Malware clssification system -- 2
Budget: ₹12,500 – ₹37,500 INR
I want to take ai-mcs.in to the next level by tightening the core of what matters most: detection accuracy. Our current Python-Flask analysis engine already flags known signatures and runs basic heuristic checks, but false negatives still slip through. I need you to review the existing codebase, refine or even replace the models/rules, and integrate any open-source or custom ML techniques you trust—so long as they run headless on the server and return results fast enough for real-time scoring.
On the front-end, the User Scan History section of the PHP dashboard also needs a refresh so every scan instantly tells a clear story. When a member opens their history, each row should show:
• Scan date and time
• Type of scan (URL / File)
• Threat level detected
Those three data points must pull straight from MySQL and stay in sync with the new backend logic.
Tech stack you will touch: Python 3.x (Flask, pandas, any AV/ML libraries), PHP 8 dashboard components, and our existing MySQL schema. You can spin up local containers if you prefer; I’ll share an anonymised DB dump and the repo once we confirm.
Deliverables are straightforward: an upgraded detection module with documented code; a patched dashboard page that renders the additional columns responsively; and a brief deployment guide so I can roll the changes onto production without downtime.
If you’ve previously tuned malware classifiers or built scan history views that users actually read, you’ll feel right at home.
On the front-end, the User Scan History section of the PHP dashboard also needs a refresh so every scan instantly tells a clear story. When a member opens their history, each row should show:
• Scan date and time
• Type of scan (URL / File)
• Threat level detected
Those three data points must pull straight from MySQL and stay in sync with the new backend logic.
Tech stack you will touch: Python 3.x (Flask, pandas, any AV/ML libraries), PHP 8 dashboard components, and our existing MySQL schema. You can spin up local containers if you prefer; I’ll share an anonymised DB dump and the repo once we confirm.
Deliverables are straightforward: an upgraded detection module with documented code; a patched dashboard page that renders the additional columns responsively; and a brief deployment guide so I can roll the changes onto production without downtime.
If you’ve previously tuned malware classifiers or built scan history views that users actually read, you’ll feel right at home.