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Introduction:
In the dynamic world of bug bounty hunting, a fixation on the latest headline-grabbing vulnerabilities like react2shell can often distract from the foundational flaws that consistently expose organizations to severe risk. As highlighted by a seasoned practitioner’s recent success, Broken Access Control remains the undisputed king of application security failures, holding the 1 spot in the OWASP Top Ten 2025. This article deconstructs the methodology behind profitably hunting these critical flaws, moving beyond theory into practical, actionable techniques for identifying and exploiting authorization failures across modern web architectures.
Learning Objectives:
- Understand why Broken Access Control is perennially OWASP’s 1 risk and how to systematically test for it.
- Learn practical, hands-on techniques for identifying Insecure Direct Object References (IDOR), privilege escalation, and misconfigured JWT/API endpoints.
- Develop a methodology to integrate automated reconnaissance with manual, deep-dive application logic testing for maximum bounty yield.
You Should Know:
- Manual Testing for Horizontal and Vertical Privilege Escalation
The core of access control testing lies in manipulating the application’s state to perform actions as another user (horizontal) or with higher privileges (vertical). This requires a deep understanding of session management, user roles, and how object identifiers are handled.
Step‑by‑step guide:
Step 1: Map the application. Create two or more user accounts with different privilege levels (e.g., user_a, user_b, admin). Use browser developer tools or a proxy like Burp Suite to record all requests.
Step 2: Analyze identifiers. Look for parameters like user_id, account_id, doc_id, `uuid` in URLs, request bodies, and API responses. Note any session tokens or JWT.
Step 3: Test Horizontal Escalation. While authenticated as user_a, capture a request to access a resource (e.g., GET /api/v1/invoices/1234). Change the identifier (e.g., to 1235) or replace your session token/JWT with one captured from user_b‘s session. Submit the request. Success means you can access another user’s data.
Linux/curl Example: `curl -H “Authorization: Bearer
Step 4: Test Vertical Escalation. Using a low-privilege account (user_a), access administrative endpoints by modifying the request method or path (e.g., `POST /admin/deleteUser` instead of GET /user/profile). Attempt to access roles parameters in JWT.
JWT Tampering Command (using jwt_tool): `python3 jwt_tool.py
2. Automating the Discovery of IDOR and Parameter-Based Vulnerabilities
While manual testing is crucial, automation can help scour applications for potential entry points.
Step‑by‑step guide:
Step 1: Spider the application with `Burp Suite` or `OWASP ZAP` to catalogue all endpoints.
Step 2: Use tools to fuzz parameters. `ffuf` is excellent for discovering hidden resources and testing IDOR.
Command Example (Discovering IDs): `ffuf -w /usr/share/wordlists/seclists/Discovery/Web-Content/numbers.txt -u https://target.com/api/user/FUZZ/profile -fs 0` This fuzzes for numeric user IDs.
Step 3: Automate testing with custom scripts. A Python script can iterate through a list of identified object references, swapping session cookies to test for access violations systematically.
3. Exploiting JWT and API Authorization Flaws
Modern APIs rely heavily on tokens like JWTs. Misconfiguration is common.
Step 1: Decode the JWT (using `jwt.io` or the command line) to inspect its payload. Look for `alg: none` vulnerabilities, weak signatures, or exposed `kid` headers that can be manipulated.
Decode JWT in Linux: `echo “
Step 2: Test for signature bypass. If the app uses a weak secret, use `hashcat` to crack it.
Command: `hashcat -m 16500 /usr/share/wordlists/rockyou.txt`
Step 3: Test GraphQL or REST API endpoints for introspection flaws or missing access controls on mutations/queries that should be restricted.
- Cloud Storage and IAM Misconfigurations (AWS S3 Example)
Broken Access Control extends to cloud infrastructure, particularly misconfigured storage buckets and Identity and Access Management (IAM) policies.
Step 1: Discover potential S3 bucket names. Use tools like `s3scanner` or wordlists combined with permutations of the target’s name (acme-dev-storage,acme-backups).
Step 2: Check permissions. Use the AWS CLI if you have some credentials, or simply attempt anonymous access.
Anonymous Read Check: `aws s3 ls s3://bucket-name/ –no-sign-request`
Anonymous Write Check: `echo “test” > test.txt && aws s3 cp test.txt s3://bucket-name/ –no-sign-request`
Step 3: Analyze IAM policies attached to cloud functions (Lambda) or EC2 instances for overly permissive `”Effect”: “Allow”` and `”Resource”: “”` statements.
5. Mitigation and Secure Coding Practices
Finding flaws is half the battle; understanding fixes is critical for effective communication in bug reports and for defenders.
Step 1: Implement access control checks on every request. Use a central authorization middleware.
Step 2: Use indirect object references. Map a user-provided identifier (e.g., file=1) to an internal value via a stored map on the server, avoiding direct database key exposure.
Step 3: Adopt a zero-trust model. Default deny all. Enforce role-based access control (RBAC) or attribute-based access control (ABAC) policies consistently across the app and API layers.
Step 4: For cloud, follow the principle of least privilege. S3 buckets should never have `”Principal”: “”` with "Action": "s3:GetObject". IAM policies must be scoped to specific resources and conditions.
What Undercode Say:
- Fundamentals Are a Force Multiplier: While advanced exploits have their place, a deep, systematic understanding of core vulnerability classes like Broken Access Control provides a sustainable and high-yield hunting strategy. It is the bedrock upon which reliable security assessment is built.
- Context Over Tools: Success is not about the number of tools run, but about the depth of engagement with the application’s unique business logic and authorization workflow. Manual verification and logic manipulation trump raw automated output.
Analysis:
Kaushik Roy’s post underscores a critical divergence in the security community: the chase for novel, complex vulnerabilities versus the mastery of pervasive, fundamental flaws. His consistent bounty success from Broken Access Control is a data-driven argument for depth over breadth. This vulnerability’s top OWASP ranking is no accident; it stems from the complexity of implementing correct authorization across distributed microservices, APIs, and hybrid cloud environments. Hunters who develop a meticulous, patient approach to testing state transitions, object referencing, and token validation will find vulnerabilities that automated scanners consistently miss. This methodology not only yields bounties but also addresses the most significant real-world risk facing applications today.
Prediction:
The focus on Broken Access Control will intensify, driven by the expansion of API-first architectures and complex SaaS permission models. We predict a rise in AI-assisted tools designed not to replace manual hunters, but to better map application state and user role relationships, highlighting potential authorization conflict points for human validation. Simultaneously, the adoption of standardized authorization frameworks (e.g., OpenFGA, Zenbase) will grow, but misconfiguration and logic flaws in their implementation will become a new, high-value attack surface for savvy hunters. The arms race will shift from finding endpoints to intelligently reasoning about relationships and permissions within an app’s ecosystem.
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Reported By: Kaushikroy4 Bugcword – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
