Security and fraud teams can now act on Spur’s real-time trust signals across three major CDNs, backed by new capabilities to monitor and investigate Spur intelligence
Spur Intelligence announced that Spur Monocle, its real-time session enrichment solution, can now be deployed on Fastly and Amazon CloudFront in addition to Cloudflare. Security and fraud teams using these platforms can now stop risky traffic at the edge using advanced session signals while keeping friction low for legitimate users.
Fraud and abuse often arrive via VPNs, residential proxies, and other anonymizing networks that make malicious sessions appear to be ordinary users. Without reliable context about where each session comes from, teams face a hard tradeoff. They can enforce broadly and risk turning away real customers, or they can commit engineering resources to building and maintaining their own network and session detection logic.
Spur Monocle solves this by enriching every user session with real-time trust signals, including anonymization status, proxy service attribution, residential infrastructure, and emerging attacker networks. Because Monocle runs at the edge, those signals arrive inside the infrastructure that already evaluates and routes application traffic. Teams gain the context to make sharper enforcement decisions right away, without having to build or maintain their own detection tools and logic. Setup takes only minutes and requires no changes to origin code.
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“Intelligence only makes a difference when teams can put it into action,” said Alastair Parr, CTO and COO of Spur. “Whether a team is enforcing trust decisions at the edge or investigating the infrastructure behind suspicious activity, we want Spur to fit the way they already work and give them confidence that it’s working as expected.”
Additional Updates Make Spur Intelligence Easier to Monitor and Investigate
Bringing intelligence to the edge is one part of putting it to work. Additional new capabilities help teams confirm that their Spur products are running as expected and get answers faster when investigating suspicious infrastructure. Highlights include:
- AI traffic analysis in user sessions: Monocle now shows which AI agents and crawlers are reaching an app, how much traffic each sends, its share, and the change over time. Customers can filter by AI operator, and pair that with the Traffic Type filter (Crawler or Agentic) to better understand how much traffic is AI and which service it is. This is an especially impactful capability with the significant increase in agentic traffic.
- Early warning when an integration stalls: A live, color-coded health status labels each Monocle app as healthy, warning, or inactive, and a banner appears if an app unexpectedly stops sending traffic. Teams no longer have to discover the issue later through missing data.
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