10 ways SecOps can Strengthening cybersecurity with ChatGPT

10 ways SecOps can Strengthening cybersecurity with ChatGPT

Attackers are constantly changing their tactics, automating attacks on numerous endpoints, and using whatever available technique to get past the cyber defenses of their targets, as seen by security operations teams. Their agility is astonishing, allowing them to take advantage of occasions like holidays as excellent times to compromise an organization’s cybersecurity safeguards, for example. As a result, SecOps teams struggle with burnout, alert fatigue, and a lack of work-life balance while working nonstop around the clock, including on weekends and holidays. As brutal as it sounds, reality is.

The CISO of a well-known insurance and financial services company recently discussed the difficulties SecOps teams face with VentureBeat: “Given that hackers constantly change their attack techniques, SecOps teams face immediate and ongoing pressure to protect our company from evolving risks. In my experience, it requires twice as much or more work to stop a smaller number of invasions when overworked teams rely on isolated technology.

Addressing the SecOps Gap with ChatGPT:

Scaling old systems, each of which produces different kinds of alerts, alarms, and real-time data streams, is a big problem for leaders of SecOps teams. The most worrying and abused of the multiple gaps resulting from this lack of integration is the inability to ascertain whether a particular identity has the necessary credentials to reach a given endpoint and, if so, for how long. The future of zero trust is being shaped by systems that integrate identities and endpoints, and ChatGPT has the ability to close identity-endpoint gaps and secure other weak places in the network.

Attackers are sharpening their skills to take advantage of these weaknesses. SecOps teams are aware of this and have strengthened their defenses as a result. The implementation of least-privileged access, recording and monitoring all endpoint actions, enforcing authentication procedures, and removing zombie credentials from Active Directory and other identity and access management (IAM) platforms are some of the methods included in this list. Since IDs are a popular target for attackers, CISOs must be cautious in keeping up-to-date and reliable IAM systems to fend off threats.

SecOps teams also have to overcome additional obstacles like improving threat intelligence, giving real-time visibility of threat data across all security operations centers (SOCs), lowering the number of false positives and alerts, and combining various tools. ChatGPT has already demonstrated its value in strengthening cybersecurity for SecOps teams in several domains.

Consolidating Disparate Tools to Bridge the Identity-Endpoint Gap:

Closing the identity-endpoint gap requires the convergence of different tools because it provides consistent visibility into all danger surfaces and potential attack routes. According to CrowdStrike’s Kapil Raina, Vice President of Zero Trust, Identity, Cloud, and Observability, “Many customers are looking for a centralized strategy owing to financial and staffing restrictions. They find it difficult to manage the complexity of many different systems and technologies. He continues, “Customers have benefited from cost reductions through consolidation, improving insight into their attack story. By lowering internal operational risks and overhead that might otherwise slow response time, their threat graph becomes easier to act upon.

Insights from Piloting AI and ChatGPT in SecOps:

CISOs who have tested and implemented ChatGPT-based SecOps solutions have learned a lot. They stress the value of robust data governance and sanitization, even if it means postponing internal tests or launch. They also emphasize how important it is to choose use cases that are most helpful in achieving business goals and to decide how these contributions will be evaluated. Finally, they urge the use of recursive workflows and tools that can validate the warnings and problems produced by ChatGPT and separate out false positives from actionable things.

10 Ways to Strengthen Cybersecurity with ChatGPT:

It is crucial to assess how investing in ChatGPT-based solutions will affect the financial viability of zero-trust security and risk management. Leading CISOs in the financial services industry suggest looking into cybersecurity suppliers using large language models (LLMs), but they warn against using ChatGPT directly owing to the possibility of confidentiality being compromised by the retention of all data, information, and threat analyses.

By combining graph databases and GPT-3 models, Airgap Networks, for instance, has developed the Zero Trust Firewall (ZTFW) with ThreatGPT to give SecOps teams additional threat insights. In order to detect security concerns, GPT-3 models analyze natural language questions, while graph databases provide contextual information on endpoint traffic links. Other choices include Zscaler, Mostly AI, Recorded Future, SecurityScorecard, SentinelOne, Veracode, CrowdStrike’s Charlotte AI (available on the Falcon platform), Google Cloud Security AI Workbench, Microsoft Security Copilot, and Cisco Security Cloud. During Zenith Live 2023 in Las Vegas, Zscaler recently announced three generative AI projects in preview.

Here are 10 ways ChatGPT helps SecOps teams boost their cyber defenses, particularly in the face of the growing threat posed by ransomware assaults, which have grown by 40% in the last year.

