Bug Bounty Blogs – Hackersatty – Learn Ethical Hacking, Bug Bounty, and Cybersecurity Tips

How I Abused a Race Condition to Create Duplicate Notification Records (sanitized)

hackersatty — Sun, 26 Oct 2025 06:18:03 +0000

Author: Satyam Pawale — hackersatty.com
Target (sanitized): vendor.hackersatty.com — Dashboard → Settings → Notifications → Add notification (modal)
Severity: High

About Me

Hey! I’m Satyam Pawale, known as @hackersatty in the bug bounty and ethical hacking world. I started bug hunting in 2024, and ever since, I’ve been obsessed with finding vulnerabilities that most people overlook.

My goal with this blog is to share real-world bug bounty experiences so other hunters can learn the techniques, tools, and mindset required to succeed — while staying ethical and responsible.

This case is about how I found critical admin endpoint vulnerabilities that allowed direct, unauthorized access to sensitive backend pages and data.

Summary

A race condition in the GraphQL CreateNotification flow allows many identical notification records to be created for the same (email, notificationType) pair by sending the same mutation concurrently. The backend performs a non-atomic existence check + insert (or lacks a uniqueness constraint), so parallel requests each succeed and create duplicate rows. Impact includes duplicate emails, queue exhaustion, corrupted metrics, and amplified downstream processing. Fix by enforcing atomic deduplication (DB unique constraint, upsert, or transactional locking) and canonicalizing inputs server-side.

Overview

While testing the notifications feature on a sanitized test instance, I discovered that sending the exact same CreateNotification GraphQL mutation near-simultaneously results in multiple identical notification records. The web UI may include client-side deduplication for UX, but the server accepts every concurrent request and persists a row per request because there is no server-side atomic deduplication or uniqueness enforcement.

All artifacts in this write-up are sanitized: domain names and identifiers use hackersatty.com and no real emails or tokens are included.

Vulnerability —

Race condition / missing server-side uniqueness: concurrent CreateNotification GraphQL mutations for the same canonical (email, notificationType) create duplicate database records.

Why this matters

Duplicate emails — recipients receive the same notification multiple times (spam, reputational risk).
Queue & worker load — duplicate rows trigger duplicate processing and waste resources.
Analytics pollution — duplicate rows inflate counts and break metrics.
Downstream amplification — exports, reporting, or workflows iterating over rows are multiplied.
Highly automatable — a script or proxy tool can reliably create many duplicates.

Best reproduction scenario

Preconditions

Valid test account on the portal.
Active session cookie or Authorization bearer token (the same session used by the UI).
Intercepting proxy or HTTP client that can replay requests concurrently (Burp Repeater, curl with xargs -P, Python aiohttp script, etc.).
Testing done only on authorized environments.

Steps

Log into the portal at vendor.hackersatty.com with a test account.
Dashboard → Settings → Notifications → Add notification (open the modal).
Fill notification type (example: ACCOUNT_UPDATES) and a placeholder email (sanitized).
Click Save once — confirm a single entry is created (expected).
Start an intercepting proxy and perform the same Add action again to capture the GraphQL mutation for CreateNotification.
Send the captured POST /graphql request to the proxy’s Repeater (or save the raw request).
Clone the captured request many times (e.g., 5–20 identical copies).
Use Send group (Parallel) in Burp Repeater (or run the copies concurrently via a script) so they hit the server within milliseconds of each other.
Observe: each response returns success (HTTP 200 + GraphQL create payload).
Refresh the Notifications UI — multiple identical notification rows appear for the same (email, notificationType) equal to the number of successful concurrent requests.

Sanitized PoC — Request (GraphQL mutation)

POST /graphql HTTP/2

Host: vendor.hackersatty.com

Content-Type: application/json

Apollographql-Client-Name: vendor-portal

Authorization: Bearer 

Origin: https://vendor.hackersatty.com

Referer: https://vendor.hackersatty.com/dashboard/settings/notifications

{ "operationName": "CreateNotification", "variables": { "input": { "email": "", "notificationType": "ACCOUNT_UPDATES", "accountId": 12345 } }, "query": "mutation CreateNotification($input: CreateNotificationInput!) { createNotification(input: $input) { accountId notificationType email __typename } }" }

Sanitized PoC — Typical Response (each concurrent request returns same success)

Each parallel request returns a created payload and, after refresh, multiple identical notification rows exist in the UI.

Exactly how the race condition happens (technical explanation)

Non-atomic check-then-insert: the server likely performs if not exists then insert.
Concurrency window: when multiple identical requests arrive simultaneously, each executes the existence check before any concurrent inserts commit; each sees “no existing row” and proceeds to INSERT.
No DB uniqueness constraint: the DB lacks a uniqueness constraint on (canonical_email, notification_type), so all inserts succeed.
Outcome: the application returns “created” for each request; multiple identical records are persisted.
Symptoms: N UI rows for N concurrent requests; duplicated processing downstream.

This is the classic race condition between check and insert under concurrency — the fix is to make creation atomic at the storage layer or to serialize the creation path.

Techniques & tools used (methodology)

Intercepting proxy: Burp Suite (Proxy + Repeater) with Send group (Parallel).
Alternative concurrency methods: curl with xargs -P, Python aiohttp or threaded requests, wrk/hey.
Verification: compare number of created rows in UI to number of concurrent requests; inspect GraphQL responses for created payloads.
Sanitization: remove tokens, emails, and PII from stored artifacts.
Optional automation: small async script that sends identical POSTs concurrently to reproduce in staging.

Concrete fixes (prioritized)

1) Enforce uniqueness at the database layer (recommended)

Create a unique index on canonicalized email + notification_type:

This guarantees the storage layer prevents duplicates under concurrent load.

2) Use atomic upsert (`ON CONFLICT`)

Preferred pattern:

Or ON CONFLICT DO NOTHING followed by SELECT the existing row if you need to return it.

3) Server-side canonicalization

Always canonicalize emails server-side (trim + lowercase + unicode normalize) before checks or inserts.

4) Optional: idempotency token

If clients can provide an idempotency key, enforce it server-side to dedupe create attempts. This is most suitable for API clients rather than basic UI clicks.

5) Transactional locking / advisory locks

If ON CONFLICT is not available, use transactional serialization or an advisory lock keyed by (account_id, canonical_email, notification_type) to serialize creation. This is less desirable than DB uniqueness + upsert.

Pseudocode — atomic upsert (preferred)

Detection & monitoring recommendations

Alert on spikes in notifications creation per account or per email.
Instrument unique-violation metrics after adding constraints to detect attempted duplicates.
Audit logs: record create attempts, client IPs, and request ids for concurrent patterns.
Queue monitoring: track message queue length and worker backlogs triggered by notification rows.

Safe remediation rollout plan

Immediate
- Canonicalize emails server-side (lowercase + trim).
- Add rate limits to the create endpoint.
High priority
- Clean existing duplicates (see dedupe plan below).
- Create a unique index concurrently and change create flow to INSERT ... ON CONFLICT.
Post-fix
- Run dedupe migration in controlled batches and add monitoring.

Dedupe migration (safe approach)

Backup the table.
Identify duplicates:

Keep one canonical row (e.g., earliest created_at) and delete others in batches:

Validate referential integrity and update dependent tables if necessary. Run in small batches with an audit trail.

Example automated reproduction script (sanitized, Python async)

For authorized testing only — do not run against production without permission.

# async_replay.py (sanitized)

import asyncio

import aiohttp
URL = "https://vendor.hackersatty.com/graphql"

HEADERS = {

    "Content-Type": "application/json",

    "Authorization": "Bearer "

}

PAYLOAD = {

  "operationName": "CreateNotification",

  "variables": {

    "input": {

      "email": "",

      "notificationType": "ACCOUNT_UPDATES",

      "accountId": 12345

    }

  },

  "query": "mutation CreateNotification($input: CreateNotificationInput!) { createNotification(input: $input) { accountId notificationType email } }"

}
async def send_one(session):

    async with session.post(URL, json=PAYLOAD, headers=HEADERS) as resp:

        text = await resp.text()

        return resp.status, text
async def main(n):

    async with aiohttp.ClientSession() as session:

        tasks = [send_one(session) for _ in range(n)]

        return await asyncio.gather(*tasks)

if __name__ == "__main__": results = asyncio.run(main(10)) for status, body in results: print(status, body[:200])

This script sends 10 concurrent create requests; on an affected system you would see multiple created rows.

