AI-enhanced crime will expose DFIR practitioners who ignore AI.
If your work can end up in front of a jury, HR, outside counsel, or a regulator, this post applies to you.
I’m talking to the investigators who are aggressive enough to use the LLM, but smart enough not to blindly trust it.
The Critical Separation: In-the-Tool vs. Outside-the-Tool
Not all “AI” in DFIR is the same.
1. In the Tool (Embedded AI)
This is built into your forensic products (think ranking, labeling, or grouping data). It’s under the vendor’s control. It’s great for speed, but the risk is passive over-trust. Just because the tool labeled it "Highly Relevant" doesn’t mean it’s your smoking gun. It points to clues. That is all it does insofar as it affecting your investigation.
2. Outside the Tool (The Practitioner’s LLM)
This is a large language model such as ChatGPT, Gemini, or Claude used outside the forensic product. You direct it. You decide the task. It can help organize notes, compare theories, draft questions, improve report language, or assist with scripting. The risk here is active overtrust. It looks right, sounds right, and will fool you if you let it.
Same umbrella, but different things.
Casework is Human Work (The "AI Leash Rule")
If you neglect or ignore AI-enhanced casework, your capabilities are stunted. You will be outpaced. But using AI doesn't mean giving it the keys. In DFIR casework, your decisions affect liberty, liability, and livelihoods.
The AI’s leash should be short. Treat it like a "dumb terminal" with least privilege.
- AI should not make decisions.
- AI should not declare evidence.
- AI should not decide what is relevant.
- AI should not draw the final conclusion.
The second we act like the AI gets to decide "who did what," DFIR stops being investigative work and starts being tool worship. And we already have too much of that.
The AI as an Intern (Not an "All-Knowing Orb")
If you keep the LLM in its lane, it is the best intern you’ve ever had. It can:
- Organize chaotic rough notes into a readable timeline.
- Compare two competing theories and highlight which facts support which.
- Identify holes in your logic or timeline.
- Translate "Forensic-Speak" into plain English for a jury or HR.
- Draft better interview questions based on the evidence found.
It helps you think. It does not replace thinking.
The Cost of Getting It Wrong
If you give up your judgment, you aren't just hurting your reputation. You’re hurting real people.
- The wrong person gets arrested or fired.
- The guilty person walks or an innocent jailed.
- Your reputation and credibility gets shredded on the stand or in a deposition.
This is not just a criminal-case problem. Internal matters become legal matters without notice. What starts as a workplace issue can become outside counsel, a regulator, civil litigation, or a criminal referral.
Join the Webinar: The DFIR Investigator vs. The AI Investigator
I’m hosting a free webinar next week for the practitioners who want to use LLMs under control, in the real world, for actual casework. We’re going to talk about maintaining the DFIR Investigative Mindset in the age of GenAI.
If you've ever had a case from hell spiral because you didn't know what you should have known, this hour is for you.
We’ll cover:
- where AI actually helps in DFIR casework
- where practitioners are most likely to get burned
- how to use LLMs without being used by LLMs
- how to keep the investigator in charge and your casework unharmed (and your career!)
- the direction courts are going with AI (nearly a dozen US states are using LLMs in court cases right now!)
You’ll also get:
- Practitioner’s LLM Casework Cheatsheet
- AI as the Investigator, an excerpt chapter from the PSBK series
- Intro to MCP servers for DFIR and SOC investigations
- Documentation of attendance (Brett's tip: keep track of all your learning!)
A 24-hour replay will be available to those who registered (if you can't make it live, you'll have 24 hours to catch a reply, but only if you registered before the webinar starts (and make it before the 150 seats fill).