Site%3apastebin.com+key+investment+services May 2026

findings = {} for label, regex in patterns.items(): matches = re.findall(regex, text, re.IGNORECASE) if matches: findings[label] = matches return findings def generate_feature(company_name="Key Investment Services"): pastes = fetch_pastebin_mentions(company_name)

return mock_pastes def extract_sensitive_patterns(text): patterns = postgresql)://\S+' site%3apastebin.com+key+investment+services

if exposures: return "feature_value": len(exposures), "risk_level": "CRITICAL" if any("private_key" in e["exposed_items"] for e in exposures) else "HIGH", "details": exposures else: return "feature_value": 1, # mention exists but no high-risk secrets "risk_level": "MEDIUM", "details": ["paste_url": p["url"], "date": p["date"] for p in pastes] feature_output = generate_feature() print(feature_output) Example Feature Output "feature_value": 2, "risk_level": "HIGH", "details": [ "paste_url": "https://pastebin.com/abc123", "date": "2026-04-04", "exposed_items": "api_key": ["sk_live_4eC39HqLyjWDarjtT1zdp7dc"] , "paste_url": "https://pastebin.com/xyz789", "date": "2026-02-22", "exposed_items": "password": ["KeyInv@2024"] ] findings = {} for label, regex in patterns

if not pastes: return "feature_value": 0, "risk_level": "LOW", "details": "No mentions found on Pastebin." findings = {} for label