Despite advancements in edge security controls like request inspection, credential validation, and device fingerprinting, attackers continue to bypass defenses. Malicious activity often mimics legitimate user behavior, making it difficult for existing systems to differentiate.
The core issue is that each security control focuses on a specific aspect of a user session, creating blind spots. This allows attackers using residential IPs or commercial VPNs to pass through multiple layers of security without triggering alerts.
Application security relies on multiple defense layers, each answering a different question about incoming traffic. CDNs and WAFs inspect requests and filter known threats, but they may not reveal if a connection is routed through disguised infrastructure.
Bot management identifies automation, but not all malicious sessions are automated, and attackers increasingly combine automation with infrastructure designed to look like consumer traffic. Identity systems verify credentials, but valid credentials do not guarantee the legitimate account holder is presenting them. Device intelligence describes the endpoint but not the network infrastructure connecting it to the application.
While individual security signals provide valuable insights, attackers exploit the gaps between them. They create sessions that appear legitimate to any single control, effectively hiding the true context of the infrastructure behind the connection.
This situation creates a demand for an additional layer of security intelligence that provides real-time context about the underlying infrastructure. Such a layer would reveal when sessions are hidden behind VPNs, proxies, anonymization services, data center traffic, or AI activity, enabling smarter enforcement decisions.
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Existing edge security controls, including CDNs, WAFs, bot management, and identity systems, often fail to detect sophisticated attackers because they lack context about the underlying network infrastructure. Attackers exploit gaps between these individual controls by using residential IPs or commercial VPNs, making malicious traffic appear legitimate. This highlights a need for an additional layer of security intelligence focused on infrastructure context to improve detection of high-risk sessions.