Short checklist to verify the fix in staging

Add canonicalization and upsert logic + unique index in a branch.
Run the staging app and attempt the same parallel test (Burp Repeater Send group or the async script).
Confirm only one notification row exists per canonical (email, notificationType) after the concurrent attempts.
Monitor logs and unique-violation metrics; expect zero unhandled constraint errors in normal flow.
Run the dedupe migration if historical duplicates exist and then create the index.

Summary —

Enforce uniqueness at the DB layer: create a unique index on canonicalized (lower(email), notification_type).
Make creation atomic: use INSERT ... ON CONFLICT (upsert) or equivalent so concurrent creates cannot produce duplicates.
Canonicalize inputs server-side: trim and lowercase emails and return the existing resource or a clear response when duplicates are attempted.

Final Thoughts

This case is a perfect reminder that even mature applications can overlook concurrency edge cases that don’t show up in regular testing. Client-side validation or simple “check-before-insert” logic might appear sufficient, but when operations run in parallel, the tiniest race window can lead to large-scale data integrity issues.

What made this bug particularly impactful is that it didn’t rely on exotic conditions or privilege escalation — just timing. By coordinating concurrent identical requests, an attacker could manipulate backend logic in ways that normal single-threaded testing would never reveal.

In real-world systems where notifications, transactions, or queue-based processes are triggered by new records, such duplication can have serious downstream effects — from flooding users with redundant messages to distorting analytics or overloading task queues.

Building truly robust APIs requires more than input validation; it demands atomic operations, proper database constraints, and a mindset that anticipates concurrency. Race conditions often hide in plain sight, but once discovered, they offer some of the most valuable lessons for improving backend resilience.

In short, always think in parallel — because your attackers certainly will.

5 Steps to Exploit a Critical IDOR Vulnerability in Webhook Deletion

hackersatty — Sun, 14 Sep 2025 03:50:49 +0000

Critical IDOR Vulnerability in Webhook Deletion – A Real-World Exploitation Guide

When testing web applications, one of the most common but high-impact issues I encounter is Insecure Direct Object Reference (IDOR). In this blog, I will walk you through how I discovered a Critical IDOR vulnerability in a webhook deletion functionality on my testing platform (hackersatty.com).

This post is a complete breakdown of how I identified the vulnerable endpoint, exploited it, and demonstrated real-world impact — all while following responsible testing practices.

What is an IDOR Vulnerability?

Insecure Direct Object Reference (IDOR) is a type of access control vulnerability where an application exposes internal identifiers (like user IDs, webhook IDs, or document IDs) without properly checking if the user is authorized to access them.

In simple terms: if you can change an id in a request and access or delete something that belongs to another user, the application is vulnerable to IDOR.

Why IDOR in Webhook Deletion is Critical

Webhooks are essential for integrating systems — they send automated updates and notifications between platforms.

Now, imagine a situation where any user can delete another user’s webhook. This means:

Service disruption
Loss of customer integrations
Denial of important notifications
Direct impact on business operations

That’s why Critical IDOR vulnerability IDOR in webhook deletion is classified as Critical.

Reconnaissance – Finding the Endpoint

During my testing on hackersatty.com, I followed a systematic process to identify the vulnerable endpoint:

Create an account (Account A) and explore available features.
Enable developer tools (browser DevTools or Burp Suite) to capture requests.
Create a webhook → noted down the request and observed an id parameter.
Saw that the webhook deletion was performed via:

POST /pr/settings/webhook/{uuid} X-Methodoverride: DELETE
Registered another account (Account B).
Repeated the same process to create a webhook, confirming that each webhook had a unique id.

This made me suspect that simply changing the id might allow cross-account access.

Step-by-Step Exploitation

Here’s how I reproduced the issue:

Account A creates a webhook → assigned id=15120.
Captured the deletion request:

POST /pr/settings/webhook/3c4320d4-cdaa-456a-94a3-c883c8821f27 X-Methodoverride: DELETE id=15120&csrfmiddlewaretoken=
Account B creates its own webhook → assigned id=15122.
Using Account B’s session, I replayed the captured deletion request.
Modified the request to target Account A’s webhook ID (id=15120).
Result: Account B successfully deleted Account A’s webhook.

Proof of Concept (PoC)

Request (Attacker – Account B deleting Account A’s webhook):

Response:

✔ Confirms that Account B deleted Account A’s webhook without authorization.

Reference: HackerOne’s Guide to Broken Access Control.

Proof of Concept showing how an attacker exploited a Critical IDOR Vulnerability.

Impact Analysis

The vulnerability directly affects integrity and availability of the application:

Any user can delete webhooks of others.
Attack requires no elevated privileges — just a free account.
Real-world consequences: service disruptions, broken integrations, loss of business data.

Severity Assessment (CVSS v3.1)

Attack Vector (AV): Network
Attack Complexity (AC): Low
Privileges Required (PR): Low
User Interaction (UI): None
Scope (S): Changed
Integrity (I): High
Availability (A): High

Score: 9.1 (Critical)

Recommendations to Fix Critical IDOR vulnerability

Enforce proper authorization checks – Verify that the user owns the webhook before allowing deletion.
Use Object-Level Access Control – Implement strict checks for every request modifying user resources.
Avoid predictable identifiers – Use UUIDs instead of sequential numeric IDs.

Final Thoughts

This case study demonstrates how a simple oversight in access control can lead to a Critical IDOR vulnerability.

By following a structured approach — from endpoint discovery, testing unique IDs, to replaying requests — I was able to identify a severe issue that impacts the core integrity and availability of the application.

For developers, the lesson is clear: never trust client-side input and always enforce authorization checks at the server level.

For security researchers, this highlights why IDOR remains one of the most dangerous yet common vulnerabilities.

Critical Unauthorized Access to Admin Pages via Vulnerable Endpoints – A Bug Bounty Case Study

hackersatty — Mon, 11 Aug 2025 19:40:23 +0000

About Me

My goal with this blog is to share real-world bug bounty experiences so other hunters can learn the techniques, tools, and mindset required to succeed — while staying ethical and responsible.

This case is about how I found critical admin endpoint vulnerabilities that allowed direct, unauthorized access to sensitive backend pages and data.

PAID ACCESS

Introduction – Why Admin Endpoints Are the Holy Grail for Hackers

In any web application, admin panels are like the control center — the place where the most sensitive operations happen:

User account management
Database queries
Application settings
Internal reporting tools

If attackers gain access to these pages without authentication, it’s game over for the application’s confidentiality, integrity, and availability.

Unfortunately, many organizations still expose these vulnerable endpoints to the public — sometimes unintentionally, sometimes through oversight in staging or legacy code.

In this case study, you’ll see exactly how :

Found a subdomain with unprotected admin endpoints.
Used OSINT and Google Dorks to locate hidden pages.
Manipulated parameters to extract sensitive information.
Reported the bug with proof of impact.

Step 1 – Recon: Finding the Target Subdomain

Recon is 80% of bug bounty hunting. If you skip it or rush through, you miss opportunities.

I started by identifying subdomains for the target using tools like:

Subfinder – For passive subdomain enumeration.
Amass – For deep reconnaissance.
crt.sh – Certificate transparency logs.

One subdomain caught my eye:

It wasn’t the main production domain, but it looked like a management interface.

Step 2 – Using Google Dorks to Find Entry Points

Google Dorks are an incredibly powerful way to find publicly exposed sensitive pages. Some of my favorites for admin discovery include:

Here’s what I did:

Locate Login/Admin Pages:
Found references to /TARGETED_QUICK_SEARCH_LIST and /STANDARD_QUERY_PAGE.
Identify JavaScript Files:
Using site:example.com filetype:js, I found multiple scripts containing API endpoint URLs.
Directory Enumeration:
Discovered /SCHEMA_BROWSE_POPUP endpoints from old code references.

These dorks worked because developers often hardcode endpoint paths in JavaScript or leave them accessible for internal testing — forgetting to restrict them later.

Step 3 – Vulnerable Endpoints Identified

I discovered three critical endpoints that lacked authentication:

1. TARGETED_QUICK_SEARCH_LIST

URL:

Risk:

Exposed template pages and internal metadata.
Allowed attackers to map system structure for future exploitation.

2. SCHEMA_BROWSE_POPUP

URL:

Risk:

Allowed manipulation of query parameters.
Potential to view and alter database schema.
Risk of unauthorized data insertion or modification.

3. STANDARD_QUERY_PAGE

URL:

Risk:

Let attackers retrieve internal sensitive data.
Could be exploited to dump system records.

