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Frequently Asked Questions (FAQs)
Browse some of our most frequently asked questions.
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Nightfall’s native integrations connect with services via their APIs, and are fully cloud-hosted. Nightfall is the industry’s first cloud-native DLP platform. This means there are no agents or software to install, patch, manage, or update. Our platform integrates directly with the third-party cloud apps you are using (e.g. Slack, GitHub, Confluence, etc.) via their native APIs. These services’ APIs support token-based authentication, most commonly OAuth, which allows Nightfall to request a limited access token to access user data. Nightfall is fully hosted in Amazon’s AWS and Google’s GCP.
Nightfall’s Developer Platform is a fully-managed cloud service composed of REST APIs that developers use to programmatically leverage our detection engine. The Developer Platform can also be self-managed by you in your own environment.
For most systems it takes on the order of minutes to deploy. Because Nightfall is cloud-native and integrates directly via API, customers are typically up and running within a few minutes. For SaaS apps like Slack, Confluence, and GitHub, there’s no additional configuration or setup required beyond installation. Compare this to traditional endpoint or network-based tools that could may take weeks to install and rollout. With Nightfall, there is no effort required by end-users and no added latency or performance overhead to the network or to endpoint devices.
Nightfall uses machine learning to classify data. Our deep learning-based classifiers are trained on massive volumes of data to yield high accuracy. Unlike traditional methods, Nightfall considers the context surrounding a given token in order to accurately classify it. This means Nightfall performs well on unstructured and ambiguous data, which is increasingly common in enterprises today. Nightfall parses and scans 100+ file types, including images, screenshots, compressed folders, PDFs, etc. Our classifications are fed into the Nightfall platform so you can review & remediate the findings, or leverage them in your own way via our Developer Platform.
Nightfall classifies over 100+ types of sensitive data, including forms of personally identifiable data (PII), protected health information (PHI), payment card information (PCI), credentials & secrets, and more. For example, email addresses, credit card numbers, social security numbers, API keys, passwords, and many more. These data types support compliance regimes like HIPAA, GDPR, HIPAA, PCI-DSS. Likewise, Nightfall’s detectors apply to a broad variety of industries and geographies (countries in US, EMEA, APAC, etc.).
Nightfall also supports custom detectors, as well as features such as context rules & exclusion rules that enable you to further tune detectors to your specific business needs and increase accuracy. Contact us at firstname.lastname@example.org to determine if Nightfall supports detectors that meet your needs.
Yes, Nightfall scans unstructured data and parses text from 100+ file types. For example, this could be data like customer chat logs, JSON objects, application logs, spreadsheets, PDFs, images, screenshots, etc. Read more about the risks imposed by unstructured data on our blog here.
Nightfall integrates directly with your Slack organization or workspace as a Slack bot. Installing the bot takes just one click via OAuth. In Slack, a bot is controlled programmatically via a bot user token that can access one or more of Slack’s APIs. Using these APIs, Nightfall monitors content in your Slack organization in real-time, and you’ll receive notifications directly in Slack when sensitive data is detected.
Chat with us via the chat widget in the bottom right, or email us at email@example.com with any questions or to schedule a demo.
The best way to evaluate Nightfall is via a free trial. Contact us at firstname.lastname@example.org to get started, or via the chat widget in the bottom right.
No, Nightfall doesn’t require data to be pre-tagged. Nightfall uses machine learning to detect 100+ types of sensitive data out of the box, without prior tuning or tagging required. This includes forms of PII, PHI, PCI, and other sensitive content – for example, emails, social security numbers, etc. Our detectors leverage context surrounding a specific token to properly identify and classify it, which dramatically improves accuracy over traditional rules-based approaches to DLP.
Nightfall saves time by automating data detection, classification, and remediation. First, Nightfall installs in minutes, so you won’t need IT resources or time spent worrying about agents or software to install, patch, manage, and update. Second, classification is automatic and highly accurate, so you’ll eliminate time spent tagging data manually, and reduce time spent reviewing false positives and grappling with alert fatigue. Third, with Nightfall you can set up automatic workflows to take action on sensitive data proactively, which means you’ll reduce time spent manually responding to alerts and reduce mean time to resolution.
In the case of our Slack product, the Nightfall bot lives directly in the Slack workspace, which means administrators don’t have to context-switch between apps, and employees can receive descriptive notifications directly in Slack in real-time, rather than via email, meaning less time finding workarounds.
As a result, you’ll see measurable time savings and productivity improvements that give your team the leverage to focus on other security & compliance challenges.
Traditional data loss prevention (DLP) platforms focus primarily on securing data on endpoints (devices like laptops, phones, servers) or networks. As such, they don’t provide visibility into cloud applications and cloud data infrastructure that enterprises are rapidly moving towards. Nightfall is the industry’s first cloud-native DLP platform focused on detecting & protecting data in the cloud by integrating directly with these services via their APIs.
