Cloud posture
Understand configuration gaps across accounts, services, and workloads. Connect exposure to the environment it could affect.
- Asset and configuration visibility
- Internet-facing service review
- Misconfiguration prioritization
Explore the questions, evidence, and actions behind cloud, application, identity, data, and AI security. Use these discussion areas to define your requirements.
Build your security program around the relationships between infrastructure, applications, identities, and the information they protect.
Understand configuration gaps across accounts, services, and workloads. Connect exposure to the environment it could affect.
Bring risk conversations back to the source, with context that helps developers understand and resolve findings.
Explore the models, integrations, and data flows behind AI applications. Know where sensitive information can travel.
Look beyond isolated permissions to understand effective access and the paths that lead to critical resources.
Which configurations create unnecessary exposure?
Account inventory, public endpoints, network rules, encryption settings, and configuration history.
Confirm the intended baseline with cloud owners. Review exceptions and validate changes in the running environment.
Where should the engineering change be made?
Repository ownership, deployed versions, dependency manifests, and infrastructure-as-code definitions.
Connect the finding to its source. Provide reproduction context, a scoped change, and a validation plan.
What can this identity actually reach?
Role assignments, trust relationships, resource policies, and conditions that affect effective permissions.
Confirm required access with the owner, narrow permissions, and test expected application behavior.
Which information could be affected by this path?
Classification, storage configuration, data ownership, retention requirements, and access records.
Review whether access is necessary. Tighten the relevant policy and verify the sensitive resource is protected.
Which tools and data can this AI service use?
Model and agent inventory, service identities, tool grants, endpoint exposure, and input/output data flows.
Review access boundaries, apply least privilege, and establish a repeatable review for deployment changes.
Use this reference matrix to scope your security requirements. These are discussion areas; specific product capabilities and integrations need confirmation.
| Security area | Question to answer | Evidence to review | Practical next step |
|---|---|---|---|
| Cloud posture | What is exposed or misconfigured? | Resource inventory, network rules, configuration snapshots | Review public access and baseline settings with cloud owners. |
| Application security | Where should a fix happen? | Repository ownership, dependencies, deployment configuration | Route a reproducible finding to the responsible engineering team. |
| Identity risk | Who or what can reach a critical resource? | Roles, trust policies, permission grants, access logs | Validate access needs and remove unnecessary permissions. |
| Data exposure | Which sensitive data could be accessed? | Data classification, storage policies, access relationships | Confirm intended access and tighten the relevant controls. |
| AI security | What can an AI service or agent access? | Model endpoints, tool permissions, data flows, service identities | Review tool access boundaries and sensitive data handling. |
Discuss your priorities, technical requirements, and the scope that fits your team.