Step 4 – Exploiting the Vulnerabilities (Ethically)

My approach was safe and non-destructive. Here’s how I tested without harming the system:

Access the Endpoints:
I directly navigated to each URL in my browser and observed responses.
Parameter Manipulation:
Tested parameters like:

&whereClause=1=1 &SearchQueryFormat=json &fieldName=id
Observed Responses:
- Sensitive metadata returned.
- Database field names exposed.
- Some queries returned internal-only records.

Step 5 – The Impact if Exploited by a Malicious Actor

If a real attacker had found these endpoints, they could have:

Bypassed Access Control: Gaining admin-level privileges without logging in.
Dumped Internal Data: Extracted customer records, internal files, or transaction logs.
Modified Records: Inserted malicious data or deleted important records.
Escalated Attacks: Used schema knowledge to launch SQL injection or privilege escalation attacks.

Step 6 – Why This Happened (Root Cause)

From my analysis, the root cause was:

Lack of Authentication: Endpoints assumed only internal staff would access them.
Legacy Code: Older admin tools left active without security updates.
Insufficient Security Review: No recent pentests had been done on admin modules.

Step 7 – Recommendations to Fix the Vulnerabilities

To prevent such issues, I suggested:

Strict Authentication: All admin endpoints must require session tokens or role-based access.
Endpoint Whitelisting: Restrict access to admin tools by IP.
Security in Depth: Validate input parameters and sanitize all queries.
Regular Security Audits: Include admin modules in every pentest.

Advanced Pro Tips for Finding Similar Bugs

Target Internal Functionality:
Look for keywords in JavaScript like admin, query, schema, panel.
Use Parameter Fuzzing:
Tools like FFUF or ParamSpider can uncover hidden GET/POST parameters.
Leverage Archive.org:
Old versions of the site might reveal outdated admin endpoints still active.
Combine OSINT with Burp Suite:
Once you find a candidate endpoint, proxy requests through Burp to manipulate and observe.

Final Thoughts

Finding unauthorized access to admin pages is like stumbling upon the keys to a locked building — except this one controls sensitive data for thousands of users.

This case reinforced for me that:

Even “hidden” endpoints are not safe if left online.
Admin tools must always be behind strong authentication.
Recon + patience = high impact bugs.

For every hunter reading this: don’t just look for obvious login pages — dig deeper for forgotten admin functions. They’re often where the gold lies.

How I Discovered an API Security Vulnerability in a Staging Environment (and What You Can Learn from It)

hackersatty — Mon, 11 Aug 2025 19:35:42 +0000

About Me

I’m Satyam Pawale, better known in the bug bounty world as @hackersatty. I started my bug hunting journey in 2024, and since then, I’ve been deeply passionate about uncovering security flaws that others might overlook. My style of hunting is a mix of manual creativity and technical precision, which often helps me find vulnerabilities in places others ignore.

My toolkit includes Burp Suite, Postman, custom scripts, and plenty of Google Dorks — but my main weapon is curiosity.

This blog is about how I found a critical API security vulnerability in a staging environment. I’ll take you through the exact step-by-step process, from spotting the Swagger UI to crafting the proof of concept. By the end, you’ll know how to:

Identify exposed APIs.
Test them safely.
Report them professionally for maximum impact.
PAID VULNERABILITIES

Introduction: Why APIs Are a Treasure Trove for Bug Hunters

When people talk about bug bounty hunting, they often think of XSS, SQLi, or CSRF. But in the modern web, APIs (Application Programming Interfaces) are one of the richest attack surfaces.

Why?

APIs handle direct requests from clients to backend systems.
Many APIs are under-secured because developers focus on functionality first.
Staging APIs are often less monitored, yet connected to production data.

In this case, I found an API Security Vulnerability that allowed account creation and password reset without authentication — a bug that could have led to serious damage if abused.

Step 1 – The Discovery: How I Stumbled Upon the Swagger UI

It all started when I was testing a program’s staging domain:

I wasn’t expecting much — many staging environments are dead. But I always follow this golden rule:

“If it’s in scope, it’s worth checking.”

I typed the URL in my browser, and to my surprise, instead of a blank page or 403 error, I saw:

Swagger UI — a graphical API documentation tool.

![Swagger UI Example Image Placeholder]

Now, Swagger UI is not bad in itself. In fact, it’s meant to help developers test their APIs easily. But in the wrong hands, it can become a recon goldmine.

Step 2 – Reading the API Endpoints Like a Map

When I opened the Swagger interface, I saw multiple endpoints under categories like:

/User/createUser
/User/resetPassword
/Application/createApplication

And here’s where my brain went:

Create User without authentication? Could be account spamming.
Reset Password without login? That’s instant account takeover.
Create Application? Might lead to abuse or resource exhaustion.

Step 3 – Testing the Create User Endpoint

Swagger allows you to send requests directly from its interface. I clicked on /User/createUser, and it showed me the parameters needed:

I filled in my test email and hit Execute.

To my surprise, I got a 200 OK response and a message saying “User created successfully” — all without logging in or providing an API key.

Step 4 – Realising the Impact

At this point, I knew I had found something serious. This API Security Vulnerability could allow:

Mass Account Creation:
An attacker could flood the system with fake accounts, possibly causing outages or messing with analytics.
Credential Stuffing Support:
If password reset endpoints were also unauthenticated, accounts could be hijacked.
Privilege Escalation:
If new accounts had unintended access, the attacker could directly reach admin areas.
Staging-to-Production Risk:
If staging shared databases with production (a common misconfiguration), this could directly compromise real users.

Step 5 – Expanding the Test

After creating a user, I checked other endpoints:

/User/resetPassword — It let me request password resets without logging in.
/Application/createApplication — Could create resources without checks.

This confirmed a lack of authentication across multiple critical endpoints.

Step 6 – How This Happens in Real Life

This is actually common in development:

Developers disable authentication in staging to make testing easier.
They forget to secure Swagger UI or block it from the public.
The staging environment is left online, sometimes even pointing to production data.

For attackers, this is a dream scenario.

Step 7 – Proof of Concept (PoC)

Here’s the exact POST request (with safe dummy data) that demonstrated the bug:

Response:

No authentication headers. No security checks.

Step 8 – Reporting the Bug

I wrote my report with the following sections:

Title: Unauthenticated API endpoints in staging environment allowing account creation and password reset.
Description: Explained what I found, how it could be abused, and potential business impact.
Steps to Reproduce: Detailed each action.
PoC: Included exact requests and responses.
Impact: Account creation spam, account takeover risk, possible production compromise.
Recommendations: Secure all endpoints, restrict Swagger UI, run regular API audits.

Step 9 – Company’s Fixes

The company responded quickly:

Authentication added to all sensitive endpoints.
Swagger UI restricted to internal access.
Security review conducted for all staging APIs.

Step 10 – Lessons You Can Apply

Here’s what I want you to remember:

Staging ≠ Safe — Always treat staging like production.
Swagger UI can leak critical endpoints.
Authentication is non-negotiable for sensitive APIs.
Automate recon to detect open Swagger UIs (hint: Shodan dork http.title:"Swagger UI").

Pro Tips for Finding API Bugs (Advanced)

Look for Keywords in JS Files:
api_key, token, auth often reveal endpoints.
Wayback Machine Recon:
Old API docs sometimes still work.
Check CORS Configurations:
Misconfigured CORS + open API = easy data theft.
Subdomain Permutations:
If staging-api exists, try dev-api, beta-api, qa-api.

Coming Soon on Hackersatty.com

For premium readers, I’ll be sharing:

Custom Google Dorks for API discovery
My personal API recon cheatsheet
Swagger UI exploitation methodology

Stay tuned — these will be members-only resources.

Final Thoughts

Finding this API Security Vulnerability was a huge learning moment. It proved that:

Curiosity pays off.
Staging environments can be as dangerous as production if left open.
Even simple tests can reveal high-impact bugs.

If you take one thing from this blog, let it be this:

“Never ignore staging. Sometimes, it’s the backdoor to the kingdom.”

Until next time — happy hunting! 😊

GraphQL Introspection Exposure: The 1 Hidden Blueprint That Could Undermine Your Entire Backend

hackersatty — Thu, 07 Aug 2025 15:39:44 +0000

About Me

I’m Satyam Pawale, better known in the bug bounty world as @hackersatty. As a dedicated security researcher, I specialize in uncovering complex misconfigurations and information disclosures—especially in web servers and directory services.

My toolkit includes Shodan, Burp Suite, custom scripts, and creative reconnaissance techniques.

