Digital ForensicsDigital ForensicsDigital Forensics

Examples of everyday tasks

• Create or verify copies of evidence and record their hash values.
• Extract artifacts such as browser history, file details, and system logs.
• Build timelines of user and program activity.
• Explain where the evidence is strong, weak, or missing.
• Write reports that people without a technical background can follow.

Related job titles

• Digital forensic analyst
• Forensic examiner

These are career areas to explore, not a checklist. Some of these job titles usually require experience, and completing a starter project does not by itself make someone ready for them.

Starter project

Reconstruct an Incident Timeline

Use a practice disk image or supplied evidence files. Record the evidence examined and reconstruct the sequence of events.

What you’ll use

• A practice disk image or evidence files published for training
• A free forensic tool such as Autopsy, or the tools recommended with the practice case
• A spreadsheet for the evidence inventory and timeline

Resources to start with

• Digital Corpora (opens in a new tab)

  Freely available disk images and practice scenarios created for digital forensics education and research.

• Autopsy (opens in a new tab)

  A free, open-source digital forensics platform for examining disk images.

More projects for this path

Each one comes with the framework to follow, five name ideas and a walkthrough for publishing it on GitHub.

• Incident Timeline Reconstruction

  Rebuild what happened on a practice disk image, artifact by artifact.

• Browser Artifact Review

  Reconstruct a browsing session from history, downloads and cache in a practice image.

• USB Device Usage Review

  Work out which removable devices were used, when, and what that does and does not prove.

Project walkthrough

1. Read the practice case description and write down the questions you are trying to answer.
2. Record each evidence item in an inventory: its name, where it came from, its hash value if provided, and what it contains.
3. Extract relevant artifacts, such as file timestamps, browser history, and log entries.
4. Place each event on a timeline with its timestamp, its source, and what it shows.
5. Check time zones and gaps so events from different sources line up correctly.
6. Write your reconstruction, marking what the evidence confirms and what you are inferring.
7. List the limitations, such as missing logs or timestamps that could have been changed.

What to publish

• An evidence inventory
• The reconstructed timeline
• Supporting screenshots of key artifacts
• The limitations of the evidence and of your analysis
• The name and source of the practice case you used

Optional extension

Explain where two evidence sources agree or conflict.

Example résumé bullet

Numbers are what make a bullet worth reading, so count them while you work: how much data you searched, how many findings you fixed, how many tests you added. Every figure should be one a reader can find in your report. Write the line after the work is done, and leave out impact or experience you cannot show.

Numbers to record while you work

Project name | tools, datasets and frameworks | link

Give the project a name of its own: “Lantern” is an example, not a label to copy. List the tools, datasets and frameworks you actually used, since several relevant ones show more than a single tool does. Hyperlink the last part to your published repository or report.

Turn your project into a portfolio piece

A project becomes easier to evaluate when someone can understand what you did, inspect the evidence, and follow your reasoning.

Create a short report, GitHub README, or portfolio page. A clear two-to-four-page report is a useful starting point, not a strict requirement.

Include:

1. Goal: What question or problem did you investigate?
2. Environment: What tools, practice data, or systems did you use?
3. Your work: What did you personally do, and why?
4. Evidence: Include useful screenshots, queries, code, or test results.
5. Findings: What did you discover? What remains uncertain?
6. Fix or recommendation: What should change, and did you test it?
7. Sources and limitations: Credit datasets and guides. Clearly identify simulated work.

Use sample or redacted information in the public version.

Publish the report somewhere accessible without requesting permission, and check the link before putting it on a résumé.

Put numbers in it

Count as you work, and put the figures in the report: records searched, findings confirmed, tests added, checks failing before and after. A reviewer can check every one of them against your evidence, which is exactly why they are worth including. Leave out business impact you cannot show.

Name it, then show your tools

A résumé line works best in three parts: your project’s own name, the tools and frameworks you used, and a link to the work. “Role-Based Access Lab” reads like a class exercise. A name plus a tool list tells a reviewer what you can actually work with, and every tool, dataset or framework you list honestly is another thing an interviewer can ask you about.

Project name | tools, datasets and frameworks | link

• Role-Based Access Lab→Turnstile | Keycloak, RBAC design, NIST SP 800-63, Docker | GitHub
• Login Hunt→Beacon | Python, pandas, Sigma, MITRE ATT&CK | GitHub
• Cloud Project→Bedrock | Terraform, Checkov, AWS IAM, CIS Benchmarks | GitHub

Why link a report?

Your résumé gives a short description of the project. The linked report lets a reviewer inspect your work and gives you concrete evidence and decisions to discuss during an interview.

Not every recruiter will open it, but it makes your work available for review.

Hyperlink the last part to the published work, so “GitHub” or “Project Report” opens your repository or report. Check the link before you send the résumé.

# Project title

> Practice project. Describe the simulated scenario, practice data, or lab used.

## Goal
What question or problem did you investigate?

## Environment
What tools, practice data, or systems did you use? Link datasets and guides.

## My work
What did you personally do, and why?

## Evidence
Screenshots, queries, code, or test results. Use sample or redacted information only.

## Findings
What did you discover?
The numbers behind it (records searched, findings confirmed, tests added).
What remains uncertain?

## Fix or recommendation
What should change, and did you test it?

## Sources and limitations
- Datasets and guides used:
- What was simulated:
- Limitations:

Related paths to explore

• Incident Response

  Incident responders take charge when a security incident is confirmed: they limit the damage, remove the attacker’s access, restore systems, and help the organization learn from what happened.

• Malware Analysis

  Malware analysts study malicious software to understand what it does, how to detect it, and how to defend against it.

• Threat Hunting / Detection

  Threat hunters search activity records for attackers that existing alerts missed, and detection engineers turn what they learn into rules that catch the behavior automatically.