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scam_categories = {
1: [
"Fake Authority Call",
"Scammers impersonating law enforcement officials (e.g., CBI, customs, police) or service agents, coercing victims into making payments or money.",
],
2: [
"Service Disconnection Scam",
"Threats of service disconnection unless immediate verification or payment is made.",
],
3: [
"UPI Scam",
"Scammers claim accidental UPI payments and request refunds, or attempt scams related to UPI, PhonePe, Google Pay, or any quick payment interface.",
],
4: ["OTP Scam", "Scammers request OTPs to gain unauthorized access to accounts."],
5: [
"Fake Buyer/Seller Scam",
"Scammers pose as buyers requesting refunds or as fraudulent sellers asking for advance payments.",
],
6: [
"Phishing or Link Scam",
"Fraudulent SMS or calls designed to gain unauthorized access to banking platforms by sending malicious links or asking for sensitive details.",
],
7: [
"Video Call Scam",
"Blackmail involving compromising video calls, or screenshots, used to demand money.",
],
8: [
"Fake Bank Staff Scam",
"Calls from scammers posing as bank officials, requesting sensitive banking details.",
],
9: [
"Fake Job Scam",
"Scammers posing as recruiters, demanding service or registration fees for fake job offers.",
],
10: [
"Lottery Scam",
"Messages claiming lottery wins, lucky draws, or prizes, and requesting fees for processing.",
],
11: [
"Fake Identity Scam",
"Scammers imitate known individuals and request money transfers.",
],
12: [
"Other Cyber Scam",
"Any other scam conducted via phone that involves monetary fraud.",
],
}
scam_categories_str = "\n".join(
[f"{k}: {v[0]}-{v[1]}" for k, v in scam_categories.items()]
)
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