Vega's federated analytics layer makes Cyera's data sensitivity and identity context part of every query, detection, and investigation - so SOC decisions are grounded in real risk, without moving or duplicating data.
Vega's federated search makes organizational context queryable alongside telemetry in one KQL flow. Dynamic Lookup Tables turn shared logic into continuously refreshed, reusable assets for detections, investigations, and AI.
Vega's IOC Auto-Hunt runs the backsearch on every incoming threat briefing. By the time you open the page, hits are already surfaced and the hunt notebook is ready to run.
Autonomous AI investigations only reduce analyst workload when every query, every piece of evidence, and every decision is visible. A walkthrough of an SMS MFA bypass, end to end.
Vega's MITRE Coverage view answers "are we covered?" with a heatmap fed by live telemetry and live detection state. Every uncovered technique becomes either an actionable gap or a blind spot, with a concrete next move.
Vega's federated analytics engine and in-place reverse indexing now span AWS, Azure, GCP, and every major legacy SIEM - one query, normalized results, zero cross-cloud data movement.
The Vega Threat Research team identified active exploitation of CVE-2026-22679, a critical unauthenticated RCE in Weaver E-cology, 14 days before public in-the-wild reporting. This report details real-world exploitation and post-compromise behavior.
Most SOC investment goes toward making investigations faster. But a huge share of that work is reconstructing context that should have been there from the start. Fix upstream and investigations get faster as a byproduct.
Most MCP implementations in security are read-only API wrappers. Learn how natural language MCP endpoints over federated data change detection engineering, threat hunting, and alert triage.
Smarter on what data? Why Mythos and MCP don't fix missing evidence - and what federated analytics, durable history, and normalization require for investigation-grade AI in the SOC.
Centralized SIEMs move data to compute; federated analytics moves compute to data. Broader coverage, less operational overhead, and a unified layer ready for AI-driven security operations.
A field guide to RSA 2026 - agentic AI, next-gen SIEM, single pane of glass, and what nobody will say out loud about visibility, cost, and detection completeness.
AI agents are changing the operating system for SecOps - where specialized agents handle detection, triage, and response across a federated Security Analytics Mesh, reasoning across all your data without requiring centralized storage.
How attackers use blockchain-hosted payloads and fake CAPTCHA lures to bypass traditional defenses and steal cryptocurrency wallets, browser credentials, and messaging app sessions
Why AI in security operations fails without the right foundation, and what it takes to build a SOC where intelligence compounds across detection, triage, and response
Reflections on momentum, product-market fit, and what it takes to build the operating system for AI-native security operations
A veteran incident response manager shares how security data gaps extend breach recovery from days to weeks, and why data maturity is the foundation of true incident preparedness
How security data is growing faster than traditional analytics models can handle, and why federated mesh architectures represent the next evolution beyond centralized SIEMs
Why wait for queries to finish? Simply stream results as they get computed in a long running query.
Exploring how AI has been constrained by legacy security architectures and why a new foundation is needed for transformative security outcomes
Learn how modern data systems overcome the challenges of operating at massive scale using probabilistic techniques like Bloom filters & HyperLogLog
Learn how log search engines like Apache Lucene & tantivy work
