analysis
The vulnerability allowed an attacker to fully enumerate private data for any user by simply changing the username in the URL path. The server failed to validate that the requester had permission to view the private object.
Step‑by‑step guide explaining what this does and how to use it.
To test for exploitation (on an authorized target or lab environment), you would perform object enumeration.
- Craft the Malicious Request: Modify the username parameter to target different accounts.
Attempting to access a different user's private data curl -X GET 'https://target-health-app.com/_next/data/abc123build/es/profile/admin.json' \ -H 'Cookie: session=YOUR_OWN_SESSION_COOKIE'
- Analyze the Exposed Data: The response contained two critical data types:
– PII Data: Full date of birth, precise location (postal code), internal database user IDs.
– Infrastructure Metadata: Internal IP addresses (e.g., 192.168.x.x, 10.x.x.x) of backend servers handling the request, leaking network topology.
3. Verification of BOLA: If you can access User B’s private data while authenticated as User A (or even unauthenticated), you have confirmed a BOLA vulnerability. The flaw lies in the object-level authorization check.
3. The Technical Root Cause: Server-Side Trust
The core issue was not a client-side rendering flaw but a backend development error. The developer configured the API endpoint to fetch and return the entire database object without filtering fields based on the requesting user’s privileges.
Code Analysis (Hypothetical):
Instead of creating a specific Data Transfer Object (DTO) for public profiles, the backend likely used a generic function like:
// Vulnerable Code Example
app.get('/_next/data/:buildId/profile/:username', (req, res) => {
const user = db.getUser(req.params.username); // Fetches FULL user object
res.json(user); // Returns EVERYTHING (password hash, PII, internal metadata)
});
// Secure Code Example
app.get('/api/profile/:username', (req, res) => {
const fullUser = db.getUser(req.params.username);
// Check authorization: Is the requester the owner?
if (req.session.userId !== fullUser.id) {
// Return only PUBLIC data
const publicProfile = {
name: fullUser.publicName,
photo: fullUser.photoUrl
};
return res.json(publicProfile);
}
// If owner, return full profile
res.json(fullUser);
});
4. Mitigation Strategies for Developers
To prevent such leaks, developers must implement strict authorization checks and data serialization.
Step‑by‑step guide explaining what this does and how to use it.
1. Implement Object-Level Authorization: Use middleware to verify the authenticated user’s identity against the object owner.
– Example (Linux/Dev mindset): Treat every object access as a unique permission check, similar to `chmod` for files.
2. Use DTOs (Data Transfer Objects): Never return database entities directly to the client.
– Command (Windows/Linux – using `jq` to simulate filtering): If you have a raw JSON export, filter it to see what should be sent.
Simulate filtering PII from a JSON dump
cat raw_user_data.json | jq '{public_name: .name, public_photo: .photo}'
3. Security Headers (Infrastructure Hardening): While this doesn’t fix the BOLA, it adds a layer of defense. Ensure the server is configured to hide internal IPs.
– Nginx (Linux): Hide server tokens.
server_tokens off; proxy_hide_header X-Powered-By; add_header X-Frame-Options "SAMEORIGIN" always;
– IIS (Windows): Use URL Rewrite to remove server headers or use the `HttpCustomHeaders` configuration.
5. Broader Security Implications and Hardening
The leak of internal IP addresses (metadata) is a gift for attackers. It maps the internal network, allowing for pivoting attacks if combined with other vulnerabilities.
Step‑by‑step guide explaining what this does and how to use it.
If an attacker extracts an internal IP like `10.0.0.45` from the JSON response, they can attempt to scan that network segment if they have achieved any level of access (e.g., SSRF or compromised host).
- Network Mapping (Linux): Use tools like `nmap` to scan the identified internal range (for authorized testing only).
Scan for open ports on the leaked internal IP nmap -sS -p 1-1000 10.0.0.45
- Cloud Hardening (AWS/Azure/GCP): Ensure metadata endpoints (like
169.254.169.254) are not accessible from application code. If an attacker gets an SSRF, they can steal cloud instance credentials.
– AWS WAF Rule: Block requests to the instance metadata IP.
– IMDSv2: Enforce session-oriented requests to add a layer of protection.
What Undercode Say:
- Duplicate ≠ Failure: Finding a duplicate vulnerability validates that your hunting methodology and analytical skills are sharp and aligned with industry best practices. It proves you are thinking like the attackers who found it first.
- Data is Exposure: The fundamental lesson here is “defense in depth” applied to data. The browser should never be the arbiter of privacy; if the server sends it, the user can see it. Filtering at the controller level is non-negotiable.
This case highlights the critical importance of strict object-level authorization. While the report was duplicated, the knowledge gained—specifically regarding the exposure of internal infrastructure via metadata—is invaluable. It reinforces the principle that security misconfigurations often lie not in complex algorithms, but in trusting the client to handle data it should never receive. The validation of one’s methodology is often a greater long-term asset than a single bounty payout.
Prediction:
As web applications increasingly rely on static site generation (SSG) and client-side hydration (like Next.js), we will see a rise in BOLA/IDOR vulnerabilities where `getServerSideProps` or `getStaticProps` functions leak excessive data into JSON blobs. Future exploitation will focus less on SQLi and more on API response manipulation, forcing a shift in defensive strategies toward robust data serialization and automated API schema validation rather than just perimeter firewalls. AI-powered security tools will soon be trained to detect these oversized JSON responses automatically, flagging them as high-risk leaks before they reach production.
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IT/Security Reporter URL:
Reported By: Maalfer1 Ciberseguridad – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
