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Hello!  I wanted to know if there is an easy way to get a copy of all the technical support docs from Netskope. Including API docs (which are currently only available at the Netskope admin console level). My goal is to create a vector database and ultimately teach an AI Agent Netskope. For practical purposes I'd like to see the extent by which I can extend and embed a model with data and how that would stack up to some of our in house support. Apart from the public facing knowledge base I'm looking for more documents on troubleshooting client side issues. Maybe even some documentation on how to spot errors in Netskope Debug Logs, etc...  Thanks for any and all support!-Hax

The conversation around AI/ML is everywhere, but it often leads to confusion and misconceptions. In the most recent episode of Netskope’s Security Visionaries podcast, we discussed the importance of AI transparency - a cornerstone for cultivating public trust and enabling individuals to make well-informed decisions about AI risks. We believe it's time for organizations to embrace openness and transparency about their AI models. For example, organizations should be prepared to answer: What's the data used to train a model? Does it include customer data? What inputs does the model rely on? What outputs does the model generate, and how are they used i

According to Gartner, “ChatGPT and large language models are the early signs of how generative AI (GenAI) will shape many business processes. Security and risk management leaders, specifically CISOs, and their teams need to secure how their organization builds and consumes GenAI, and navigate its impacts on cybersecurity.”   In addition, Gartner says that “The level of hype, scale and speed of ChatGPT adoption has raised end-user awareness of LLMs, leading to uncontrolled uses of LLM applications. It has also opened the floodgates to business experiments and a wave of AI-based startups promising unique value propositions from new LLM and GenAI applications. Many business and IT project teams have already launched GenAI initiatives, or will start soon.”   CISOs and security teams need to prepare for impacts from GenAI in four different areas according to Gartner: “Defend with” GenAI “Attacked by” GenAI Secure enterp

How does the Netskope capture the data of User like email or used I'd when I install the agent via email invite or the mass script based what's was the intelligence behind it also what protocols used between ns client and Netskope cloud gateway (POP) please let me know this answer 

I am proud to present to you the culmination of years of innovation and fruitful collaborations across multiple product teams at Netskope - the remarkable SkopeAI!SkopeAI stands as a testament to our commitment to excellence in the realm of AI-powered data security and threat protection solutions. We have harnessed the power of cutting-edge AI/ML technology to deliver industry-leading safeguards against modern-day security challenges.The launch of SkopeAI is not the end but rather a stepping stone in our AI journey. With an unwavering focus on staying at the forefront of AI and machine learning technology, we are determined to explore new frontiers, raise the bar higher, and enhance our security offer

Today, I come to you seeking your valuable insights and suggestions on how we can enhance the security of our organization. Specifically, we aim to prevent users from uploading or sharing any source code through the platform Google Bard.To this end, we kindly request your expertise in brainstorming and proposing potential solutions to achieve our goal.In advance, I appreciate your help.

  At Netskope, we have developed a deep learning-based Inline Phishing Detection Engine. Similar to generative pre-training of large language models, such as BERT and ChatGPT/GPT-4, we use a large number of web pages to train a HTML encoder and then use it to build the phishing classifier. The Inline Phishing Detection Engine has been generally available to all Intelligent SSE and Netskope Next Gen-SWG customers. In this blog post, we share some of the patient-zero and evasive phishing examples that the engine has detected.   Have you seen any phishing pages detected by the Inline Phishing Detection Engine in your environment? Please let us know if you have any feedback.   

  In today’s rapidly digitizing world, the importance of data security has become paramount. With the increasing amount of sensitive information being shared and stored online, securing information from cyber attacks, information breaches, and theft has become a top priority for companies of all sizes. Data loss prevention (DLP) is a critical part of the Netskope Intelligent Security Service Edge (SSE) security platform, providing best-in-class data security to our customers.   Images often contain a wealth of valuable and sensitive data. Financial documents, personal identification, and confidential business communications frequently include images that require the utmost security. At Netskope, we have developed state-of-the-art deep learning-based computer vision classifiers that can analyze images and identify sensitive information in a wide va

Join us on Linkedin Live on June 22 at 9:30am PDT to discuss how Generative AI SaaS applications, like ChatGPT, have revolutionized corporate workflows, but have also introduced significant data security risks.   Modern cloud-first businesses are grappling with unprecedented challenges as sensitive data becomes increasingly exposed to a new breed of applications. 📈 23% of employees access ChatGPT at least once a day, based on a recent Netskope study through Advanced Analytics, and this number is expected to grow rapidly. Join Netskope executive leaders for a lively discussion on: The sensational Generative AI phenomenon led by ChatGPT What Generative AI Apps can do: Endless possibilities How you can prevent data exposure, breaches and add

Dear Netskope administrators, let me share an idea about using ChatGPT as your assistant. Netskope has many URL categories, and here's a prompt to have ChatGPT respond to what categories are available.   Fill in the "Search criteria" part of the following prompt with the category you want to investigate, and by inputting it into ChatGPT, it will pick up the corresponding category for you.　Prerequisites: GPT4 is available, and the WebPilot plugin is enabled.　*Please note that this is a simple investigation, so if you are actually going to apply it, please carefully review the help page and set it accordingly.   ---ChatGPT Prompt---You are a security engineer. You are trying to restrict access to a website on a category basis. Please follow the Steps to pick the appropriate candidate. #Reference URL

The rise of generative AI tools such as ChatGPT has captured the attention of many people. In a recent blog post, we discussed the benefits, challenges, and potential risks of AI in the cybersecurity domain. We're curious: do you have any questions or concerns about AI? Feel free to share them with us! 

Machine learning-based image classification offers a fast and effective way to detect sensitive information within images, allowing for granular real-time DLP policy controls. Our DLP Classification Service accommodates an extensive range of image classifiers, such as passports, driver's licenses, SSNs, checks, payment cards, screenshots, whiteboards, and more. To improve its accuracy and provide better customer experience, we have retrained the classifiers for Release 103.   Significant changes were made to the image classifiers, including: A newer underlying model architecture with an 80% increase in the number of parameters High-quality labeled training data, including augmented images that are realistic for the image data we see in the cloud, to minimize false positives   Acc

Earlier this month, we enabled the inline AI-powered phishing detection engine in Netskope Threat Protection for all customers, significantly enhancing its capability to block phishing content in real time.    Phishing is one of the most common online security threats. At Netskope, we use cutting-edge deep learning techniques to learn the patterns of phishing websites. Similar to generative pre-training of large language models, such as BERT and GPT, we use a large number of web pages to train the HTML encoder and then use it to build the phishing classifier. We have been awarded three U.S. patents for our innovative approach to phishing detection.   We have been gradually rolling out the inline phishing detection engine. The engine has discovered a range of