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Introduction:
Manual bug bounty hunting remains a high-return skill even in an era of automated scanners. By understanding application logic and testing each functionality by hand, a security researcher turned 31 submissions into $1,830 in payouts over a single month—proving that deep technical insight often outperforms brute-force automation. This article extracts the methodology behind that success and delivers a hands-on guide to replicating it using Burp Suite, manual payload crafting, and targeted vulnerability exploitation.
Learning Objectives:
- Apply manual testing workflows with Burp Suite to discover business logic flaws and input validation bugs.
- Differentiate between false positives, duplicates, and accepted reports to maximize payout efficiency.
- Execute step‑by‑step command‑line and GUI techniques for API security, cloud misconfigurations, and privilege escalation.
You Should Know:
- Replicating the Manual Bug Bounty Workflow with Burp Suite
The post’s author submitted 31 reports using only Burp Suite and a browser—no scanners. This section explains how to set up that environment and manually hunt for common, high‑impact bugs.
Step‑by‑step guide – Manual recon and testing:
- Intercept and log all traffic: Configure Burp Suite’s proxy (127.0.0.1:8080) and install its CA certificate in your browser. Turn on “Intercept” only for specific tests; otherwise, use “Passive scanning” to avoid noise.
- Map the target: Right-click the target’s root in Burp’s Target tab → “Spider this host” (or manually browse while “Record” is on). Save the site map as a baseline.
- Identify dynamic parameters: Look for
?id=,?user=,?file=, `?redirect=` in URLs and POST bodies. Use Burp’s “Param Miner” extension (BApp store) to guess hidden parameters. - Test each functionality:
- For each form, submit legitimate data, then replay the request with mutated values (e.g., add `’` or `”` to test SQLi).
- For file uploads, try
.php.jpg,shell.jsp, or SVG with embedded script. - For authentication, attempt parameter pollution (
user=admin&user=guest). - Track findings in a spreadsheet (as the author did) with columns: Endpoint, Payload, Expected/Actual behavior, Severity, Status.
Linux command to automate request replay (using `curl` with Burp proxy):
curl -x http://127.0.0.1:8080 -H "User-Agent: manual-hunter" -d "username=admin' OR '1'='1&password=test" http://target.com/login
Windows PowerShell equivalent:
$proxy = [System.Net.WebRequest]::GetSystemWebProxy()
$req = [System.Net.WebRequest]::Create("http://target.com/login")
$req.Proxy = $proxy
$req.Method = "POST"
$req.ContentType = "application/x-www-form-urlencoded"
$body = "username=admin' OR '1'='1&password=test"
$req.ContentLength = $body.Length
$writer = New-Object System.IO.StreamWriter($req.GetRequestStream())
$writer.Write($body)
$writer.Close()
$resp = $req.GetResponse()
Why this works: Manual testing catches logic flaws that automated scanners miss (e.g., race conditions, broken object level authorization). The author’s 14 accepted reports likely included such issues.
- Triaging Your Own Reports: From Rejected to Paid
Out of 31 submissions, 4 were rejected, 11 duplicates, and 3 informational. Learning to filter before submission saves time and increases credibility.
Step‑by‑step guide to pre‑submission validation:
- Reproduce the bug in three different environments (e.g., different browsers, incognito, different user roles). If it fails in any, it may be a false positive.
- Check for duplicates using the program’s “Activity” feed or search for keywords from your finding. If you see a similar report from another hunter, document why yours is different (e.g., different endpoint or impact).
- Classify severity using CVSS v3.1: calculate base score. Informational issues (e.g., missing security headers without exploitability) should be documented but not submitted as paid reports.
- Write a concise report:
- Step‑by‑step reproduction with screenshots and raw HTTP requests/responses.
- Impact statement: “An attacker could escalate privileges to admin without authentication.”
- Suggested fix: code patch or configuration change.
Command to check for duplicate open ports (to confirm you aren’t wasting time on known assets):
nmap -sV -p- --open target.com | tee scan_results.txt
Compare with past reports from the program’s disclosure archive (if public). If the same service version appears in previous accepted reports, shift focus.
3. Manual Payload Crafting for High‑Value Vulnerabilities
The author found 31 bugs without automation. Here are three manual payload sets that consistently yield paid reports.
SQL Injection (time‑based):
' OR SLEEP(5)-- ' UNION SELECT @@version,2,3-- -
Test each parameter by replacing its value. In Burp Repeater, send the request and observe response time.
Cross‑Site Scripting (context‑aware):
<img src=x onerror=alert(document.cookie)> < svg/onload=alert(1)> javascript:alert(1)//?something=</script><script>alert(1)</script>
Use Burp’s “Intruder” with a payload list of 50 XSS vectors to systematically test each reflection point.
IDOR (Insecure Direct Object Reference):
Change a numeric ID in a URL or JSON body:
Original: GET /api/user/12345/profile Modified: GET /api/user/12346/profile
Also try `../12346` or ?user_id=12346. If you see another user’s data, that’s a paid‑level finding.