In this article, I’ll guide you through the discovery and exploitation of a GraphQL introspection exposure vulnerability—so you can sharpen your bug bounty skills and better secure GraphQL-based APIs in production environments.

Introduction

Graphql introspection exposure is revolutionizing API design by allowing clients to request exactly what they need and nothing more. But with great flexibility comes great responsibility.

One of the most overlooked yet dangerous misconfigurations in GraphQL is leaving introspection enabled in production environments.

If attackers can query your schema structure without any authentication, they’re holding a blueprint of your backend, including sensitive endpoints, user object fields, and internal logic.

This post dives deep into how I discovered such an exposure on hackersattybugs.online/graphql, what I found inside, and how you can protect your APIs.

What is GraphQL Introspection?

GraphQL introspection is a self-documenting feature that allows developers and clients to ask a GraphQL server about its schema.

Common introspection queries can return:

All types and their fields
Available queries and mutations
Nested relationships and object structures
Custom directives and authentication mechanisms

This is great for development and tools like GraphiQL or Apollo Studio—but in production, it becomes a critical information disclosure vulnerability.

Why Introspection Shouldn’t Be Public

According to OWASP, unauthenticated introspection is equivalent to handing over your entire backend map to an attacker.

Even without credentials, attackers can:

Enumerate all API functionality
Identify sensitive objects (like User, Token, AdminPanel)
Prepare precise injection or manipulation attacks
Target misconfigured or undocumented endpoints

In many cases, introspection is the first step toward chaining bigger GraphQL exploits like:

Bypassing authorization
Performing privilege escalation
Triggering denial of service with complex nested queries

Discovery on hackersattybugs.online

While manually reviewing assets under the target scope, I came across a public configuration file that listed internal services and base URLs. One of them pointed to:

I loaded this endpoint in Postman and tried a basic introspection query without any authentication token.

To my surprise—it responded with the entire schema.

That’s when I knew this was a serious issue.

Step-by-Step Exploitation

Here’s how I confirmed the introspection exposure and explored the schema:

Step 1: Basic Schema Query

Response: A complete dump of all types, objects, and fields used in the backend.

Step 2: Discover Sensitive Types

I looked for common sensitive types like:

User
Session
AdminConfig
AccessToken
FileMetadata

And yes, I found all of them — completely unauthenticated.

Visual representation of a GraphQL introspection exposure discovered during a bug bounty assessment.

Step 3: Explore Available Queries

Using this payload:

I mapped every available graphql introspection exposure to clients.

Step 4: Look for Mutations

Then I checked mutations, which can be more dangerous since they change data:

Some interesting ones I discovered:

resetPassword
updateUser
createInternalToken
uploadFile
GraphQL introspection endpoint leaking backend schema in a real bug bounty case.

None of these required authentication to view.

Proof of Concept Payload

Here’s a final POC payload that anyone could run without a token:

Insert Screenshot Here

Alt text: GraphQL introspection query showing full schema exposure on hackersattybugs.online

What I Found Inside

Through this exposed schema, I was able to:

Discover all internal query names
Find user objects with fields like email, passwordHash, role, and lastLogin
Identify undocumented internal APIs for administrative operations
Learn about file metadata storage, possibly tied to S3 buckets or internal storage
Confirm that no authorization checks were triggered during introspection

Real-World Risks of Introspection Exposure

Leaving introspection open is like publishing your backend’s API docs to the entire internet.

Attackers can:

Reverse-engineer business logic
Target sensitive fields for injection or manipulation
Combine with SSRF or IDOR for deeper exploits
Abuse undocumented functionality for account takeover

Case Study:

PortSwigger’s GraphQL Academy shows how introspection can lead to unauthorized access to user data by revealing the structure of user-related queries.

How to Disable Introspection

Here’s how to disable introspection in your production GraphQL APIs, depending on the tech stack:

Apollo Server (Node.js)

GraphQL-Java (Spring Boot)

Express-GraphQL

Best Practices for Securing GraphQL APIs

To avoid introspection exposure and related attacks:

✅ Disable introspection in production
✅ Use depth and complexity limiting (e.g., graphql-depth-limit)
✅ Require authentication for all GraphQL endpoints
✅ Rate limit introspection queries
✅ Log and monitor query patterns for anomalies
✅ Avoid exposing sensitive fields in user objects (e.g., password, token)

Also, tools like LokiJS, GraphQL Armor, and Shield can add query-level protections to your stack.

Conclusion

graphql introspection exposure is an amazing tool for developers—but a dangerous threat in the hands of an attacker when left exposed.

In this case, I found an unauthenticated GraphQL endpoint that leaked the full schema and revealed sensitive internal operations.

The fix was simple: disable introspection in production.

If you’re running a bug bounty program or building secure APIs, this should be a mandatory checklist item.

Final Thoughts: Other Bug Bounty Blogs

GraphQL introspection exposure is just one example of how visibility can become a vulnerability.

With the right mindset and tools, bug bounty hunters can uncover massive flaws—without even needing authentication.

Remember: always stay within scope, validate what you find, and follow responsible disclosure guidelines.

Keep exploring. Keep hunting.

👉 Read more: How I Found Critical IDOR on Another Site

Apache server-info Exposure: 7-Step Deep Analysis of 403 Bypass & Internal Data Leak

hackersatty — Wed, 06 Aug 2025 10:41:22 +0000

About Me

I’m Satyam Pawale, better known in the bug bounty world as @hackersatty. As a dedicated security researcher, I specialize in uncovering complex misconfigurations and information disclosures—especially in web servers and directory services. My toolkit includes Shodan, Burp Suite, custom scripts, and creative reconnaissance techniques. In this article, I’ll guide you through the discovery and exploitation of an Apache server-info Exposure vulnerability, so you can sharpen your own bug bounty skills and help secure critical infrastructure.

2. Introduction

Apache server-info Exposure via a 403 bypass is a critical misconfiguration that can unveil deep internal infrastructure—ranging from module lists and environment variables .

3. What Are Apache server-info Exposure and server-status?

Apache server-info Exposure HTTP Server provides two administrative modules by default:

mod_info (/server-info): Reveals server configuration, loaded modules, compiled-in directives, and runtime parameters.
mod_status (/server-status): Displays live metrics—active requests, worker threads, bytes served, and uptime.

These endpoints are invaluable for administrators but must be strictly restricted (e.g., Require local or IP whitelisting). Left exposed, they become a treasure trove for attackers mapping infrastructure and identifying potential weaknesses.

4. Path Normalization & Bypass Fundamentals

Web servers normalize incoming paths to apply security rules uniformly. However, path normalization vulnerabilities arise when different components handle slashes inconsistently. A common bypass technique:

Expected Denial:

GET /server-info → 403 Forbidden
Bypass with Double Slash:

GET //server-info → 200 OK

Some security controls see //server-info as a different resource, failing to apply the 403 rule. By chaining encoding tricks or additional slashes, attackers slip past defenses.

5. Discovery of the Vulnerability

During routine reconnaissance with automated path enumeration tools, the following sequence occurred:

Initial Scan:
- Tool: Custom Python script iterating common admin paths.
- Found /server-status and /server-info returned 403 on standard requests.
Bypass Attempt:

curl -I http://target.example.com//server-status # HTTP/1.1 200 OK
Verification:
- Visiting //server-status in a browser displayed live server metrics.
- Similarly, //server-info rendered a full HTML page listing configuration details.

6. Technical Deep Dive: Double-Slash Bypass

6.1 Apache server-info Exposure Configuration Fragment

6.2 Path Normalization Steps

Raw Request: //server-info
Server Core: Treats leading double slash as a single slash.
Authorization Module: Matches against the original request URI (//server-info), skipping the rule that blocks external requests.

