DOE · DOE-693 · record R3549

COREII

Department of Energy · NE INL - NE Idaho National Laboratory (NE)

Overview

Development stage: PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: This AI system leverages Retreival Augmented Generation (RAG) enabled Generative AI over large corpuses of OT/ICS cybersecurity data and information to support decision making within critical infrastructure operations.
Start date: 2025-04-01 (day precision)Source: 2025-04-01T00:00:00
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Cybersecurity
Operational functions: Cyber threat detection Derived by keyword rules; see methodology

Problem the AI is intended to solve

Support decision making for critical infrastructure OT cybersecurity operations. Provides a secure environment where senstive data can be ingested and retreived reliably. Reduces the time it takes to perform threat analysis, supply chain analysis, kn

Expected benefits

Making information and knowledge easier to retreive and digest. Signficantly improves analysis time. Maximizes the transfer of knowledge to users of various backgrounds. Translates complex and complicated research results into accessible practical solutions.

System outputs

Distillation of research results and findings into pratical decision making information.

Technology

AI classification: Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
System name(s): Not reported
Custom-developed code: Yes
Public source code: Currently under SDR process and public release in progress. No URL available yet.

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
Vendor (as reported): 1899-12-31 11:59:00
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: No
Demographic features: Not reported
Training and evaluation data: The Large Language Model is a pretrained open source model but the Retreival Augemented Generation (RAG) engine retreives from the entire OSTI.gov corpus, Known Exploited Vulnerabilty (KEV) dataset, CyOTE Precursor Analysis Reports, CyOTE Observable Dataset, entire Energy Information Agency EIA.gov dataset, all CISA OT Advisories, and ARC Web Market Analysis Studies (Proprietary). This was a sample of the data that can be added to by future users.
Federal Data Catalog: yes

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported