AI Cyber Threat Prediction System ThreatOracle Launches: 72-Hour Advance Warning for Zero-Day Attacks
Israeli cybersecurity firm CyberShield launches AI threat prediction system ThreatOracle, which analyzes global network traffic patterns and dark web intelligence to issue warnings 72 hours before zero-day attacks occur.
Israeli cybersecurity company CyberShield today launched AI cyber threat prediction system ThreatOracle. Unlike traditional security systems that respond after attacks occur, ThreatOracle predicts threats by analyzing anomalous global internet traffic patterns, dark web forum attack tool trades, and suspicious software supply chain changes before attacks actually happen.
ThreatOracle's core is a continuously learning threat intelligence graph integrating real-time data from 4,700 global sensor nodes. The system uses causal reasoning models to identify attack preparation activities — such as attackers purchasing exploit tools on dark web forums, conducting reconnaissance scans on targets, or planting backdoors in code repositories.
During 8 months of testing, ThreatOracle successfully provided advance warning for 3 major zero-day attack events, with an average warning time of 67 hours before the attacks occurred.
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