Python for OSINT: Tools and Techniques GSOA Practice Questions (Page 5)

Questions 21–25

1. 21foundation · easy

   In a Python OSINT automation script, which component is responsible for turning raw collected data into a structured format that can be easily analyzed or stored?

   • AHTTP client
   • BScheduler
   • CLogger
   • DData processing module
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2. 22foundation · easy

   Which data format is commonly used in Python OSINT scripts to store structured data that includes nested fields, making it easy to read and write with the built-in json library?

   • ABinary
   • BPlain text
   • CCSV
   • DJSON
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4. 23expert · hard

   An OSINT analyst is building a Python workflow that collects data from a social media API, a news API, and a public dataset. The analyst wants to generate a daily report that combines data from all three sources. The workflow must be reproducible and run automatically every day. Which approach is the most maintainable?

   • AUse a workflow orchestration tool like Apache Airflow to define the tasks and dependencies.
   • BWrite a single monolithic script that calls all three APIs and generates the report.
   • CRun the script manually each day and save the report to a shared drive.
   • DUse a series of shell scripts that call Python scripts for each source and combine the outputs.
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5. 24foundation · easy

   An OSINT analyst wants to run a Python script on a schedule in the cloud without managing a virtual machine. Which cloud service model is most appropriate for this task?

   • AFunction-as-a-Service (FaaS)
   • BInfrastructure-as-a-Service (IaaS)
   • CPlatform-as-a-Service (PaaS)
   • DSoftware-as-a-Service (SaaS)
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6. 25application · medium

   An OSINT analyst has a Python script that collects data from a social media API and stores results in a local CSV. The analyst needs to run this script daily at 2 AM, but the local machine is not always on. The analyst has access to an AWS account and wants to move the script to the cloud. Which approach is the most reliable?

   • AUpload the script to an AWS EC2 instance and use a cron job to run it daily at 2 AM.
   • BPackage the script as an AWS Lambda function and trigger it with a CloudWatch Events rule at 2 AM daily.
   • CStore the script in an S3 bucket and manually run it from the AWS console when needed.
   • DUse AWS Batch to run the script, but only when the analyst manually submits a job.
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