Detect malware or phishing URLs, e-mails and messages on the go!
Detect malware or phishing URLs and e-mail/messages on the go!
scan for malacious or phishing URL
scan for malacious or phishing URL
stay AWAY! not a safe URL
Suspected phishing/malware URL
don't fret Its a SAFE URL!
stay ALERT! seems to be a spam or phishing e-mail
Suspected phishing/spam e-mail
don't fret, It doesn't seem to be a spam or phishing e-mail!
stay ALERT! seems to be a spam/phishing message
Suspected spam message
don't fret, It doesn't seem to be a spam message!
Get the browser extension for quick and real time monitoring of the URLs you accessHere
Get the browser extension for quick and real time monitoring of the URLs you accessHere
What is Threat
Sleuth?
ThreatSlueth is an AI powered solution to detect malware or phishing URLs, spam emails and messages on the go!
How does it work?
It employs ML models trained on large amount of data to analyze and identify the URLs, emails and messages for features indication spam or malacious intent.
Through natural language processing and pattern recognition, it identifies suspicious patterns or characteristics indicative of phishing attempts or spam. This analysis includes examining the various features of content to identify signs of spam or phishing.
What types of features and characteristics does ThreatSleuth analyze to identify potential phishing URLs?
The data from thedatasetis filtered and categorzied based on several features which include the length of url, the tld(top level domain), length of tld, lexical features such as frequency of letters and numbers, special characters and some vital features like presence of ip address, use of url shortening service and more, the categorized dataset is then trained on various classifiers of which we picked the one with the best overall accuracy
What is the typical response time for ThreatSleuth to identify a potential threat after analyzing a URL, email, or message?
ThreatSlueth provides rapid response in real time(as you would have just seen above:)) typically in range of milliseconds to few seconds The trained compressed ml model coupled with a FastAPI server api framework does the magic!
How accurate is ThreatSleuth in detecting phishing attempts and spam emails/messages?
Well the accuracy was excellent on the testing set of the dataset, its your turn to test it with some real-world data and analyze. Do you find inaccurate results? please report those URLs
How does ThreatSleuth handle false positives and false negatives in its threat detection process?
Predicting false positives and negatives is a common challenge prevelant across most of the ML models throughout the world due to class imbalance in the datset, here we take a user feedback based approach and analyze and re-train the model periodically with the provided user data to optimize and refine the model to provide near perfect accuracy