Uncovering Hidden Attack Paths in Cloud Environments Using Runtime Signals

2026-06-25 · Source: wiz.io - Www.wiz.io · Field: Technology & Digital — Cybersecurity & Data Privacy, Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure · Depth: Intermediate, medium

Summary

Wiz has introduced a new layer of runtime telemetry, integrating live network signals from workloads into its Security Graph to enhance agentless risk analysis. This new capability, powered by the Wiz Runtime Sensor, collects real-time network activity such as active connections between containers, DNS queries to databases, and AI workloads communicating with remote MCP servers. By correlating these runtime signals with existing agentless risk findings, Wiz uncovers previously hidden attack paths. For instance, an internet-facing AI chatbot with vulnerabilities and access to sensitive data, actively connecting to an external MCP server, is identified as a single, critical data exfiltration path. Wiz found that for 1 in every 6 environments monitored, adding runtime risk context surfaced a high- or critical-severity attack path that prior analysis had missed. This integration provides security teams with a complete view of active connections and validated attack paths, enabling more precise prioritization and remediation.

Key takeaway

For Cloud Security Engineers prioritizing critical risks, relying solely on agentless scanning leaves significant blind spots. You should integrate runtime network telemetry to uncover active attack paths, particularly those involving AI workloads communicating with external services like MCP servers. This approach reveals connections not defined in configurations, enabling you to prioritize and remediate validated threats before attackers exploit them, reducing data exfiltration risks.

Key insights

Runtime network signals reveal hidden attack paths by correlating live connections with existing cloud risks.

Principles

• The connection is the attack path.
• Agentless scanning misses runtime-only connections.
• AI workloads create new, often invisible, attack vectors.

Method

The Wiz Runtime Sensor collects live network signals (DNS queries, active connections) from workloads, feeding them into the Wiz Security Graph to correlate with agentless risk findings and identify complete attack paths.

In practice

• Integrate runtime telemetry with risk analysis.
• Prioritize remediation based on validated attack paths.
• Monitor AI workload connections to external MCP servers.

Topics

• Cloud Security
• Attack Path Analysis
• Runtime Telemetry
• Wiz Security Graph
• AI Workload Security
• Network Visibility
• MCP Protocol

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Security Engineer, Security Engineer, MLOps Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by wiz.io - Www.wiz.io.