AI in DFIR 101: Why You Should Use AI for Planning

Investigation planning involves translating core questions into specific data collection and analysis strategies. This process generally follows three phases: searching for existing playbooks, creating new plans when none exist, and customizing those plans for the specific environment, such as adding known IP addresses or hostnames. While deterministic tools—including SOAR platforms and search engines—are effective for keyword-based retrieval and simple substitutions, they lack the ability to generate new mappings between questions and data sources.
Generative AI provides value by filling these gaps, specifically in the creation phase where it can leverage broad knowledge to suggest evidence sources. It also serves as a fallback during search and customization phases when documentation is incomplete or keywords do not exactly match. There is a trade-off between the high defensibility of manual or deterministic processes and the speed and creativity offered by AI, which requires more verification to ensure logical coverage.

* The planning phase of an investigation converts questions into data collection lists and analysis ideas.
* Malware investigation questions include data exfiltration, persistence installation, and credential theft.
* Exfiltration data sources include process history, browser history, and firewall logs.
* Persistence data sources include triggered tasks.
* Credential data sources include process history and authentication logs.
* The planning process consists of three phases: playbook search, playbook creation, and playbook customization.
* Four task options exist: manual, validated deterministic tools, non-validated deterministic tools, and direct GenAI output.
* Deterministic tools are used for keyword matching in SOAR or OpenSearch.
* GenAI is used for non-exact keyword matches and mapping questions to data sources.
* Cyber Triage is a tool that uses deterministic approaches to automate collection and analysis.
* Cyber Triage provides a 7-day evaluation.

This is an educational framework for integrating GenAI into Digital Forensics and Incident Response (DFIR). The strongest version of this narrative is that AI should not replace the investigator but should act as a "knowledge supplement" to ensure comprehensive evidence collection, specifically in the "creation" gap where deterministic tools cannot function.
The narrative follows a classic vendor-led educational funnel: it establishes a conceptual problem (the rigidity of playbooks), proposes a methodology for a solution (the three-phase AI integration), and then positions a specific product (Cyber Triage) as the current deterministic baseline that will soon evolve to include these AI capabilities. Because the piece uses its own conceptual framework to validate the necessity of AI, and then points toward its own product as the vehicle for this evolution, it engages in a subtle Authority Game.
Patterns detected: ARC-0031 Authority Game
The driving paradigm is the transition from "Static Defense" (fixed playbooks) to "Adaptive Response" (AI-assisted planning). This echoes the broader shift in cybersecurity toward "AI-driven" operations, where the assumption is that the volume and complexity of threats have outpaced human memory and manual documentation.
The implication for human agency is a shift from *knowledge retrieval* to *knowledge verification*. The investigator moves from being the source of the plan to the auditor of an AI-generated plan. While this increases speed, it risks "automation bias," where a junior analyst might trust a GenAI-suggested data source without understanding why it is relevant.
Bridge Questions:
1. If an AI suggests a data source based on "vast knowledge" but the investigator cannot explain the logic, is the process still legally defensible in court?
2. How does the reliance on AI for "creative" planning affect the development of intuition and expertise in junior SOC analysts?
Counterstrike Scan: A coordinated influence campaign would use "educational" content to create a perceived deficiency in current manual workflows, then offer a proprietary tool as the only scalable solution. While this content has a vendor CTA, it remains primarily a helpful conceptual guide rather than a manufactured crisis.