https://github.com/deadkennedyx/fishhunt
Machine learning + malicious sites scanner for phishing detection
https://github.com/deadkennedyx/fishhunt
cybersecurity infosec machine-learning machinelearning phishing scam tools
Last synced: about 2 months ago
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Machine learning + malicious sites scanner for phishing detection
- Host: GitHub
- URL: https://github.com/deadkennedyx/fishhunt
- Owner: DeadKennedyx
- License: apache-2.0
- Created: 2024-01-03T21:08:55.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-04T21:15:41.000Z (over 1 year ago)
- Last Synced: 2025-03-24T07:07:08.648Z (2 months ago)
- Topics: cybersecurity, infosec, machine-learning, machinelearning, phishing, scam, tools
- Language: Python
- Homepage:
- Size: 8.86 MB
- Stars: 10
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
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FISHHUNT BY DEADKENNEDYX
```
As of right now FishHunt is a GMAIL phishing detection system, uses a machine learning model trained on 5000 phishing emails and 5000 non-phsishing emails.
It also uses [MalTrail](https://github.com/stamparm/maltrail?tab=readme-ov-file#blacklist) list of malicious domains that is updated every day and checks the urls in the emails for any of those malicious urls.
### Appreciation
If you are cloning dont forget to give me a little star!
### USAGE:
1- `pip3 install -r requirements.txt`.
2- Copy and paste your credentials.json in the root folder from your google oauth client, file name must be `credentials.json`
2- Go to `/FishNet` and run `python3 email_training.py`, this will start the model training with the legal and phishing emails `.mbox`.
3- We will have now 2 file outputs after running the email_training `phishing_model.pkl` and `vectorizer.pkl`, move this files to the root folder.
4- Now go to root folder and run `python3 main.py`, if you have not been logged in before then it will open a browser tab with the gmail auth page
5- After logging in it will create a `token.json` file in the root folder which will be used for further runs of the script without needing to log in each time you run it
5- By default it checks your last 100 emails, you can modify the script `phishing_detection.py` to increase the default, or implement websockets/push-notifications for live tracking