OSINT Clinic: Co-designing AI-Augmented Collaborative OSINT Investigations for Vulnerability Assessment

Small businesses need vulnerability assessments to identify and mitigate cyber risks. Cybersecurity clinics provide a solution by offering students hands-on experience while delivering free vulnerability assessments to local organizations. To scale this model, we propose an Open Source Intelligence (OSINT) clinic where students conduct assessments using only publicly available data.We enhance the quality of investigations in the OSINT clinic by addressing the technical and collaborative challenges. Over the duration of the 2023-24 academic year, we conducted a three-phase co-design study with six students. Our study identified key challenges in the OSINT investigations and explored how generative AI could address these performance gaps. We developed design ideas for effective AI integration based on the use of AI probes and collaboration platform features. A pilot with three small businesses highlighted both the practical benefits of AI in streamlining investigations, and limitations, including privacy concerns and difficulty in monitoring progress.

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713283
Citations
3
Primary Topic
Mobile Crowdsensing and Crowdsourcing
Type
article
Field-Weighted Citation Impact
5.08
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article

OSINT Clinic: Co-designing AI-Augmented Collaborative OSINT Investigations for Vulnerability Assessment

Kurt Luther, Anirban Mukhopadhyay
3 citations
Mobile Crowdsensing and Crowdsourcing
5.08
article

OSINT Clinic: Co-designing AI-Augmented Collaborative OSINT Investigations for Vulnerability Assessment

Kurt Luther, Anirban Mukhopadhyay
article en
3 citations

Abstract

Small businesses need vulnerability assessments to identify and mitigate cyber risks. Cybersecurity clinics provide a solution by offering students hands-on experience while delivering free vulnerability assessments to local organizations. To scale this model, we propose an Open Source Intelligence (OSINT) clinic where students conduct assessments using only publicly available data.We enhance the quality of investigations in the OSINT clinic by addressing the technical and collaborative challenges. Over the duration of the 2023-24 academic year, we conducted a three-phase co-design study with six students. Our study identified key challenges in the OSINT investigations and explored how generative AI could address these performance gaps. We developed design ideas for effective AI integration based on the use of AI probes and collaboration platform features. A pilot with three small businesses highlighted both the practical benefits of AI in streamlining investigations, and limitations, including privacy concerns and difficulty in monitoring progress.

Virginia Tech (US)
Openalex Percentile: Top 5%
Mobile Crowdsensing and Crowdsourcing
5.08
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