Attackers are already using AI, but you can return fire by deploying your own AI-powered cyber security tools. Turning to general use LLMs like ChatGPT or DeepSeek is not an option for security management as they are not specialized for network security and risk exposing sensitive data. But enterprise-grade, purpose built GenAI assistants and AI agents have the potential to provide all the benefits of GenAI to help you stay ahead of AI-powered attacks, without exposing your organization to the inherent risks of using general purpose GenAI tools.
The benefits of GenAI assistants include streamlining operations, saving time and costs, and improving security outcomes. They can analyze unprecedented volumes of data, spot patterns, extract insights, generate content and recommendations, all while engaging with users in a conversational manner. Based on learned data patterns, GenAI assistants can create and deliver new outputs that align with the context and address the prompts they receive, providing relevant suggestions, answering complex questions, and creating high-value content in just moments. A GenAI cyber security assistant or agent can work like an always-on virtual team member who is available on-demand to provide real-time, accurate insights and perform a wide range of tasks with speed and accuracy, from incident investigation, to analysis, playbook automation, threat hunting, and more.
Key Benefits of GenAI Security Management Assistants:
- Automate complex security tasks: From threat hunting to incident analysis, GenAI manages routine and advanced operations.
- Accelerate response times: AI-powered insights reduce investigation time and streamline decision-making.
- Enhance team efficiency: By reducing manual workloads, security professionals can focus on high-priority threats.
- Improve security posture: Organizations can proactively defend against evolving cyber threats with AI-driven intelligence.
While GenAI assistants and agents offer remarkable potential to enhance security management, it is critical to approach their implementation with certain security considerations in mind. To prevent data from being breached or leaked, you need to ensure a closed data processing environment protected from unauthorized access. Another vulnerability common to LLMs is that they extract data to use in further training the models. Using synthetic data and Retrieval Augmented Generation (RAG) can prevent unauthorized extraction and use of sensitive data. These and other robust security controls are required for responsible use of GenAI assistants and agents to manage enterprise security.
Safely Discover the Power of GenAI in Security Management
As a cyber security leader, you are constantly seeking to implement new technologies to give you the edge over would-be attackers, but implementing new technology requires precautions to avoid unintentional exposure. To help navigate the adoption of GenAI assistants and agents for security management Check Point experts developed an eBook available for download: Transforming Security Management with GenAI-Powered Assistants’
