Wiz Outlines a Four-Pillar Framework for AI-Era Threat Readiness

Article Details

Defense Focus

Improve AI-era threat readiness by continuously identifying and validating exposure, detecting meaningful runtime threats with environmental context, and accelerating investigation, containment, and remediation.

Detection Methods

• Continuously discover and inventory internet-facing assets, applications, APIs, services, and identities, including shadow APIs.
• Use AI-driven analysis to assess whether exposed applications, APIs, services, and identity flows are exploitable; simulate attacker behavior to identify end-to-end attack paths.
• Perform advanced AI code analysis on prioritized, high-impact code to find complex logic flaws, chained vulnerabilities, and insecure application flows.
• Ingest and correlate cloud, workload, runtime, identity, network, data-access, secrets-use, and version-control telemetry.
• Use AI to investigate alerts through multiple steps, produce a verdict, and establish behavioral baselines to reduce noise.
• Continuously validate detection efficacy and response speed through attack simulation.

Data Sources

• Cloud and workload telemetry, including runtime telemetry
• Identity provider logs and audit logs
• Cloud audit logs
• Version control system audit logs
• Data-access, secrets-usage, and network-activity telemetry
• Code, cloud, runtime, identity, workload, and application context

Platforms

• Cloud environments
• Workloads
• Kubernetes
• Identity providers
• Version control systems

Defensive Actions

• Reduce unnecessary internet exposure; keep sensitive assets and privileged access paths unreachable from untrusted paths regardless of patch status.
• Prioritize exposed assets by reachability, exploitability, business impact, runtime use, identity privileges, and data sensitivity; route findings to accountable owners.
• Segment or isolate unpatchable and high-risk systems, and remove unused or orphaned assets.
• Use hardened base images and components, minimize unnecessary packages and dependencies, and prevent known risky patterns from reaching production.
• Establish workflows to triage newly disclosed vulnerabilities and remediate at the source where possible.
• For high-fidelity threats, use response playbooks to isolate workloads, revoke risky permissions or data access, block suspicious communication or processes, rotate secrets, notify owners, open incidents, and preserve forensic evidence.
• Require human approval for sensitive response actions where appropriate.