DeepScam-AI-powered Scam Detection

Example

Analyzing an email purporting to be from a bank, requesting login information. DeepScam examines the sender's domain, the presence of personalized greetings, and checks for suspicious links.

Scenario

A user receives an email asking for urgent verification of their account to avoid suspension. DeepScam would analyze this email to identify telltale signs of phishing, such as generic greetings, urgency, and suspicious links.

Example

Evaluating a website link that claims to offer exclusive discounts. DeepScam checks the URL against security databases and assesses the site's legitimacy.

Scenario

Before making a purchase from a new online retailer, a user checks the site's URL with DeepScam, which verifies the site's security and reviews to prevent financial fraud.

Example

Researching a phone number that left a voicemail about an unpaid tax bill. DeepScam searches scam databases and evaluates if the number has been reported.

Scenario

A user receives a call claiming they owe money to the IRS and must pay immediately. DeepScam can help verify whether the phone number is known for scamming activities.

Example

Examining a story where a user is told they've won a lottery they never entered, requiring a payment to claim the prize. DeepScam compares this with known scam narratives.

Scenario

Someone contacts a user with a job offer that seems too good to be true, asking for personal details and a setup fee. DeepScam analyzes the scenario to determine its scam likelihood.

Example

Inspecting a downloaded file that's supposed to be an invoice but exhibits unusual behavior. DeepScam checks the file against virus databases for known threats.

Scenario

A user receives an email attachment labeled as urgent documentation. Before opening, the file is uploaded to DeepScam, which assesses it for potential malware or security threats.