Master cloud forensics artifact collection. This scenario evaluates your ability to correctly identify the native storage locations and service providers for cryptographic access logs within a Microsoft Azure architecture.
Your forensic firm has been retained by a financial technology company to investigate a suspected internal data breach. The subject under investigation is a former DevOps engineer whose credentials were used to extract sensitive API keys and database connection strings shortly after their termination.
The company utilizes Microsoft Azure to host its infrastructure. All critical secrets, including the compromised API keys, are stored securely inside an Azure Key Vault. As the lead forensic analyst, you must preserve and collect the exact access logs demonstrating which identity requested the secrets, the time of the request, and the originating IP address to establish a definitive timeline of the exfiltration.
The log snippet above proves the 'SecretGet' operation was successful. The investigator must now identify which Azure service natively stores and queries these data-plane audit events for comprehensive forensic reporting.
In a cloud-forensics case involving a Microsoft Azure environment, an analyst needs to review the logs of access to an Azure Key Vault. Which Azure service provides these logs?
The JSON log snippet displays an AuditEvent with an operationName of SecretGet. This is a data-plane operation. It contains crucial forensic artifacts: the exact timestamp, the target resource, the outcome (Success), the originating IP (192.0.2.45), and the identity claim (UPN) of the actor.
This scenario aligns with the Collection and Analysis phases of cloud forensics, specifically targeting log acquisition and timeline reconstruction from centralized cloud repositories.
Azure Monitor Logs (backed by Log Analytics workspaces) is the service used to collect, aggregate, and query detailed diagnostic logs—including Key Vault data-plane access logs. When an investigator needs to see who performed operations like `SecretGet`, `KeyGet`, or `CertificateGet` within the vault, they must query Azure Monitor Logs using Kusto Query Language (KQL).
• B (Azure Activity Log): Activity Logs only track control-plane operations (e.g., who created the Key Vault, who changed its access policies). It does not log the data-plane access to the secrets themselves.
• C (Azure Advisor): A service that provides recommendations for cost, security, reliability, and performance. It is not a log repository.
• D (Azure Security Center): Now part of Microsoft Defender for Cloud, it provides security posture management and threat alerts, but it is not the primary raw log querying engine for granular access audits.
An investigator will access the Azure Portal, navigate to the Log Analytics workspace tied to the Key Vault's diagnostic settings, and execute a KQL query (e.g., AzureDiagnostics | where ResourceProvider =="MICROSOFT.KEYVAULT" | where OperationName == "SecretGet"). The results are then exported as CSV/JSON, hashed (SHA-256) to ensure preservation and chain of custody, and ingested into a centralized forensic timeline tool (like Plaso/Log2Timeline).
In cloud forensics, understanding the division between Control Plane and Data Plane is critical. The Control Plane manages the infrastructure (deploying a database, configuring a firewall), logged by Azure Activity Log/AWS CloudTrail. The Data Plane involves interacting with the data inside those resources (querying the database, reading a secret). Data Plane logs must explicitly be routed to diagnostic sinks like Azure Monitor Logs, and are the primary source for proving data exfiltration.
Enhance your digital forensics expertise with full-length CHFI practice scenarios.
Explore more CHFI simulations