Inside JagAI: How Threat Scoring Protects You From Unknown Malware

From Binary Verdicts to Threat Scores

Traditional antivirus gives a binary answer: a file is either malicious or clean. Reality is more nuanced. JagAI assigns a continuous threat score from 0 to 100, reflecting the probability that a file or behavior is malicious. This approach enables graduated responses - a file scoring 90 is quarantined immediately, while a file scoring 60 triggers enhanced monitoring until more data is available.

Features JagAI Evaluates

JagAI evaluates hundreds of features across multiple categories. Static features include file entropy, section characteristics, import table analysis, and string patterns. Behavioral features include process creation chains, file system activity patterns, network communication profiles, and registry modification sequences. Contextual features include file origin, download history, prevalence across the True Protection user base, and time since first observation.

The Scoring Model

JagAI's scoring model uses an ensemble of machine learning classifiers trained on millions of labeled samples. By combining multiple models that analyze different feature sets, the system achieves higher accuracy than any single model. The ensemble is retrained regularly with newly collected samples, and model performance is continuously validated against held-out test sets to detect any drift or degradation.

Transparency and Control

True Protection shows you exactly why a file received its threat score. The threat report displays the top contributing features, allowing security teams to make informed decisions about borderline files. Administrators can adjust score thresholds to match their organization's risk tolerance - stricter environments can lower the quarantine threshold while environments with many custom tools can raise it to reduce false positives.