7. Proof of Concept (PoC) Walkthrough

Standard Access (Denied):

curl -i http://target.example.com/server-info # HTTP/1.1 403 Forbidden
Bypass Request (Allowed):

curl -i http://target.example.com//server-info # HTTP/1.1 200 OK
Retrieve Configuration:
- Visit http://target.example.com//server-info?config to list full conf.
- Use ?module=mod_authnz_ldap.c to see LDAP auth directives.
Confirm Sensitive Credentials:

AuthLDAPBindDN "uid=apacheauth,cn=Service Accounts,dc=example,dc=com" AuthLDAPBindPassword "P@ssw0rd!123"
Extract Private IP Ranges:
- - Over 100 lines of Require ip and Allow from with CIDR blocks like 10.0.0.0/8, 172.16.0.0/12.
Path normalization flow demonstrating double-slash bypass to elude 403 protections

8. Exposed Data & Internal Config Details

Through /server-info, the attacker gains:

LDAP Authentication Credentials:

AuthLDAPBindDN "uid=apacheauth,cn=Service Accounts,dc=example,dc=com" AuthLDAPBindPassword "P@ssw0rd!123"
Complete Module List:
- mod_ssl, mod_dav, mod_proxy, mod_authnz_ldap, mod_log_config, and more.
Environment Variables:
- SERVER_ROOT, HTTPD_ROOT, MPM_WORKER, and custom site-specific vars.
Private & Public IP Ranges:

10.0.0.0/8 172.16.0.0/12 192.168.0.0/16 203.0.113.5 198.51.100.22 …100+ entries
Runtime Hooks & VirtualHosts:
- Active mod_rewrite rules, virtual host configs, SSL cipher suites.

9. Impact Analysis

Confidentiality: Attackers see internal topologies, service accounts, and credentials.
Integrity: Knowledge of modules (e.g., mod_proxy) enables targeted CVE chaining.
Availability: Although read-only, leaked DoS‐vulnerable modules (e.g., mod_dav) could be exploited.
Compliance: Violates GDPR/PCI-DSS by exposing sensitive configuration and creds.
Attack Chains:
1. Use AuthLDAPBindDN to bind and enumerate directory.
2. Identify vulnerable modules (e.g., mod_authnz_ldap CVE-2018-1312).
3. Mount DoS or RCE attacks based on leaked module versions.

10. Mitigation & Hardening Strategies

Disable Unused Modules: Remove mod_info and mod_status from production.
Strict Access Controls:

Require ip 127.0.0.1 ::1
Path Normalization Fixes:
- Upgrade to Apache server-info Exposure ≥2.4.50 where double-slash handling is hardened.
- Add WAF rules to block // sequences.
Credential Security: Move LDAP bind credentials to a secure vault—never in plaintext.
Regular Audits & Pen Tests: Include bypass scenarios in automated scans.

11. Broader Security Lessons

Assume All Endpoints Are Public: Test with modified URIs (//, ..;, URL-encoding).
Defense in Depth: Even if modules are enabled, restrict them at the network perimeter.
Secret Management: Hardening is only as strong as your secret storage.
Monitor for Anomalies: Alert on requests containing suspicious patterns (//server-).

11. External Resources & Further Reading

13. Conclusion

The Apache server-info Exposure vulnerability demonstrates how a seemingly minor path-normalization issue can compromise an entire web server’s security posture. Attackers can bypass 403 restrictions, harvest sensitive credentials, map private networks, and identify vulnerable modules—paving the way for lateral movement and targeted exploits. By understanding the mechanics of double-slash bypass, continuously auditing server configurations, and enforcing strict access controls, organizations can defend against such high-impact misconfigurations.

14. Final Thoughts: Other Bug Bounty Blogs

Google Dorking remains a powerful reconnaissance technique in modern bug bounty methodology. With the right mindset and crafted queries, it’s possible to uncover sensitive files, misconfigurations, credentials, and more—without sending a single request to the server. This makes it especially useful for stealthy or scope-sensitive bug bounty programs.

Remember: always stay within scope, validate what you find, and follow responsible disclosure guidelines.

Keep exploring. Keep hunting.

LDAP Credential Exposure: 7-Step In-Depth Analysis of an Unauthenticated Data Leak

hackersatty — Wed, 06 Aug 2025 10:04:38 +0000

About Me

I’m Satyam Pawale, better known in the bug bounty world as @hackersatty. Over the years, I’ve honed my skills in uncovering critical vulnerabilities—ranging from API misconfigurations to directory-service exposures—by combining deep protocol expertise with inventive reconnaissance techniques. As a dedicated bug bounty hunter, I leverage tools like Shodan, Burp Suite, and custom scripts, alongside thoughtfully crafted Google Dorks, to find hidden endpoints and sensitive data leaks that others might miss.

In this article, I’ll share my journey discovering an unauthenticated LDAP credential exposure, demonstrate a step-by-step proof of concept, and explore real-world exploitation scenarios. My goal is to help you add powerful LDAP reconnaissance and exploitation strategies to your own bug bounty toolkit—so you can responsibly disclose impactful flaws and make the web a safer place.

1. Introduction

LDAP Credential Exposure occurs when unauthenticated API endpoints leak internal directory configuration data—including usernames, passwords, server addresses, and domain information—without any access control. Such a flaw can be exploited by attackers to bind directly to corporate directory services (e.g., Active Directory), perform directory enumeration, pivot laterally, and potentially escalate privileges to domain-wide compromise.

In this write-up, we examine a real bug bounty report against a fictionalized “AcmeSecure” environment—sanitizing all sensitive data—and deliver an exhaustive exploration that spans over 2,000 words. You’ll learn:

The history and purpose of LDAP Credenital Exposure
How LDAP Credential Exposure authentication works under the hood
Reconnaissance methods (e.g., Shodan queries)
Detailed virus-style API misconfiguration analysis
Step-by-step proof-of-concept exploitation
Multiple real-world attack scenarios and impact

2. LDAP Credenital Exposure : Origins and Purpose

LDAP (Lightweight Directory Access Protocol) originated in the early 1990s as a simplified alternative to the X.500 directory standard. Developed by Tim Howes and his team at the University of Michigan, LDAP quickly became the de-facto protocol for directory services.

Primary Role: Provide a structured, hierarchical directory for storing information about users, groups, computers, printers, and policies.
Data Model: Tree-structured entries (DNs—Distinguished Names) comprised of attributes (e.g., cn, uid, memberOf).
Common Implementations: OpenLDAP, Microsoft Active Directory, 389 Directory Server.

Figure: Sample LDAP directory hierarchy

3. How LDAP Authentication Works

At its core, LDAP Credenital Exposed authentication revolves around the Bind operation:

Anonymous Bind: No credentials; often restricted to public or read-only data.
Simple Bind: Provides a DN (e.g., cn=reader,dc=example,dc=com) and a password—sent in cleartext or Base64—unless protected by TLS.
SASL Bind: Supports stronger mechanisms (e.g., GSSAPI/Kerberos, DIGEST-MD5).

Key Insight: If an attacker obtains valid bind credentials, they can perform any operation permitted by that account’s ACLs—ranging from simple searches to full directory modifications.

4. Common LDAP Deployment Architectures

Organizations often deploy LDAP Credential Exposure in multi-tier configurations:

Primary Directory Servers: Authoritative storage, typically protected behind firewalls.
Read-Only Replicas (RODCs): Distributed for load balancing; still require authentication.
Edge-Facing Connectors: Application-specific proxies or API gateways that translate internal LDAP Credenital Exposure requests into RESTful calls.

When applications expose LDAP configuration via internal APIs—especially for dynamic authentication forms—they must ensure those endpoints enforce strict access controls. Unfortunately, misconfigurations are widespread.

Sanitized JSON snippet displaying LDAP server address, username, and Base64-encoded password returned by an unauthenticated API endpoint, demonstrating LDAP Credential Exposure

5. Reconnaissance Techniques

Before exploitation, attackers perform broad reconnaissance. Tools and methods include:

Shodan Searches:

hostname:"*.acmesecure.com" http.status:200

This filter returns all hosts under the target domain with port 80/443 open and responding with status 200.
SSL/TLS Metadata Analysis: Identifies certificate common names and SANs (subject alternative names) to map subdomains back to the organization.
Crawler Scripts: Automated scanners (e.g., waybackurls, gau) enumerate historical endpoints and parameter names.

By correlating subdomains and endpoints, attackers pinpoint candidate API paths that may leak configuration details.

6. Discovery of the Vulnerability

6.1 Initial Shodan Finding

One subdomain, api.acmesecure.com, responded to:

with a 200 OK and JSON payload. No Authorization header or session cookie was required.

6.2 Secondary Subdomain

A development instance, dev-acme.acmesecure.com, mirrored the production API stub:

This endpoint also returned identical JSON, confirming the flaw was systemic across environments, not just an overlooked corner of the network.

