Create With AI – Detecting Missing Rate Limiting on Login Endpoints
S4E.io
Enterprise-grade Automation with Pentester-level Flexibility
This library showcases real examples of how security teams use S4E Create with AI to save time, reduce manual effort, and strengthen their defenses.Unlike traditional scanners that limit users to predefined checks, S4E Create with AI gives complete flexibility. You describe what you need, and the AI builds and runs it instantly. This allows teams to automate the exact tests they want instead of being restricted to what the product designer imagined.
Detecting Missing Rate Limiting on Login Endpoints
Problem
Many applications still lack proper rate limiting on login or API endpoints. Without limits, attackers can perform brute-force or credential stuffing attacks to gain unauthorized access.
Security teams must verify that each login endpoint correctly enforces rate limiting, but doing so manually or with one-size-fits-all tools can be inefficient and error-prone.
Risk Prevented: Account compromise through brute-force or credential stuffing attacks due to missing or weak rate limiting.
Traditional Approach
Analysts typically test rate limiting by sending bursts of requests manually or using simple scripts and then monitoring for signs like slow responses, temporary bans, or 429 errors. This requires custom scripting, manual review of responses, and carries a high chance of missing subtle indicators. Scaling this process across multiple APIs or applications is nearly impossible.
How Create with AI Changes It
Using S4E Create with AI, you can generate this entire test with a single prompt. The AI builds a scan that sends rapid consecutive requests to each login endpoint and analyzes responses for rate-limiting signals such as HTTP 429, Retry-After headers, or increased 401/403 patterns. It then reports clear findings across all verified assets in one consistent format — no scripting or manual analysis needed.
Instant Solution (Create with AI)
Prompt: Create a rate limiting test scan. This scan should send requests to the /login endpoint using the username and password parameters. The scan should send a short burst of rapid consecutive requests and analyze the server responses. If the server returns rate-limit indicators such as HTTP 429 (Too Many Requests), an increase in 403/401 responses, IP blocking behavior, or a Retry-After header, the scan should report that rate limiting is present; otherwise it should report that rate limiting is absent or insufficient.
The generated scan performs controlled rapid POST requests, analyzes the results, and determines whether the target implements rate limiting effectively — all automatically.
🎥 Watch the Scan in Action
The video demonstrates Create with AI generating and running a scan that rapidly tests a login endpoint and identifies whether rate-limiting mechanisms are correctly enforced.
Value
- Quickly validates rate-limiting enforcement across all assets
- Simulates real attacker behavior safely and consistently
- Eliminates guesswork and manual response analysis
- Produces standardized evidence for compliance and incident reviews
Closing Takeaway
Missing or misconfigured rate limits can expose applications to brute-force attacks within seconds. S4E Create with AI turns this complex validation process into a reusable automated check that continuously monitors for weak or missing rate-limiting protections.
🧰 Check It Yourself
Check the sample scan below or watch the video for a live walkthrough.
class Job(Task):
def run(self):
asset = http_or_https(asset=self.asset, _headers=self.headers, session=self.session)
endpoint = f"{asset}/login"
params = {
'username': self.user_env.get('username', 'user'),
'password': self.user_env.get('password', 'pass')
}
self.output['detail'] = []
self.output['compact'] = []
self.output['video'] = [f"python3 rate_limiting_test_scan.py {endpoint}"]
rapid_responses = []
for _ in range(5):
response = self.session.post(endpoint, data=params, headers=self.headers, timeout=10, verify=False)
rapid_responses.append(response)
rate_limit_present = False
for response in rapid_responses:
if response.status_code == 429 or 'Retry-After' in response.headers:
rate_limit_present = True
break
elif response.status_code in [401, 403]:
rate_limit_present = True
break
if rate_limit_present:
self.output['compact'].append('Rate limiting is present.')
self.output['detail'].append('Received HTTP 429 or retry headers indicating rate limiting.')
else:
self.output['compact'].append('Rate limiting is absent or insufficient.')
self.output['detail'].append('No rate limit indicators found in responses.')
self.output['video'].append("Testing /login endpoint with rapid requests...")
self.output['video'].extend([f"Sent request {idx+1}: Response {resp.status_code}" for idx, resp in enumerate(rapid_responses)])
if rate_limit_present:
self.output['video'].append("Rate limit detected based on responses.")
else:
self.output['video'].append("No rate limiting detected.")
def calculate_score(self):
if 'Rate limiting is present.' in self.output['compact']:
self.score = 0
else:
self.score = 5Want to see and learn more?
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