4. API Security Testing Without Scanners
Modern web apps rely heavily on APIs. Manual testing of REST and GraphQL endpoints is a goldmine.
Step‑by‑step:
- Capture API calls in Burp Proxy while using the target app. Look for
/api/v1/,/graphql,/swagger,/openapi.json. - Test for broken object level authorization (BOLA) – for each API endpoint, replace object IDs with IDs from a different test account.
- Test for mass assignment – add unexpected parameters like `”is_admin”:true` or `”role”:”superuser”` to POST/PUT requests.
- Test for GraphQL introspection (if allowed). Send:
{__schema{types{name,fields{name}}}}If introspection is enabled, you can dump the entire schema and find hidden mutations.
Linux command to fuzz API endpoints (using `ffuf`):
ffuf -u http://target.com/api/v1/FUZZ -w /usr/share/wordlists/dirb/common.txt -x http://127.0.0.1:8080
This routes through Burp so you can analyze responses.
5. Cloud Hardening and Misconfiguration Detection
Many bug bounty programs involve cloud assets (S3 buckets, Azure Blob, Lambda functions). Manual checks often reveal misconfigurations.
Check for public S3 buckets:
aws s3 ls s3://target-bucket-name --no-sign-request
If it lists files without credentials, that’s a critical finding.
Check for open Azure Blob containers:
az storage container list --account-name targetaccount --auth-mode login
But first, attempt anonymous access using `curl`:
curl https://targetaccount.blob.core.windows.net/container-name?restype=container&comp=list
Check for exposed .git or .env files:
curl -k https://target.com/.git/config curl -k https://target.com/.env
If returned, you can download the entire repo or grab secrets.
Mitigation advice for defenders: Block public access at the bucket level, enable MFA delete, and rotate keys every 90 days.
6. Vulnerability Exploitation and Mitigation – Race Conditions
Race conditions are classic manual bugs. The author likely exploited them in payment or voting functionalities.
Step‑by‑step exploitation with Burp Suite:
- Find an endpoint that changes state (e.g.,
POST /redeem_coupon). - Send the request to Intruder → “Null payloads” → set “Number of threads” to 20.
- Also send the same request to Repeater, then use “Send group” (parallel) with 10 tabs.
- Observe if a coupon can be redeemed more than once or a vote counted multiple times.
Python script for manual race condition testing:
import threading
import requests
url = "https://target.com/api/redeem"
payload = {"coupon": "SAVE20"}
def attack():
r = requests.post(url, json=payload, proxies={"http":"http://127.0.0.1:8080"})
print(r.status_code, r.text)
threads = []
for _ in range(30):
t = threading.Thread(target=attack)
t.start()
threads.append(t)
for t in threads:
t.join()
Mitigation: Use database row locks, idempotency keys, or atomic transactions.
7. Training Courses and Continuous Learning
To achieve 57 certifications (as Tony Moukbel’s profile mentions) and succeed in manual bug bounty, structured training is essential. Recommended free and paid resources:
- PortSwigger Web Security Academy (free) – Labs for every vulnerability class, directly applicable to manual testing.
- PentesterLab – Hands-on exercises for Burp Suite mastery.
- TCM Security – Practical Bug Bounty (paid) – Focuses on manual methodology.
- Hacker101 (free) – Video lessons and CTF-style challenges.
Linux command to set up a local vulnerable lab (for safe practice):
docker pull vulnerables/web-dvwa docker run -d -p 80:80 vulnerables/web-dvwa
Then browse to `http://localhost` and start testing with Burp.
Windows command (using Docker Desktop):
docker run -d -p 80:80 vulnerables/web-dvwa
What Undercode Say:
- Manual testing still dominates for logic bugs – Automation misses context, and the author’s $1,830 from 11 paid reports proves that deep functional understanding pays off.
- Quality over quantity – 14 accepted reports out of 31 (45% acceptance) is high; many hunters submit 100+ automated issues for less payout. Focus on reproducible, high‑impact findings.
Analysis: The bug bounty landscape is shifting toward complex applications where scanners fail. Attackers who master Burp Suite, understand API flows, and think like developers will consistently outperform script‑kiddie automation. Defenders must adopt the same mindset: manual code review, threat modeling, and targeted penetration testing remain the most effective ways to find critical vulnerabilities. The post’s raw numbers—11 paid, 3 informational—highlight a realistic success curve: expect duplicates and rejections, but each accepted report builds reputation and skill.
Prediction:
As AI‑powered scanners commoditize low‑hanging fruit, manual bug bounty hunting will bifurcate into two tiers: automated volume hunters (earning $10–$50 per bug) and elite manual hunters (earning $1,000+ per logic flaw). Platforms will introduce “manual‑only” leaderboards and higher bounties for business logic vulnerabilities. Over the next 18 months, we expect a 40% increase in manual testing training courses and a corresponding rise in acceptance criteria that explicitly reject scanner‑generated reports.
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IT/Security Reporter URL:
Reported By: Josekutty Kunnelthazhe – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