1. Detection engineering is proving to be a strong use case: For ChatGPT, detection engineering is a useful use case. SecOps teams can distinguish between genuine threats and false positives because to its real-time threat detection and response capabilities. ChatGPT frees SecOps personnel to concentrate on analyzing complex warning patterns by automating baseline detection engineering duties.

2. Improving incident response at scale: ChatGPT has successfully enhanced incident response. It offers precise and effective advice for handling security problems during testing. Contextual accuracy is essential, particularly in complicated settings, and training the model with more detailed contextual references improves outcomes. Tasks related to incident response that were previously handled manually can now be completed by SecOps team members more quickly.

3. Streamlining SOC operations at scale to offload overworked analysts: To relieve the burden on overburdened security operations center (SOC) analysts, a top insurance and financial services company is launching a proof of concept (PoC) using ChatGPT. The objective is to automate the study of cybersecurity occurrences, present risk evaluations for various scripts, and provide suggestions for immediate and long-term actions. Additionally, ChatGPT is being evaluated to provide IT and security organizations with guidance on security procedures, staff training, and raising learning retention rates.

4. Work hard towards real-time visibility and vulnerability management: It can be difficult to achieve greater visibility across several SOC tools, but ChatGPT is trained on real-time data to produce vulnerability reports. These reports list every threat or vulnerability across the network of a company that has been identified and discovered. If data is used to train the language models (LLMs), they can be graded according to risk level, action recommendations, and severity.

5. Increasing accuracy, availability and context of threat intelligence: By examining real-time monitoring information from business networks, ChatGPT forecasts potential attack and intrusion scenarios. ChatGPT assists in distinguishing between false positives and real threats when used in conjunction with LLM knowledge sets that are constantly expanding. The initial tests have yielded encouraging outcomes in terms of processing substantial amounts of threat intelligence data and giving pertinent insights to SOC analysts in real-time.

6. Identifying how security configurations can be fine-tuned and optimized for a given set of threats: The use of ChatGPT makes it easier to find and suggest security configuration upgrades. It reduces false positives brought on by poor settings by evaluating data indicators of compromise (IoCs). The capacity of ChatGPT to fine-tune configurations is essential for enhancing cybersecurity because manual configuration errors are a major contributor to breaches.

7. More efficient triage, analysis and recommended actions for alerts, events and false positives: The time lost on false positives, a major problem in SOC operations, is greatly reduced via ChatGPT. Pilot programs have proven that generative AI made available through ChatGPT significantly reduces the resolution time for false positives. According to studies, SOC analysts waste a lot of time on false positives, therefore this efficiency gain is quite important.

8. More thorough, accurate and secure code analysis: The secure code analysis capabilities of ChatGPT, including the detection of malicious processes and dubious service installations, have been successfully tested. These tests show that ChatGPT can analyze complicated code and deliver precise results without producing false positives. The technology is effective in locating potential security flaws.

9. Improve SOC standardization and governance, contributing to a more robust security posture: Maintaining a strong security posture requires standardizing SOC operations and procedures. As important as increasing visibility across many tools is, ChatGPT helps to improve SOC uniformity. Organizations are better able to prevent security events and safeguard intellectual property when they have consistent routines that can alter to reflect changes in the security landscape.

10. Automate SIEM query writing and daily scripts used for SOC operations: The generation and updating of security information and event management (SIEM) queries is made easier using ChatGPT. These queries take up a large percentage of the time that SOC analysts spend on them, thus automating their generation frees up time that may be used for other duties. Within the SOC, this automation increases productivity and efficiency.

ChatGPT’s potential to improve cybersecurity is just beginning:

We may anticipate the launch of several cybersecurity solutions based on ChatGPT technology in the following months of the second half of 2023. During the most recent earnings call, CEO Nikesh Arora said that Palo Alto Networks would be launching one of these platforms. Arora emphasized his enthusiasm for the “significant opportunity” they saw by integrating generative AI into their operations and products. In the upcoming year, Palo Alto Networks also plans to adopt their own security LLM (Long-Long-Model).

A rise in product releases aimed at streamlining Security Operations Centers (SOCs) and addressing the risk posed by attackers exploiting the identity-endpoint gap is anticipated for the second half of 2023.

The richness of insights obtained from telemetry data analysis through generative AI platforms is what makes this field particularly exciting. These revelations will open the door for creative product and service ideas. Advancements in the discipline are being accelerated by endpoints and the data they assess. Undoubtedly, ChatGPT-based generative AI technologies will have a significant impact on how easily and quickly these insights are made available to security experts.



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