6.3 Raw API Response (Sanitized)

Username: ldap_reader_sample
Password (Base64): c2VjdXJlLXBhc3N3b3Jk
TLS Disabled: use_tls: false

7. Technical Deep Dive: API Misconfiguration

Why do misconfigurations like LDAP Credential Exposure happen? Common root causes:

Debug Endpoints Left Active: Development or testing code pushed to production without disabling admin/debug routes.
Lack of API Gateway Enforcement: Internal endpoints bypass gateway policies that would normally enforce authentication.
Monolithic Codebases: Shared libraries expose configuration via utility functions that assume internal trust.
Insufficient Code Reviews: Overlooked default routes or helper methods (e.g., getLdapConfig()) end up in production builds.

In our scenario, a REST-style endpoint—originally intended only for the application’s frontend login page—was never protected by middleware checks. The development build included it for convenience, and the deployment pipeline did not strip it out.

8. Proof of Concept (PoC) Walkthrough

Below is a step-by-step demonstration of how an attacker verifies and exploits the leak:

Unauthenticated Fetch:

curl -s https://api.acmesecure.com/api/v1/config/ldap | jq
Decode Base64 Password:

echo "c2VjdXJlLXBhc3N3b3Jk" | base64 -d # Outputs: secure-password
LDAP Bind Test (Simple Bind):

ldapsearch -x -H ldap://ldap.acme.local -D "cn=ldap_reader_sample,dc=corp,dc=acme,dc=local" \ -w secure-password -b "dc=corp,dc=acme,dc=local" "(objectClass=*)"

Successful results confirm live credentials.
Directory Enumeration:
Once bound, the attacker can query for sensitive entries:

ldapsearch -x -H ldap://ldap.acme.local -D "cn=ldap_reader_sample,..." \ -w secure-password -b "ou=IT,dc=corp,dc=acme,dc=local" "(uid=*)" cn mail
Pivoting to Other Services:
Many enterprise apps support LDAP-backed auth—so the attacker can log in to internal dashboards, SSO portals, or even password reset endpoints if sufficiently privileged.

9. Exploitation Scenarios and Lateral Movement

Once an attacker has valid LDAP credential Exposure, the attack paths multiply:

Active Directory Domain Compromise: If the service account has write permissions to userPassword, an attacker could escalate privileges by resetting critical accounts.
SSO Exploitation: Corporate Single Sign-On portals often use LDAP to authenticate users; stolen creds can allow direct access to web applications.
Email Harvesting: LDAP directories usually list user email addresses—valuable for phishing campaigns.
Credential Reuse Attacks: If the same password is used in other internal systems (e.g., Jenkins, Confluence), the risk compounds.
Pass-the-Hash Tactics: Even without plaintext passwords, an attacker might extract or relay NTLM hashes via Kerberos or NTLM protocols.

Real-World Outcome: At a Fortune 500 company, an attacker leveraged an exposed LDAP service account to enumerate all employees, then phished high-value targets with legitimate-looking internal URLs. Within 24 hours, they gained access to the CFO’s email and extracted financial forecasts.

10. Impact Analysis

An LDAP Credential Exposure vulnerability directly undermines:

Confidentiality: Exposure of usernames, passwords, and internal network structure.
Integrity: Unauthorized users binding with write privileges can alter directory entries.
Availability: An attacker could overload the LDAP server with malicious queries, causing denial-of-service.
Regulatory Compliance: Violations of GDPR, HIPAA, or SOX by exposing or modifying personal data.
Business Continuity: Critical business applications relying on LDAP may become compromised or untrusted.

Attackers with directory access can rapidly escalate to full domain compromise, exfiltrate sensitive data, or disrupt critical services.

11. Mitigation Overview

While this write-up focuses on deep-dive analysis, here’s a concise set of high-level recommendations:

Disable or Protect Debug Endpoints: Remove unused API routes in production.
Enforce Authentication & Authorization: Every internal endpoint must pass through an API gateway or middleware.
Adopt Secure Secret Storage: Move credentials to vaults (e.g., HashiCorp Vault) and never encode them in Base64.
Use Encrypted LDAP (LDAPS): Enforce TLS on directory binds (use_tls: true).
Implement Routine Pen Tests: Simulate reconnaissance and API fuzzing to catch exposures early.

12. Broader Lessons for Developers and SecOps

Shift Left on Security: Integrate automated security checks (e.g., SAST, DAST) into CI/CD pipelines.
Least Privilege Architecture: Service accounts should have only the minimal permissions they require.
Environment Parity: Keep test, staging, and production environments closely aligned in configuration—so that stripping debug routes in one doesn’t break another.
Comprehensive Inventory: Maintain an up-to-date map of all APIs and endpoints.
Monitoring & Alerting: Instrument critical routes with anomaly detection and alert on high-volume or unauthenticated calls.

13. External Resources & Further Reading

14. Conclusion

The LDAP Credential Exposure bug underscores how a single misconfigured endpoint can unravel an organization’s entire directory security posture. By examining each stage—from reconnaissance through exploitation and impact—we gain critical insights into both attacker methodologies and defender responsibilities.

❗ Take Action Today: Review your API surface, audit for any exposed directory configurations, and enforce robust access controls. Preventing an LDAP Credential Exposure could mean the difference between a contained incident and a full domain takeover.

Final Thoughts : Other Bug Bounty Blogs

Remember: always stay within scope, validate what you find, and follow responsible disclosure guidelines.

Keep exploring. Keep hunting.

25+ Google Dorks for Bug Bounty: Find Exposed Signatures, NDAs & Confidential Docs

hackersatty — Fri, 18 Jul 2025 10:46:28 +0000

By Satyam Pawale (@hackersatty)

About Me

Google Dorks Bug bounty is one of the most underrated skills in bug bounty hunting, yet it can lead to discovering high-severity and real-world vulnerabilities. I’m Satyam Pawale, widely known in the cybersecurity community as @hackersatty. As a passionate bug bounty hunter, I specialize in uncovering impactful bugs through creative reconnaissance techniques, especially using publicly available search engines like Google.

In this article, I’ll show you how to perform actionable bug bounty reconnaissance using Google Dorks Bug bounty to discover sensitive information like signature pages, NDAs, internal contracts, credentials, and other confidential files that are often unintentionally exposed on the web. Whether you’re a beginner or a seasoned hunter, you’ll learn how to add this powerful skill to your recon arsenal.

Let’s dive deep into the art of dorking for vulnerabilities.

Introduction

Google Dorking, also known as Google hacking, is an advanced search technique used to find exposed sensitive information through the use of tailored Google queries. For bug bounty hunters, Google Dorks Bug Bounty can serve as a gateway to discovering misconfigurations, exposed credentials, hidden portals, and even full documents that were never meant to be public.

I’m Satyam Pawale, widely known in the cybersecurity community as @hackersatty. As a passionate bug bounty hunter, I specialize in unearthing hidden vulnerabilities and valuable assets using methods that are both manual and automation-driven. Google Dorking is one of the oldest yet still highly effective methods for performing reconnaissance during bug bounty assessments.

In this article, we’ll walk through real-world examples, advanced Google Dork techniques, signature hunting, and tips to optimize your bug bounty recon. Whether you’re just starting out or already deep into bug bounty hunting, this guide will give you a fresh edge using Google search itself.

What is Google Dorking?

Google Dorking involves using special search operators to extract hidden information from public-facing websites. The idea is that Google indexes everything—sometimes more than it should—and by crafting specific queries, you can find pages that developers never intended to be indexed.

Focus Keyword: Google Dorks Bug Bounty

Why Use Google Dorks Bug Bounty?

Bug bounty is about scope, precision, and creativity. Often, the most critical bugs are buried in obscure or forgotten assets. Google Dorks Bug Bounty let you:

Find sensitive documents (PDF, XLSX, DOCX, TXT)
Uncover exposed login panels and admin consoles
Locate API keys or credentials in indexed pages
Discover configuration files or server info
Reveal staging environments and forgotten subdomains

Google Dorks extend your recon capabilities without the need for intrusive scanning.

Real-World Examples of Google Dorks Bug Bounty

1. Finding Exposed PDF Contracts

site:example.com filetype:pdf confidential

Use this to find PDF files with potentially sensitive contracts or agreements. Add intitle:"nda" to refine for NDAs.

site:example.com filetype:pdf intitle:nda

2. Discovering Passwords in GitHub Repos

site:github.com "api_key" "example.com"

Search GitHub for exposed API keys linked to your target.

3. Login Panel Discovery

site:example.com inurl:admin

site:example.com intitle:"login"

Great for finding potential login endpoints and bypassing public-facing dashboards.

4. Configuration Files Exposure

site:example.com ext:env | ext:yaml | ext:json

Many .env, .yaml, or .json files contain DB credentials and API tokens.

