Cyberattacks are increasing and are unlikely to decline, forcing organizations to defend in conditions where the attack surface is expanding and attacks often remain undetected for a critical period. The most dangerous window is when attacks are actively running but not yet identified; this “unknown” phase can be immediate in visible ransomware cases or persist for years. Even after identification, traditional security approaches can take hours to days (or longer) to provide effective protection, leaving time for additional attackers to exploit the same weaknesses. As a result, signature-based anti-malware is necessary but insufficient; organizations also need technologies that protect against unknown and zero-day attacks.
At the same time, Digital Transformation requires constant information exchange with partners, customers, and users. Ensuring access to clean, secure business content becomes central to enabling collaboration and maintaining trust. To address threats “beyond detection,” several complementary approaches are highlighted: cognitive security using AI for anomaly identification, isolation for risky activities like web browsing, and Content Disarm and Reconstruct methods that strip potentially dangerous elements from content.
Content Threat Removal advances further by extracting useful business information, discarding everything else, and reconstructing entirely new “clean” data—leaving malicious components behind. Deep Secure, founded in 2009 and headquartered in the UK, provides products spanning deep content inspection “guards” and a newer Content Threat Removal Platform. The platform transforms data through three components (extract, verify, rebuild), deployable on hardware, virtualized environments, or cloud. It supports application-level proxies for mail, file transfer, and web, plus ICAP “sidecar” integration with existing gateways and firewalls, and targets threats including steganography in images. While transformation can risk performance impact, Deep Secure emphasizes non-real-time channels and claims no measurable negative effect compared to detection-based approaches, positioning the platform as a strong component for securing cross-boundary content exchange.
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