Cybersecurity Firms Shift to GenAI Frameworks
A qualitative analysis of 25 documents spanning from 2022 to 2025 highlights how cybersecurity entities are evolving in response to generative AI by adjusting their threat modeling frameworks. This research, available on arXiv, outlines three main patterns of adaptation: the incorporation of LLMs for enhanced security, the use of GenAI frameworks for automating risk detection and response, and the integration of AI/ML in threat hunting. Organizations with well-established security systems, especially in finance and critical infrastructure, demonstrate greater preparedness due to effective governance, specialized AI teams, and significant investments. This transition signifies a departure from conventional signature-based approaches towards AI-enabled frameworks, shaped by security maturity, regulatory demands, and workforce capabilities.
Key facts
- Study examines 25 documents from 2022 to 2025
- Three adaptation patterns: LLM integration, GenAI frameworks, AI/ML for threat hunting
- Finance and critical infrastructure sectors show higher readiness
- Shift from signature-based to AI-capable frameworks
- Success factors include security maturity, regulation, and investment
- Published on arXiv with ID 2506.12060
- Qualitative research using systematic document analysis and comparative case study
- Organizations with mature infrastructures have structured governance and dedicated AI teams
Entities
Institutions
- arXiv