5. Index Pages and Directory Listings

site:example.com intitle:"index of /"

Use this to locate open directories or file servers.

Dork Crafting Approach

A smart bug bounty hunter understands how to craft dorks per asset type. Here’s how to approach it:

Step 1: Understand the Asset Type

Web apps: Look for login pages, dashboards
APIs: Look for documentation, keys, usage logs
Documents: PDFs, Excel sheets, TXT notes
Cloud Storage: Google Drive, AWS S3, Firebase

Step 2: Combine Keywords & Operators

Use logical operators:

site: to limit to a domain
filetype: to find specific formats
intitle: for keyword in title
inurl: for keyword in URL
cache: to view old or deleted versions

Step 3: Add Contextual Terms

Terms like “confidential”, “internal use only”, “do not share”, “restricted” often lead to gold mines.

site:example.com filetype:pdf "internal use only"

Advanced Signature Hunting Using Google Dorks

A powerful tactic is finding signature pages that contain document footers, author names, company templates, or timestamp structures. You can do this by:

Searching for Signature Markers

site:example.com filetype:pdf "Signature"

site:example.com filetype:pdf "Authorized Signatory"

These can reveal:

Contractual documents
Signed NDAs
Employment documents
Partnership forms

Sometimes these documents contain personal info, email IDs, full addresses, or contract clauses—providing strong reconnaissance material or even PII disclosures.

Example:

site:gov.in filetype:pdf "Signature"

Results may include tender documents with authorizing signatories and sensitive contact information.

Hunting Exposed IP Addresses

You can look for IP addresses by searching for headers or configuration exposures:

site:example.com intext:"X-Forwarded-For:"

site:example.com intext:"Server IP"

These dorks help you track misconfigured headers or identify internal infrastructure.

Explore the ultimate Google Dorks collection by Satyam Pawale (@hackersatty) on GitHub – crafted for bug bounty hunters and OSINT researchers to uncover hidden vulnerabilities and exposed data.

Practical Use in Bug Bounty Programs

Here’s how to leverage these discoveries:

Recon Stage

Use Google Dorks to discover undocumented subdomains and portals.
Validate sensitive file exposure.

Exploitation Stage

Analyze PDF/Excel documents for hardcoded credentials or PII.
Use configuration files to attempt login or privilege escalation.

Reporting Stage

Provide the full Dork used.
Include metadata (e.g., PDF timestamp, author info).
Explain potential impact (e.g., credential reuse, data leakage).

Tips to Avoid False Positives

Validate URLs using tools like curl, wget, or Burp Suite.
Use Google Cache to grab deleted or moved files.
Be cautious of decoy pages or honeypots.

Tools to Combine With Google Dorks

GitHub Dorking Tools: Use github-dork to automate GitHub leak discovery.
GoogleHackingDatabase: Explore pre-built dorks from Exploit-DB.
DorkScanner: Automates mass scanning with custom dorks.
Burp Suite: Validate endpoints or files.

Final Thoughts : Other Bug Bounty Blogs

Remember: always stay within scope, validate what you find, and follow responsible disclosure guidelines.

Keep exploring. Keep hunting.

Powerful $1000 Bug Bounty Guide: Discover Hidden Endpoints in JavaScript JS Files

hackersatty — Tue, 17 Jun 2025 18:23:56 +0000

Satyam Pawale (@hackersatty)

Introduction

If you’re a bug bounty hunter, JavaScript js files should be your best friends. They’re often overlooked but loaded with critical clues like hidden API endpoints, hardcoded secrets, and sensitive directories.

In this guide, I’ll walk you through how I use JavaScript file analysis to find real vulnerabilities and boost my bug bounty payouts. You’ll learn practical regex commands, tooling, and techniques to automate this process—even if you’re just getting started in bug bounty hunting.

Why JavaScript Files Matter

JavaScript (JS) files aren’t just for front-end logic. Developers often leave sensitive info like:

Internal API routes
Auth tokens or API keys
Endpoints not listed in Swagger docs
Logic that reveals hidden features

They can expose the entire backend structure, giving you a big advantage during recon.

Step 1: How to Read and Download JavaScript Files

You can find JavaScript files by opening browser dev tools, going to the Network tab, and filtering for .js. Copy their URLs or use tools like:

Other tools to automate JS collection:

waybackurls
gau
subjs

Step 2: Extract API Endpoints and Directories

JS files often contain relative or full API paths. Here’s a quick way to pull them:

Look for:

These could be unprotected routes or useful for further attacks like IDOR or SSRF.

Step 3: Detect HTTP Methods

APIs don’t only use GET. JS files show all HTTP verbs like POST, PUT, DELETE:

To extract them automatically:

Look for dynamic methods or hidden admin requests.

Step 4: Search for Hardcoded Secrets

Sometimes developers leave keys right inside the JS. Use this to find them:

What you might find:

Firebase keys
AWS credentials
JWT secrets
Stripe tokens

Also try searching for these keywords:

Step 5: Automate the Entire Process

Tools That Help You Hunt Faster:

LinkFinder – Extract endpoints from JS
SecretFinder – Find secrets, keys, and tokens
JSleak – Powerful tool for JS recon
catjs – Highly customizable regex-based JS analyzer

Example Workflow:

Step 6: Fuzzing Discovered Endpoints

Once you’ve collected endpoints from JS, test them using:

ffuf for directory fuzzing
Burp Intruder for parameter injection
Nuclei for known vulnerabilities

You might discover:

Unauthenticated access
Broken access control (IDOR)
Debug or dev-only APIs
Misconfigured routes

Step 7: Analyze JavaScript for Parameter Names and Sensitive Variables

When developers write frontend JavaScript, they often pass user input or internal values as parameters to API calls or functions. These variable names can help you craft smarter attacks like:

Parameter pollution
IDOR
Open redirect
XSS

🔍 What to Look For:

Look for variable names in JS code that might indicate sensitive input, such as:

These are goldmines — especially when passed to backend APIs or appended to URLs.

🛠️ Regex to Extract Suspect Variables:

Run this in your downloaded JS files:

You’ll often catch lines like:

🎯 Why This Matters for Bug Bounty

Once you know the exact parameter names being used, you can test them with tools like:

Burp Repeater – Manually inject or override params
ffuf or ParamSpider – Fuzz for parameter-based bugs
Arjun – Auto-discovers hidden HTTP parameters

For example:

You might discover parameters like:

admin=true
access=internal
debug=1

All because the JS revealed them!

Best Practices

Always prettify JavaScript code for better readability (jsbeautifier, online formatters)
Respect robots.txt and terms of service
Don’t report fake issues—test thoroughly and reproduce
Use clear write-ups with request/response, impact, and remediation

Bonus: Real Bug Bounty Report from JavaScript Analysis

I once found a hidden admin dashboard /admin/internal/config from a JS file. No auth, full access to user records. Reported it → $1000 payout.

Tools used:

Burp Suite
LinkFinder
Manual JS review

Conclusion

If you want to be a successful bug bounty hunter, you must master JavaScript analysis. It’s one of the highest ROI areas in recon. Start small—analyze one file, extract endpoints, look for secrets, automate what works.

Stick with it. I started just a year ago, and now I consistently find high-severity bugs through JS analysis.

Keywords in This Article:

read javascript file
javascript js file
bug bounty hunter
bug bounty reports
learn bug bounty hunting
bug bounty course
bug bounty writeup
bug bounty tools
bug bounty for beginners
javascript file analysis

Internal Links

My Internal Blogs

External Resources:

Critical Security Vulnerability: Unauthenticated Access to /shipments/deleted 1 Endpoint Allows Irreversible Data Deletion

hackersatty — Mon, 02 Jun 2025 10:20:05 +0000

By Satyam Pawale (@hackersatty)

About Me

Unauthenticated API Endpoint

Hello all! My name is Satyam Pawale, or simply @hackersatty within the bug bounty space. I started my cybersecurity journey in 2024, and since then, I have committed to finding and reporting responsibly vulnerabilities that might otherwise lead to significant harm.

In this blog, I’d like to talk about a real-world vulnerability that I found—a non-authenticated API endpoint where sensitive shipping records could be deleted with no type of login. No credentials, no auth, just one unauthenticated call that could delete business-critical information.

Introduction: Why APIs Require Lock and Key

Unauthenticated API Endpoint APIs drive nearly everything in the background of today’s web applications—showing product lists, handling user accounts. The same capability can turn into a security nightmare if APIs are left unguarded.

