Webinar: Join us, Tues 5/24. Nightfall & Hanzo experts will discuss how machine learning can enhance data governance, data security, and the efficiency of legal investigations. Register now ⟶
Prevent insider threat in SaaS and IaaS enviroments
Decrease your insider threat risk with DLP
Do you know when sensitive data is replicated or shared across various platforms? Data Loss Prevention (DLP) from Nightfall scans data in a broad set of files types, including unstructured data with machine-learning based OCR so you can discover unknown unknowns and protect against insider threat.
Learn where your sensitive data is stored
Use Nightfall’s machine learning trained detectors to fully customize scans in your SaaS and IaaS environments to search for business-critical data at risk of exposure. Defend against insider threat at the source: prevent users from sending credit card information in Slack messages, protect against credentials being exposed in GitHub, and more.
Manage insider threat risk with DLP
Anyone with access to your systems, platforms, and apps can be a potential vector for data exposure. Insider threat can also stem from third-party vendors, contractors, and others who can log in and access your data. Your attack surface is likely larger than you think. Protect data across your cloud systems with Nightfall and start using machine learning trained detectors to find and mitigate threats anywhere, anytime.
Nightfall enables data protection for many modern applications.
UserTesting is building culture of security with their DLP program — and Nightfall
Nightfall supports UserTesting’s core security values: put customers first, keep it simple, and recognize value. Security is integrated into their internal communication infrastructure with DLP.Read the UserTesting case study