Your cloud defenses have critical blind spots. Zero trust focuses on user access, but once inside the cloud, attackers move laterally – across accounts, regions, and workloads – without runtime enforcement or visibility.
Cloud providers expose logs, but they do not correlate behaviors into multi-stage attack sequences across workloads.
Cloud security posture tools detect misconfigurations but cannot show how runtime behaviors link together into exploitable attack paths.
Security teams need runtime proof that controls stop lateral movement and data loss—static snapshots aren’t enough.
This free, agentless assessment uses AI-assisted correlation to transform flow and DNS telemetry into actionable runtime insight. It identifies patterns like DNS tunnelling, lateral movement, and suspicious egress and connects them into “Workload Breach Chains” — the multi-stage paths an attacker could realistically take through your environment.
AI-driven context discovery reveals how isolated behaviors combine into exploitable attack sequences—not just alerts or raw logs.
See how correlated detections surface the sequences that matter most—showing which runtime behaviors create the greatest risk.
Uses your existing telemetry with no agents, deployment, or architectural changes required.
Turn runtime visibility into meaningful action. Understand how risks connect across workloads, identify high-impact problem areas, strengthen zero trust strategy, and align security, cloud, and platform teams around shared runtime evidence.
Reveal Hidden Runtime Risks
Reveal hidden runtime risks by identifying clear-text HTTP and other unencrypted workload communication using flow-level indicators. Understand where real behaviors, identities, or connectivity patterns deviate from expected Zero Trust intent.
Correlate Behaviors into Paths
Correlate runtime behaviors—DNS tunnelling, east-west movement, and suspicious egress—into attacker-relevant sequences. See how isolated detections link together into the early stages of multi-step attack paths that posture tools cannot surface.
Prioritize What Matters Most
Focus on runtime behaviors that break multiple potential breach paths—not isolated alerts. Identify which workloads create the largest attacker-reachable surface so teams can prioritize the issues with the highest real-world impact on reducing multi-stage exposure.
Validate Zero Trust at Runtime
See where segmentation intent, workload identity expectations, or egress guardrails are not being met—based on real runtime communication. Validate Zero Trust boundaries with evidence showing how behaviors align—or misalign—with designed trust policies.
Align Security & Cloud Teams
Unify security, cloud, and platform teams around shared runtime evidence instead of static posture data. Provide a common view of how workloads actually communicate, enabling teams to coordinate remediation, reduce friction, and scale Zero Trust consistently.
Using AI-assisted correlation, the assessment adds context to flow and DNS data—revealing hidden relationships, surfacing gaps in protection, and showing how attacker movement could unfold at runtime through correlated multi-stage behavior sequences.
Automatically discover applications, environments, and workload roles using AI-based analysis of names, tags, and runtime patterns.
Use AI-assisted correlation to group related workloads and reveal hidden relationships—clarifying how attacker movement could unfold at runtime.
Identify outbound calls to AI/ML APIs and public package sources that may introduce data-sovereignty, exposure, or supply-chain risks.
The Workload Attack Path Assessment is a free, agentless, read-only tool that analyzes your cloud’s flow and DNS telemetry to reveal how real attacks could move through your environment. Using AI-assisted correlation, it identifies behaviors like DNS tunneling, lateral movement, and suspicious egress, and connects them into Workload Breach Chains — giving you attacker-realistic insight posture tools miss.
Cloud security posture tools focus on configuration drift and settings. The Workload Attack Path Assessment focuses on runtime behavior. It analyzes actual workload-to-workload and workload-to-internet communication to reveal how risks could progress — providing attacker-realistic insight that posture tools simply cannot generate.
Not at all. The assessment is completely agentless and operates through read-only log ingestion, making it fully out-of-band with zero impact on production systems. Setup is straightforward—you simply share access to your existing AWS or Azure flow logs and DNS telemetry (one cloud environment per assessment). There’s no need for agents, re-architecture, or any changes to your current network topology. Results appear directly in the console with no deployment overhead or downtime.
You get a clear understanding of how attacks could progress inside your cloud — plus prioritized findings showing where segmentation, identity, or egress controls may be missing. You also gain audit-ready zero trust evidence aligned to ZTMM 2.0, HIPAA 2025, PCI DSS 4.0, and DORA. Even when risk is low, you receive proof that runtime communication aligns with Zero Trust expectations.
Yes. You securely connect your AWS or Azure account using a read-only role, and the assessment automatically ingests flow logs and DNS telemetry. No agents, no deployment, and no changes to networks, routes, or workloads are required — the integration is fully read-only and scoped to only the data required for the assessment.
Your workloads are talking. Are you listening?