While I was excavating a logistics platform (xyz.com), I uncovered an alarming problem: an open Unauthenticated API Endpoint that supported unauthenticated deletion of shipment records. No login was necessary, no API key verification—just call the endpoint, and data disappeared.

A dive into how I discovered it, why it’s risky, and what needs to be done to address such a problem.

Vulnerability Overview

Let’s break it down. Here’s what went wrong:

A POST endpoint at /shipments/deleted was open to everyone.
There was no authentication required.
There were no user permission checks (RBAC).
The endpoint carried out destructive actions with no validation.

This is an age-old example of an unauthenticated API endpoint with the potential to have severe business implications.

Technical Breakdown

Affected Endpoint

https://xyz.com/shipments/deleted

What Was Going On

The endpoint was accepting POST requests.
No session or login were needed.
No user roles were validated.
Anyone who had this URL could delete their shipment data.

To summarize: anyone could open a terminal, enter one command, and begin deleting records.

Proof of Concept (PoC)

That’s it. This one-liner might erase shipment records in production. The fact that an API action with such great power was not authenticated is terrifying.

Example of a critical security flaw where an unauthenticated API endpoint enables data deletion without login, exposing shipment data to public access.

Exploit Impact: What Could Go Wrong?

Let’s dive into the impact in more detail:

Unauthorized Data Deletion
No login necessary. Anyone might delete.
No Recovery
The deletion was irreversible. Once a shipment was deleted, there was no “undo.”
Automation Threat
Attackers would be able to automate this call with scripts and destroy whole datasets in minutes.
Business Disruption
The platform might lose order tracking, shipment history, and business continuity.
Legal Risk
Irreversible data loss without logs might breach data protection regulations such as GDPR.

This problem didn’t just impact data—it could bring operations to a standstill and hurt customers.

Reproducing the Vulnerability

Here’s what I tested:

Open terminal
Enter the curl command mentioned above
Shipment records were wiped out in an instant without login or authentication

I also tested with a browser-based tool and validated the same outcome.

Why This Happens: Missing Security Layers

Several developers assume that their APIs will only be requested from legitimate clients. But this is an unfounded assumption:

Security by Obscurity doesn’t work: If an endpoint is exposed, someone will discover it.
Forgetting Auth Checks: Developers, sometimes in staging or testing, disable auth. It should never happen in production.

Recommended Fixes

Require Authentication for All Sensitive APIs
Authenticate with tokens (JWT, OAuth2) or API keys.
Use Role-Based Access Control (RBAC)
Ensure only users of the appropriate role (e.g., admin) can delete records.
Include Request Validation
Validate inputs, check CSRF tokens, and include confirmation dialogues for destructive operations.
Log Everything
Log the who, what, and when for endpoint access. Add exceptions for user IPs, timestamps, and action types.
Remove Public Access
Don’t leave sensitive endpoints open to public internet exposure. Utilize API Gateways, WAFs, or IP whitelisting.
Monitor and Alert
Implement alerts for suspicious API access patterns, such as bulk deletion attempts.

Responsible Disclosure Timeline

Date	Event
Oct 11, 2024	Report from researcher submitted
Oct 17, 2024	Security team requested additional information
Oct 18, 2024	Clarification and PoC provided
Oct 22, 2024	Vulnerability acknowledged and triaged
Nov 12, 2024	Retest showed the issue persisted
Dec 3, 2024	Patch deployed and verified as fixed

Lessons for Security Researchers

Check Every Endpoint
Even small or outdated endpoints may still be active and vulnerable.
JavaScript is a Goldmine
Inspect JavaScript files for references to internal API paths.
Test Without Login
Before logging in, try common endpoints unauthenticated. It may lead to surprising results.
Combine Tools + Manual Testing
Use Burp Suite, FFUF, or bespoke scripts, but check manually.
Follow Up
Retest always after reporting to make sure patches have been applied.

Final Thoughts

This wasn’t some high-fancy zero-day or intricate chain of exploits. It was a humble but ruinous flaw—an unauthenticated API endpoint that supported destructive operations.

The solution? Simple too. But finding it required diligent testing, attention to detail, and inquisitiveness.

For coders, the message is clear: always lock down your Unauthenticated API Endpoint . Don’t let bad guys wreak havoc. For researchers, never take an endpoint at face value—test it.

Security doesn’t need to be complex. But it needs to be intentional.

Let’s create secure apps, bug by bug.

Other Internal Blog Link:

Hackersatty

Resources:

Final Thoughts: Keep Hunting, Keep Learning

This was one of my earliest critical bug bounty finds and taught me that Unauthenticated API Endpoint are one of the most vulnerable attack surfaces today. With tools like Swagger, Postman, and Burp Suite at your disposal, you don’t need to brute force—just observe and test logically.

🔍Unauthenticated API Endpoint is more than headers and tokens—it’s about understanding how developers structure access and how attackers think.

If you found this write-up helpful, feel free to connect with me on LinkedIn or follow my work on Twitter.

Until next time, stay curious and stay secure! 🔐

Bug Bounty Blogs – Hackersatty – Learn Ethical Hacking, Bug Bounty, and Cybersecurity Tips

How I Abused a Race Condition to Create Duplicate Notification Records (sanitized)

About Me

Summary

Overview

Vulnerability —

Why this matters

Best reproduction scenario

Sanitized PoC — Request (GraphQL mutation)

Sanitized PoC — Typical Response (each concurrent request returns same success)

Exactly how the race condition happens (technical explanation)

Techniques & tools used (methodology)

Concrete fixes (prioritized)

1) Enforce uniqueness at the database layer (recommended)

2) Use atomic upsert (ON CONFLICT)

3) Server-side canonicalization

4) Optional: idempotency token

5) Transactional locking / advisory locks

Pseudocode — atomic upsert (preferred)

Detection & monitoring recommendations

Safe remediation rollout plan

Dedupe migration (safe approach)

Example automated reproduction script (sanitized, Python async)

Short checklist to verify the fix in staging

Summary —

Final Thoughts

5 Steps to Exploit a Critical IDOR Vulnerability in Webhook Deletion

Critical IDOR Vulnerability in Webhook Deletion – A Real-World Exploitation Guide

What is an IDOR Vulnerability?

Why IDOR in Webhook Deletion is Critical

Reconnaissance – Finding the Endpoint

Step-by-Step Exploitation

Proof of Concept (PoC)

Impact Analysis

Severity Assessment (CVSS v3.1)

Recommendations to Fix Critical IDOR vulnerability

Final Thoughts

Critical Unauthorized Access to Admin Pages via Vulnerable Endpoints – A Bug Bounty Case Study

About Me

Introduction – Why Admin Endpoints Are the Holy Grail for Hackers

Step 1 – Recon: Finding the Target Subdomain

Step 2 – Using Google Dorks to Find Entry Points

Step 3 – Vulnerable Endpoints Identified

1. TARGETED_QUICK_SEARCH_LIST

2. SCHEMA_BROWSE_POPUP

3. STANDARD_QUERY_PAGE

Step 4 – Exploiting the Vulnerabilities (Ethically)

Step 5 – The Impact if Exploited by a Malicious Actor

Step 6 – Why This Happened (Root Cause)

Step 7 – Recommendations to Fix the Vulnerabilities

Advanced Pro Tips for Finding Similar Bugs

Final Thoughts

How I Discovered an API Security Vulnerability in a Staging Environment (and What You Can Learn from It)

About Me

PAID VULNERABILITIES

Introduction: Why APIs Are a Treasure Trove for Bug Hunters

Step 1 – The Discovery: How I Stumbled Upon the Swagger UI

Step 2 – Reading the API Endpoints Like a Map

Step 3 – Testing the Create User Endpoint

Step 4 – Realising the Impact

Step 5 – Expanding the Test

Step 6 – How This Happens in Real Life

Step 7 – Proof of Concept (PoC)

Step 8 – Reporting the Bug

Step 9 – Company’s Fixes

Step 10 – Lessons You Can Apply

Pro Tips for Finding API Bugs (Advanced)

Coming Soon on Hackersatty.com

Final Thoughts

GraphQL Introspection Exposure: The 1 Hidden Blueprint That Could Undermine Your Entire Backend

About Me

Introduction

What is GraphQL Introspection?

Common introspection queries can return:

Why Introspection Shouldn’t Be Public

Discovery on hackersattybugs.online

Step-by-Step Exploitation

Step 1: Basic Schema Query

Step 2: Discover Sensitive Types

Step 3: Explore Available Queries

2) Use atomic upsert (`ON CONFLICT`)