Legacy DLP solutions are also limited in what they can recognize because they rely on traditional detection methods, such as regex rules and digital signatures/fingerprints. These have severe limitations in accuracy, usually resulting in a high volume of false positives, and significant alert fatigue for end-users. This means negative ROI and limited value.
In contrast, Nightfall leverages machine learning to scan data and its surrounding context, meaning Nightfall can scan both structured & unstructured data with high accuracy. Because of this higher accuracy, customers often have Nightfall automate the response to data leakage events, yielding measurable time savings. Security, compliance, and engineering teams can focus on other problems, versus triaging alerts, getting hours back in their day. What was once negative ROI with traditional DLP is now positive ROI with Nightfall.
With the proliferation of cloud SaaS and data infrastructure, sensitive data sprays across more and more third-party services like Slack, GitHub, and AWS at an alarming rate. It’s a major challenge to see what data is in these silos and is being transmitted across them in real-time. Moreover, data is increasingly complex & unstructured and is created at an unprecedented rate, making it impossible to consistently tag and keep track of. All of this data can be subject to security risks, in the form of data filtration or leakage outside your organization, resulting in a breach. Likewise, you may be subject to compliance regimes that dictate your use & protection of customer data, such as HIPAA, GDPR, CCPA, and PCI-DSS.
Nightfall is a data loss prevention platform that alleviates these burdens by automatically discovering & classifying sensitive data, giving you visibility into your cloud apps, and giving you the ability to respond & remediate instances of data sharing or data loss that represent security or compliance risks to your business. With these controls in place, you’ll have greater visibility into how sensitive data is stored, managed, shared, processed, and protected within your organization, and reduce the likelihood that this data is compromised by malicious or inadvertent activity.
Nightfall is the industry’s first cloud-native data loss prevention platform that discovers, classifies, and protects data via machine learning. In contrast, a CASB (cloud access security broker) is typically a network-based solution that sits between cloud service users and cloud applications to monitor activity and enforce security policies. Data loss prevention identifies and protects sensitive content from loss, such as inappropriate use, sharing, exfiltration, or misuse.
CASBs may have limited data classification and protection capabilities via API, although they aren’t designed for this purpose. As with any monolithic vendor that tackles a wide breadth of problems, a CASB doesn’t achieve the same level of depth in functionality, accuracy in detection, or granularity in remediation as a best-of-breed DLP solution.
Nightfall is designed to inspect content, so we cover a much broader set of (over 100+) file types, including unstructured data, and detect a broader set of (over 100+) detectors. Likewise, accuracy is substantially improved via machine learning. In summary, Nightfall may work well with a CASB if you already have one, or as a replacement for companies focused on high-fidelity data protection in the cloud.
E-discovery and data loss prevention (DLP) are different, albeit conceptually similar. Nightfall is a cloud-native DLP platform.
E-discovery typically pulls messages and files from a platform to store the information in third-party data warehouses, where messages and files can be searched, archived, or retrieved. This serves legal and compliance use cases should the data need to be retrieved or searched for a legal hold.
DLP ensures sensitive data, such as personally identifiable information (PII), isn’t shared inappropriately by scanning for content within messages and files that break selected policies. This serves security and compliance use cases around discovering, classifying, and protecting sensitive data.
Compliance regimes like GDPR, CCPA, HIPAA, and PCI-DSS require effective management & protection of customer data to keep consumers safe. The Nightfall platform can help you first discover and classify sensitive customer data like PII, PHI, and PCI that many compliance regimes identify as data that must be protected. With Nightfall, you’ll also be able to remediate issues by taking actions like notifying admins & quarantining/deleting data. This reduces the risk of losing or exposing sensitive customer data and reinforces your commitment to protecting this information. As a result, your organization can better achieve or maintain compliance — avoiding fines, fees, or legal troubles associated with data loss.
Yes, Nightfall’s machine learning-based detectors identify protected health information (PHI), such as social security numbers, across your SaaS and cloud infrastructure, and ensure that such data isn’t exposed or shared in systems where it shouldn’t be. Nightfall is essential for ensuring HIPAA compliance within SaaS applications like Slack and is critical to development teams scaling healthcare applications within a production environment. Read our case studies to see how we help companies like Galileo Health and Springbuk maintain HIPAA compliance.
Yes, protecting sensitive customer data is paramount to GDPR and CCPA compliance. Nightfall detects & classifies personally identifiable information (PII) with over 100 out of the box detectors, including forms of PII specific to European countries – for example, UK Driver’s License Numbers. Discover sensitive data at rest as it exists in data silos today, or monitor in real-time on an ongoing basis. Nightfall will not only enable you to discover where sensitive data exists across SaaS & data infrastructure but will also give you the power & insight to selectively remediate issues as they arise.