Security teams can react 80% faster to Cyberhaven generation tools for AI power supply

Workers are eager to take advantage of AI tools – whether or not their employer likes it. This disapproved use, which is known as a Shadow AI, increases dramatically: as much as 96% of the work The employees who make AI are through non -corporate accounts. Whether it is done inadvertently or maliciously, this can leak highly sensitive and own data from the enterprise.

Security platform Cyberhaly He says he can solve this problem by tracking the data line or life cycles of data in different users and endpoints. The company has specific models with LLIMS (LLIMS) for this task and today announces Linea AI, the next generation of its platform designed to help stop the Shadow AI and predict what flag accidents may be the most dangerous.

“It is manifested in this form of pedigree: you understand where the data that has access to it comes from, in all different endpoints, in all your users,” said Nishant Doshi, CEO for the product and the development of Cyberhaven, before Exclusive Interview.

90% reduction in incidents requiring manual examination

According to Cyberhaven’s analysis for the work flows of 3 million workers, the use of AI is increasing 485% Between March 2023 and March 2024, employees are increasingly sharing sensitive data: nearly 83% of legal documents and about 50% of the source code, research and developments and recordings of HR and employees, which employees share with AI, go to non -corporate AI accounts.

To help prevent this unauthorized use and protection of the company’s sensitive data, Linea AI uses LLIM, trained on billions of actual business data. Equipped with computer vision and multimodal AI, it can analyze image data, screenshots, technical diagrams and other materials. The new “Let Linea Ai Relication” feature now autonomly evaluates the incident’s policy and severity disorders to help reduce the Fatigue of the Security Center (SOC).

“So just like the big language of the language (LLM), which envisages the next word, we predict what the next actions will be,” Dosha explained.

Cyberhaven claims that as a result, customers monitor a 90% reduction in incidents requiring manual examination and 80% decline for average response time (MTTR) for data security -related incidents. The company’s tools can detect critical risks by 50 plus per month not detected by traditional instruments.

“Cyberhaven shows us exactly how our data moves and are used throughout the organization, giving us visibility that is not found with traditional security tools,” says Prabhat Karan, Opi and Cio on Family Finance App Green lightS “Now we have a single platform that not only covers traditional data loss (DLP) and internal risk management, but actually understands how people use data throughout our organization.”

Doshi explained that while traditional approaches focused on matching models – identifying network models and data detection data and vulnerabilities – Cyberhaven performs content and context verification. His platform examines the data and provides a context around it based on traces of pedigree.

“So if you download something, you send it to me, I send it to five other people, they send it to five other people – this is a genealogy,” Dosha explained.

How Cyberhaven Protects the most valuable Enterprises data with AI

Cyberhaven offering is powered by Frontier AI models and transformer neural network architecture. It uses a multi-stage engine extracting engine (RAG) to refine its LLIM to analyze the company’s most valuable data and to “get to the needle in the hay,” Dosha said.

The platform performs an intelligent screen analysis, which is a “permanent blind place” in data security, said Aaron Archene, a senior security engineer in the Platform for Wage Access Platform DailypayS

So, for example, let’s say that the security team wants to prevent the screenshots from leaving the company. There may be thousands and they have to go through anyone to determine whether it is a harmless cat meme or a screenshot containing product schemes.

“It is difficult to find, let alone prevent, the exfiltration of engineering designs, AI models, research data, product road cards,” says Archene.

Maintaining tabs of users

Cyberhaven is now making Cybersecurity step beyond the opening with its new autonomous, AI-nourishing Let Linea to decide that it sifted out users’ data and registration files to help the security teams understand the incident’s weight. The platform of course screenshots, PDF, source code and other digital materials and can provide context based on data genealogy, Doshi explained. It can be understood then whether a specific incident of human analysts should be considered.

“We are trying to predict the next action based on all the historical knowledge we have: this is an abnormal event or it is a benign event,” Doshi said. “We call this understanding of data because you really look at the data and understand this data in depth.”

Arcin explained that when it comes to internal risk, security teams carry out improved monitoring to create flows of information about specific users who have been marked as an increased risk (based on any number of factors).

“Let’s say I improved you, you were busy that day, 150 events were generated,” he said. “I will have to go through each of them manually, to determine” this is a business as usual. ” “This one looks a little suspicious.” “This one looks really suspicious.” And I still have others to go after.

For example, the platform was able to find users sending data to its personal accounts at OneDrive or to sync sensitive files on iCloud, Dosha said. A gold step beyond this is employees who leave company and try to get sensitive data with them.

“In real time, we can prevent users or a set of users from uploading sensitive data to these public LLMs,” Dosha said. “We can also warn them and also educate them,” when they do something involuntary or naive.

Dailypay, in turn, has managed to reduce MTTR by 65%as Linea provides a digestible summary of AI, Archene said. Typical data loss tools (DLP) requires a lot of personal resources to gain this kind of visibility.

He examined other DLP providers, including Netskope, DTEx Systems and the next DLP, but eventually settled on Cyberhaven because of his data line strategy. Unlike anything he has seen in the industry, he said.

“It saves us a lot of time for escalation and triag, as well as prevention,” Archene said. “Linea AI consistently identifies the nuanced risks that traditional systems will absolutely miss.”