10 ways SecOps teams can strengthen cybersecurity with ChatGPT
Find out how spending on ChatGPT-based solutions strengthens the business case for zero-trust security and enhances risk management from the board’s perspective. CISOs recommend evaluating cybersecurity vendors with large language models (LLMs) rather than using ChatGPT itself due to confidentiality risks. Explore options like Airgap Networks’ Zero Trust Firewall (ZTFW) with ThreatGPT, Cisco Security Cloud, CrowdStrike, Google Cloud Security AI Workbench, Microsoft Security Copilot, and more.
Here are 10 ways ChatGPT is helping SecOps teams bolster cyber-defenses against increasing attacks, including a 40% rise in ransomware incidents over the past year.
1. Detection engineering is proving to be a strong use case
CISOs running pilots find that ChatGPT effectively automates baseline detection engineering tasks, allowing SecOps teams to focus on investigating complex alert patterns. LLMs learn from real versus false-positive alerts and threats, enabling accurate detection and response.
2. Improving incident response at scale
ChatGPT provides actionable guidance for incident response, offering accurate recommendations based on real-time data. Contextual accuracy is crucial, and training the model extensively helps achieve better results. Automating recurring incident response tasks frees up time for SecOps team members.
3. Streamlining SOC operations at scale to offload overworked analysts
ChatGPT assists overworked SOC analysts by automatically analyzing cybersecurity incidents and providing recommendations for immediate and long-term responses. It also helps with risk assessments, advising IT and security teams, employee training, and improving learning retention rates.
4. Work hard towards real-time visibility and vulnerability management
ChatGPT trained on real-time data offers vulnerability reports that list known threats or vulnerabilities across the organization’s network. These reports can be ranked by risk level, action recommendations, and severity, providing valuable insights for vulnerability management.
5. Increasing accuracy, availability, and context of threat intelligence
ChatGPT predicts potential threat and intrusion scenarios by analyzing real-time monitoring data and leveraging the knowledge base created by LLMs. It aims to differentiate between false positives and actual threats, providing contextualized insights to SOC analysts.
6. Identifying how security configurations can be fine-tuned and optimized for a given set of threats
ChatGPT helps identify and recommend configuration improvements by interpreting data indicators of compromise (IoCs). This is crucial in minimizing false positives caused by suboptimal configurations, reducing the risk of breaches.
7. More efficient triage, analysis, and recommended actions for alerts, events, and false positives
Generative AI-based platforms like ChatGPT significantly reduce the time wasted on resolving false positives, allowing SOC analysts to focus on genuine threats. Studies have shown the extensive time and resources wasted on validating unreliable vulnerability alerts and false positives.
8. More thorough, accurate, and
8. More Thorough, Accurate, and Secure Code Analysis
ChatGPT continues to impress cybersecurity researchers with its ability to handle complex secure code analysis. In a comprehensive test conducted by Victor Sergeev, ChatGPT successfully identified suspicious service installations without any false positives. It even provided a valid hypothesis that the code was being used to disable logging or other security measures on a Windows system.
Sergeev went a step further by infecting a target system with the Meterpreter and PowerShell Empire agents and emulating typical adversary procedures. The scanner, enriched with ChatGPT conclusions, successfully identified two malicious running processes out of 137 benign processes, with no false positives.
9. Improve SOC Standardization and Governance, Contributing to a More Robust Security Posture
CISOs emphasize the importance of improving standardization of SOC processes and procedures, alongside enhancing visibility across diverse and disparate tools. Consistent workflows that can adapt to changes in the security landscape are crucial for staying ahead of security incidents.
As the CISO of a company in the electronics industry producing microcomponents puts it, the goal is to “get our standardization act together and ensure no IP is ever compromised.”
10. Automate SIEM Query Writing and Daily Scripts Used for SOC Operations
Automating the creation and updating of security information and event management (SIEM) queries can significantly benefit SOC analysts. These queries are essential for analyzing real-time event log data and identifying anomalies. By leveraging generative AI and ChatGPT-based cybersecurity, SOC analysts can save valuable time, potentially freeing up at least a day and a half a week.
ChatGPT’s Potential to Improve Cybersecurity is Just Beginning
In the second half of 2023, we can expect to see more ChatGPT-based cybersecurity platforms being launched, including one from Palo Alto Networks. Palo Alto Networks’ CEO, Nikesh Arora, hinted at the company’s earnings call that they see a significant opportunity in embedding generative AI into their products and workflows. Additionally, the company plans to deploy a proprietary Palo Alto Networks security LLM in the coming year.
This period will witness a surge in new product launches aimed at streamlining SOCs and closing the identity-endpoint gap that attackers continue to exploit. The exciting part is how generative AI platforms, analyzing telemetry data, will provide innovative product and service ideas. Endpoints and the data they analyze are fueling these innovations, and the same holds true for generative AI platforms relying on ChatGPT to provide quick and accessible insights to security professionals.
