Agentic and Generative AI for Open-Source Intelligence and Cyber Investigations: Taxonomy, Evaluation, Challenges, and Future Directions
arXiv:2607.03233v1 Announce Type: cross Abstract: The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intelligence, cybersecurity, and cyber investigation. Large language models (LLMs) and agentic AI systems, capable of tool use, multi-step reasoning, and iterative intelligence generation, have emerged as promising solutions, yet evaluation frameworks have not kept pace with reported capabilities. This survey systematically reviews 74 studies and makes four contributions. First, it establishes agentic
The rapid development and widespread adoption of large language models and agentic AI systems are pushing the boundaries of what is possible in intelligence gathering and cyber investigations, making this a critical juncture for systematic review.
This survey provides a much-needed taxonomy and evaluation framework for agentic AI in sensitive applications like OSINT and cyber investigations, directly impacting national security and corporate intelligence strategies.
The reliance on manual OSINT analysis will continue to diminish, replaced by increasingly sophisticated AI-driven systems capable of multi-step reasoning and iterative intelligence generation, fundamentally altering investigation methodologies.
- · AI development companies
- · Cybersecurity firms
- · Intelligence agencies
- · Government defence contractors
- · Manual OSINT analysts
- · Legacy cyber investigation tool providers
- · Organizations without AI adaptation strategies
Law enforcement and intelligence operations will become more efficient and capable of processing vast amounts of information.
The ethical and legal frameworks governing AI use in surveillance and investigations will require significant updates and international cooperation to prevent misuse.
The proliferation of advanced AI agents could lead to an AI arms race in cyber warfare, increasing the complexity and destructive potential of state-sponsored attacks.
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Read at arXiv cs.AI