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Funded on the platform
Yieldstreet protects PII in Slack with Nightfall DLP
Funded on the platform
HQ Location: New York, NY
Azret Deljanin, VP of Infrastructure and Security
Yieldstreet is an alternative investments platform that strives to democratize access to financial products historically only available to institutional investors. With Yieldstreet, there are investment opportunities available to both accredited and non-accredited investors looking to invest in funds in the litigation finance, marine finance, and art finance asset classes.
Data security and growth are top goals for Yieldstreet
Azret Deljanin is the VP of Infrastructure and Security at Yieldstreet and is tasked with providing secure and scalable technology solutions to a growing regulated organization. Adding new solutions to their tech stack is more than just implementation. Protecting sensitive investor and company data is paramount to every vendor they bring on board. Yieldstreet chose Slack because of its strong security and compliance tool sets, but they needed a way to classify data across all their workplace collaboration solutions.
DLP that’s built to scale with the company
Yieldstreet’s investors must provide sensitive information to the platform in order to get started with investing. This typically includes personally identifiable information (PII) like bank account information and tax ID numbers. So when Yieldstreet chose Slack to manage internal collaboration, they needed a solution to prevent leakage and misuse of sensitive data and decided to leverage Nightfall DLP for Slack. With 150+ machine-learning trained detectors to automatically scan for data, Azret and his team could take the appropriate actions to manage their attack surface. “Nightfall classifies data with text rules or OCR to find application secrets, API keys, passwords, and more things we could not detect out of the box with Slack,” says Azret.
A foundation for strong security, now and tomorrow
Nightfall DLP for Slack adds value for Yieldstreet by detecting, classifying, and remediating misuse of sensitive data seamlessly within their Slack app. “We can make sure that we’re using the right rule set and the right confidence level in that particular rule set,” says Azret. “And now that we’re able to review that data and understand what’s being shared within Slack, we can train our users on what’s appropriate to share.” Nightfall DLP to Slack helps Yieldstreet uphold their company value of investor trust in an operator friendly way.
“Nightfall allows us to redact or prevent sharing data and notify our security team almost instantly in Slack, and presents us with what actions we can take. It allows us to review the data; determine whether or not it is sensitive and delete it if we choose. It helps inform us on how we can train our users on what is safe to share and the mediums to use to share sensitive information.”
Nightfall is the industry’s first cloud-native DLP platform that discovers, classifies, and protects data via machine learning. Nightfall is designed to work with popular SaaS applications like Slack, Google Drive, GitHub, Confluence, Jira, and many more via our Developer Platform. You can schedule a demo with us below to see the Nightfall platform in action.
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