Python for OSINT: Tools and Techniques GSOA Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   On a Linux system, which built-in tool is commonly used to schedule Python scripts to run at defined intervals?

   • Acron
   • Bsystemctl
   • Ccurl
   • Dgrep
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2. 2application · medium

   An analyst has written a Python script that checks a news website for new articles every hour and sends a notification to a Slack channel when a new article is found. The script uses an API key for Slack and must run reliably on a Linux server. The analyst wants to ensure the script runs even after a server reboot. Which approach should be used?

   • AAdd a cron job that runs the script every hour, and store the Slack API key in an environment variable.
   • BCreate a systemd service that runs the script every hour and set it to restart on failure and enable it to start on boot.
   • CUse a Python while loop with time.sleep(3600) and run it in a terminal using nohup.
   • DSchedule the script with APScheduler inside the script and run it as a background process.
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4. 3application · medium

   A small OSINT team has a Python script that collects data from multiple public sources and writes results to a local SQLite database. The team now needs to share the collected data with a remote analyst who cannot access the local network. The script must continue to run on the original local machine, but the remote analyst needs read-only access to the latest data. Which approach is the most practical?

   • AChange the script to run on the remote analyst's machine instead of the local one.
   • BExport the SQLite database to a CSV file and email it to the remote analyst daily.
   • CModify the script to write to a cloud-hosted PostgreSQL database and have the remote analyst connect to it.
   • DSet up a VPN so the remote analyst can access the local SQLite database directly.
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5. 4foundation · easy

   An OSINT analyst wants to write a Python script that repeatedly fetches data from several public sources, normalizes the records, and then writes a summary report. Which Python library is specifically designed to simplify making HTTP requests and handling responses in such a workflow?

   • Aos
   • Bjson
   • Ccsv
   • Drequests
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6. 5expert · hard

   An analyst has a Python script that monitors a website for changes and sends alerts via email. The script uses a free email API that has a rate limit of 10 emails per hour. The analyst wants to run the script every 15 minutes, but is concerned about exceeding the email rate limit when multiple changes are detected. Which approach is the most appropriate?

   • AUse a different email API with a higher rate limit, even if it costs more.
   • BSend an email only when the script detects a change, and ignore the rate limit.
   • CAggregate detected changes into a single email and send it at most once per hour.
   • DSend an email for every detected change and rely on the API to queue excess emails.
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