AI-Native Data Leak Prevention (DLP) for Slack

Automatically detect and secure sensitive and personally identifiable data anywhere in Slack, with a certified Slack Marketplace partner.

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Automate and simplify data leak protection for Slack

The way we work has changed, but data protection has not. Existing solutions fall short when uncovering sensitive data risks in the cloud. It's time for a new solution.

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Discover

Integrate in minutes to detect sensitive data in 100+ file types, including images.

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Classify

AI-based detectors identify potential security and compliance risks with high accuracy.

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Protect

Real time alerts and automated remediation actions, to reduce compliance workload.

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HIPAA reporting and monitoring made easy

Healthcare organizations need to protect PHI and comply with HIPAA. Nightfall automatically classifies all cloud data and finds at-risk patient data from a single platform.

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    Use prebuilt, high accuracy detectors or create your own

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    Build detection rules for your use cases

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    Scan text and files, including images

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    Remediate sensitive data with redaction techniqu

Collaborate securely with all your employees

Nightfall provides the visibility needed to minimize security risks, set up automated remediation workflows, and achieve compliance.

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Fastest implementation

Designed and built for the way you work in Slack, Nightfall installs as a Slack bot.

Integrate in seconds and scan for data at the application level. Get full visibility into sensitive data across Slack.

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Accurate detection

Reduce noise for  your team through our high-accuracy detection engine.

Apply DLP policies flexibly according to location within Slack, and adapt automation to your needs.

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Proactive protection

Spend less time responding to incidents and remediating actions.

Set up automated DLP workflows for quarantines, deletions, alerts, and coaching end users on data security best practices.

Experience always-on security at scale

Nightfall provides the visibility needed to minimize security risks, set up automated remediation workflows, and prove compliance.

Your Slack environment is complex, but identifying data security risks shouldn't be

Detect suspicious files & messages in real-time and take action directly within Slack.

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    With no agents to install, setup takes minutes.

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    Scan a broad set of file types including unstructured data.

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    Use machine-learning trained detectors to scan for sensitive data.

Reduce time triaging security alerts using high-accuracy AI detectors and out-of-the-box detection templates

Apply policies flexibly based on location within Slack to focus efforts on what really matters.

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    Customize detectors with thresholds and other rules to reduce false alerts.

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    Detect and identify PII, PCI, PHI, credentials & secrets, custom data types, and more.

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    Apply context-based, AI detectors for high accuracy and continual improvement.

Scale your operations by educating users. Users can become the first line of defense for security

Enable employees to remediate with minimal overhead through notifications and coaching.

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    Set up automated workflows to remediate sensitive findings.

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    Build a culture of trust and strong data security hygiene.

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    Manage all of the security tasks in your SIEM or Nightfall dashboard.

Learn more
about benefits

Duis vel morbi orci volutpat tellus. Gravida dolor pretium ut rhoncus tellus diam suspendisse ut.

HIPAA reporting and monitoring made easy

Healthcare organizations need to protect PHI and comply with HIPAA. Nightfall automatically classifies all cloud data and finds at-risk patient data from a single platform.

  • Group of integration logos

    Use prebuilt, high accuracy detectors or create your own

  • Group of integration logos

    Build detection rules for your use cases

    Group of integration logos

    Scan text and files, including images

  • Group of integration logos

    Remediate sensitive data with redaction techniqu

Learn more

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Getting started is easy

Install in minutes to start protecting your sensitive data.

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