Stripe Webhook Secret Abuse
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Test Stripe webhook endpoints with leaked whsec signing secrets."""
from kittysploit import *
from lib.protocols.http.http_client import Http_client
from lib.scanner.http.stripe_webhook_probe import enumerate_stripe_webhooks
from lib.scanner.http.vibe_secrets_probe import collect_vibe_http_bodies, mask_secret
class Module(Auxiliary, Http_client):
__info__ = {
"name": "Stripe Webhook Secret Abuse",
"description": (
"Discovers whsec_* webhook secrets and probes common Stripe webhook paths. "
"Tests unsigned acceptance and HMAC-signed delivery with leaked secrets."
),
"author": ["KittySploit Team"],
"tags": ["stripe", "webhook", "payment", "enumeration", "auxiliary"],
"modules": [
"scanner/http/vibe_stack_secrets_detect",
"scanner/http/preview_deploy_prod_secrets_detect",
],
"agent": {
"risk": "intrusive",
"effects": ["network_probe"],
"expected_requests": 8,
"reversible": True,
"approval_required": True,
"produces": ["credentials", "risk_signals"],
"cost": 1.1,
"noise": 0.5,
"value": 1.3,
},
}
whsec = OptString("", "Stripe webhook signing secret (whsec_…)", False)
auto_discover = OptBool(True, "Scrape SPA for Stripe webhook secrets", False)
def run(self):
bodies = collect_vibe_http_bodies(self.http_request) if self._to_bool(self.auto_discover) else []
homepage = next((t for p, t in bodies if p == "/"), "")
findings, creds = enumerate_stripe_webhooks(
self.http_request,
homepage,
whsec=str(self.whsec or "").strip(),
)
hits = [f for f in findings if f.get("kind") != "stripe_whsec_discovered" or creds.get("whsec")]
critical = [f for f in findings if f.get("severity") == "critical"]
if not hits:
print_error("No Stripe webhook signals (set whsec or enable auto_discover)")
return False
for hit in hits:
if hit.get("path"):
print_success(f"Stripe {hit.get('kind')} @ {hit.get('path')}")
else:
print_success(f"Stripe {hit.get('kind')}")
self.set_info(
severity="critical" if critical else "high",
reason=f"Stripe webhook abuse: {len(hits)} signal(s)",
findings=findings,
credentials={k: mask_secret(v) for k, v in creds.items()},
)
return True
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08 Aug 2026 21:48Current
5.8Medium risk
Vulners AI Score5.8