Cybersecurity AI (CAI) Dataset

Computer Science > Cryptography and Security [Submitted on 27 May 2026] Cybersecurity AI (CAI) Dataset Víctor Mayoral-Vilches We present CAI Dataset, a fourteen-month corpus of cybersecurity LLM trajectories collected through the open-source CAI agent framework, built in response to PentestGPT's finding that expert operator trajectories, not base-model capability, are the bottleneck for cybersecurity LLM performance. CAI Dataset aggregates 230,935 session logs and 26,027,742 user prompts from 16,768 source IPs across 123 countries, exercising 4,187 unique LLM identifiers against 23,147 target domains over 18.07 TB of durable storage. The mix is hands-on (36.4% offensive, 20.1% attacker-intent, 27.5% business / integration, 4.4% defensive), making CAI Dataset, to the best of our knowledge, the largest described corpus of LLM-driven hacker trajectories. It is released to partner organisations and selected customers as an audience-size series (CAI Dataset10, CAI Dataset1k, CAI Dataset200k). Read longitudinally, the corpus is a record of cybersecurity itself turning automated: operators routinely paste live credentials, production hostnames and bearer tokens into prompts knowing their inputs are logged, a trade-off they accept to stay competitive. Aggregated across the industry, this concentrates a substantial fraction of the world's offensive and defensive operator context inside a handful of frontier-model API providers, a single failure surface whose breach or politically motivated repurposing could cascade into nation- and enterprise-scale disruption. The only configuration that preserves both the productivity advantage and operator-side confidentiality is an on-premise, privately-hosted cybersecurity-specialised LLM served inside the operator's trust boundary, which CAI Dataset is shaped to make practical. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2605.28146 [cs.CR]   (or arXiv:2605.28146v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2605.28146 Focus to learn more Submission history From: Víctor Mayoral Vilches [view email] [v1] Wed, 27 May 2026 08:29:28 UTC (128 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)