Overview
The Threat Intelligence AI module serves as Pakistan's digital sentinel, providing comprehensive cyber defense through three specialized AI systems. Built to address the unique security challenges facing Pakistani organizations—from government networks to financial institutions—this module combines rapid attack classification, sophisticated phishing detection, and multilingual threat analysis.
Pakistani organizations often operate with limited telemetry and constrained infrastructure. Our lightweight classifiers enable security teams to perform rapid triage with minimal computational requirements, making advanced threat detection accessible even in low-resource environments.
The module processes threats in multiple dimensions: network traffic analysis for attack classification, content-based phishing detection supporting English and Urdu, and hybrid multilingual threat assessment that understands Pakistan-specific security contexts including anti-government rhetoric, separatist content, and regional threat patterns.
Key Metrics
1000s
Threats Analyzed Daily
0ms
Detection Speed
0+
Model Accuracy
0%
False Positive Rate
24/7
Active Monitoring
3
Specialized Models
Sub-Modules
Three Specialized AI Systems Working in Concert
This lightweight classifier provides real-time classification of cyberattacks from network traffic data. It is designed for resource-constrained environments, making advanced security accessible across Pakistan.
Engage with this Model
Launch the interactive demo to analyze network traffic in real-time.
This transformer-based text classifier protects users by analyzing emails, messages, and other text for fraudulent content. It provides fast, accurate phishing detection on CPU hardware, powered by a custom-trained model.
Engage with this Model
Launch the interactive demo to analyze suspicious emails and text messages in real-time.
A hybrid AI system combining multilingual sentiment analysis and topic modeling to monitor social media and online forums for threats specific to Pakistan, understanding context in English, Urdu, and Roman Urdu.
Engage with this Model
Launch the external Streamlit demo to analyze text for sentiment and topics in real-time.