Discover the Latest Generative AI Products and Services from Top Cybersecurity Vendors
Are you curious about the latest generative AI products and services from top cybersecurity vendors? Look no further! NeuralNation has compiled a list of the most innovative and cutting-edge offerings from companies like Cisco, Google, and Microsoft.
Airgap Networks is one of the top 20 startups to watch in zero trust, and their Zero Trust Firewall (ZTFW) platform with ThreatGPT is a prime example of how DevOps teams are leveraging generative AI to add value for prospects and customers. Meanwhile, CrowdStrike’s deep AI and machine learning expertise is reflected in every aspect of their product and services strategy, including their latest product, Charlotte AI, a generative AI security analyst.
But that’s not all! Veracode has launched Veracode Fix, a generative AI-based product that uses AI to make suggestions for making software more secure, while Zscaler has announced three generative AI projects in preview at its Zenith Live 2023 event. And that’s just the tip of the iceberg!
Follow NeuralNation’s ongoing generative AI coverage to stay up-to-date on the latest developments in this exciting field!
The world of cybersecurity is constantly evolving, and generative AI is at the forefront of this revolution. With its ability to detect anomalies faster than current technologies, parse logs in real-time, and simulate attack patterns, generative AI is changing the game. We spoke with over a dozen cybersecurity leaders, including Airgap Networks’ CEO Ritesh Agrawal and CrowdStrike’s president Michael Sentonas, to identify the top five ways generative AI is impacting current and future product strategies.
Firstly, generative AI is enabling real-time risk assessment and quantification, allowing CIOs and CISOs to better manage risk and prioritize costs. This skill set is becoming increasingly valuable, and leading cybersecurity vendors are already incorporating generative AI into their platforms to train models and capture telemetry data.
Secondly, generative AI is revolutionizing extended detection and response (XDR) platforms, contextualizing massive amounts of telemetry data and eliminating data silos. This is a game-changer for XDR providers like CrowdStrike, Microsoft, and Palo Alto Networks.
Thirdly, generative AI is improving endpoint resilience and self-healing capabilities, allowing endpoints to turn themselves off, recheck OS and application versioning, and reset to an optimized, secure configuration autonomously. This is a significant source of innovation, and providers like Absolute Software, BlackBerry, and McAfee are leading the way.
Fourthly, generative AI is improving existing AI-based automated patch management techniques, prioritizing vulnerabilities by patch type, system, and endpoint. This is why vendors are fast-tracking generative AI improvements, and leading providers like Ivanti and Tanium are already incorporating it into their platforms.
Finally, generative AI is improving contextual intelligence and prediction accuracy, allowing IT and security teams to focus on strategic initiatives for the business. With over 160,000 vulnerabilities currently identified, the future of security is offloading mundane and repetitive tasks to AI copilots. The possibilities are endless, and the cybersecurity industry is only just scratching the surface of what generative AI can do.
Revolutionizing AI Tools for Cybersecurity
As CIOs and CISOs continue to brief their boards on generative AI, managing and monitoring models and chatbot services has become a top priority. Cybersecurity vendors like Airgap Networks, CrowdStrike, Cyberhaven, Microsoft Security Copilot, SentinelOne, and Zscaler have already announced their available tools. However, more vendors are expected to create and fine-tune private LLMs that will require tools for improving the accuracy and precision of model results. Zscaler, for example, is focusing on prompt engineering to address this issue, as it previewed at its recent Zenith Live 2023 event.
The Double-Edged Sword of Generative AI in Cybersecurity
At Zenith Live 2023, NeuralNation conducted interviews with Zscaler’s senior management team and customers, including CIOs and CISOs. They all pointed to a paradox they are facing: How can generative AI deliver exceptional productivity while risking the release of intellectual property and confidential company information into public models like OpenAI’s? Syam Nair, Zscaler’s CTO, addressed this issue early in their keynotes.
Nair reassured the audience that Zscaler’s ZTX platform, combined with the core of zero trust designed into the platform, was how the company plans on securing customers’ data and privacy. He explained how they could better ensure their data’s security: “This is where zero trust and the need for zero trust for AI applications comes into being.”
Designing in zero trust, starting with identity, was a common theme at Zscaler Live 360. Zscaler is focused on capitalizing on its own LLMs’ real-time insights and versatility to strengthen zero trust across its platform.
With the rise of generative AI in cybersecurity, companies are facing a double-edged sword. While it can deliver exceptional productivity, it also risks the release of confidential information into public models. Zscaler is one of the cybersecurity vendors that has already announced tools to manage and monitor models and chatbot services. They are also focusing on designing in zero trust, starting with identity, to better ensure their customers’ data’s security. As more vendors fine-tune their private LLMs, we can expect to see more tools for improving the accuracy and precision of model results.
Generative Artificial Intelligence (AI) has long been a part of our lives, but it’s only recently that we’ve seen it being used in cybersecurity to enhance precision and accuracy. Many industries are already leveraging the power of AI to detect threats, identify malicious activity, and prevent cyberattacks. Here are five ways generative AI can help improve cybersecurity precision.
1. More Accurate Detection
Generative AI is capable of analyzing data for anomalies that indicate malicious or suspicious activity. With the ability to quickly process large volumes of data, AI can identify patterns more accurately than traditional cybersecurity methods. This is especially beneficial for spotting new or previously unknown threats.
2. Faster Response Times
Generative AI is able to detect threats faster than ever before. This means that cybersecurity professionals will be able to respond to threats much more quickly and reduce the potential impact of a cyberattack. Faster response times also enable more proactive measures, allowing for earlier detection of potential threats.
3. Improved Usability
Generative AI has the potential to simplify and speed up cybersecurity processes. This will make it easier and faster for cybersecurity professionals to carry out their tasks and reduce the risk of errors. Additionally, AI-enabled solutions are designed to be easy to use and will require minimal training.
4. Reduced False Positives
With a more precise approach to security, generative AI can reduce the number of false positives, or incorrect identifications of threats. This will help streamline security processes, as well as reduce the time and resources required for manual review and resolution.
5. Better Security Posture
Given the ability of generative AI to quickly detect, analyze, and respond to threats, organizations are better equipped to improve their security posture. AI can be leveraged to automate security tools and processes, allowing for better accuracy and speed of response. The end result is improved security and better prevention of cyberattacks.
As the technology evolves, the potential for generative AI to provide improved accuracy and precision in the cybersecurity field will only grow. Organizations looking to benefit from the advantages of AI-powered security solutions should look into investing in this technology.
