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Google Docs
Detect scams SMS and phishing links before they cause harm
ZeroFraud goes beyond traditional keyword filtering by combining machine learning, regex-based detection, threat intelligence, and risk scoring to analyze SMS messages in real time. It also features automated threat intelligence updates, an offline-capable admin dashboard, and a continuous feedback loop that improves detection accuracy over time.
Top comment
Hi everyone! I'm excited to introduce ZeroFruad. The idea came from seeing how many people continue to fall victim to SMS scams, phishing links, fake payment alerts, OTP theft, and mobile money fraud. Most solutions rely on simple keyword matching, but scammers constantly change their wording to bypass those filters. I wanted to build something that could adapt to these evolving tactics. Instead of relying on a single detection method, ZeroFraud combines machine learning, regex-based detection, threat intelligence, and a risk scoring engine to analyze messages from multiple perspectives before determining whether they're suspicious. Building ZeroFraud has been a great learning experience, combining cybersecurity, AI, backend development, and Android development into one project. One of the biggest challenges was balancing detection accuracy with minimizing false positives while keeping analysis fast enough for real-time use. This is still an evolving project, and I'm looking forward to learning from the Product Hunt community. If you have ideas, suggestions, or feedback, I'd genuinely appreciate hearing them. Thanks for checking it out!
About Google Docs on Product Hunt
“Detect scams SMS and phishing links before they cause harm”
Google Docs was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #88 on the daily leaderboard. ZeroFraud goes beyond traditional keyword filtering by combining machine learning, regex-based detection, threat intelligence, and risk scoring to analyze SMS messages in real time. It also features automated threat intelligence updates, an offline-capable admin dashboard, and a continuous feedback loop that improves detection accuracy over time.
On the analytics side, Google Docs competes within Productivity and Tech — topics that collectively have 1.3M followers on Product Hunt. The dashboard above tracks how Google Docs performed against the three products that launched closest to it on the same day.
Who hunted Google Docs?
Google Docs was hunted by caleb. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Google Docs including community comment highlights and product details, visit the product overview.