Miles Jamison 
Glasswall has introduced Foresight, a threat intelligence capability designed to help security teams identify potentially malicious files earlier by applying machine learning and structural file analysis within Content Disarm and Reconstruction, or CDR, workflows.
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Why Was Glasswall Foresight Developed?
Traditional intelligence methods often rely on file signatures or behavioral analysis through detonation, leaving organizations exposed to zero-day and targeted attacks. Security teams are continually tasked with interpreting alerts, managing emerging vulnerabilities and protecting critical files. Foresight was developed to provide security professionals with structured, reliable intelligence to help them identify and prioritize risks, optimize policies, and respond more quickly.
How Does Glasswall Foresight Identify Unknown Malware?
Foresight uses proprietary machine-learning models to provide probabilistic threat scoring when integrated with CDR workflows, giving security teams clearer insight and control over file safety. Instead of relying on internet-trained AI or sandbox analysis, it evaluates structural telemetry from the CDR process to deliver detailed threat intelligence while preserving the original file structure. Operating fully offline, Foresight supports air-gapped and denied, disrupted, intermittent and limited, or DDIL, environments where traditional antivirus tools often fall short.
How Is the Tool Integrated Into Existing Workflows?
When processed through Glasswall Meteor, files undergo deep analysis of embedded characteristics to produce a probabilistic threat score. This intelligence is applied alongside existing CDR policies, allowing for policy-driven decisions that avoid detonation delays or complex infrastructure. The capability supports PDF, DOCX and XLSX formats.
