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Snowflake Data Security: Key Features & How a Metadata Control Plane Strengthens It Further

Updated May 27th, 2025

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Snowflake secures data through a multi-layered, end-to-end model to safeguard data at all access points. Snowflake data security includes authentication policies, private connectivity, network policies, always-on end-to-end encryption, and governance tools like session policies and the Trust Center.

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But while Snowflake secures the platform, most organizations still lack unified visibility, policy enforcement, and trust signals across tools and teams. That’s where a metadata control plane like Atlan becomes essential, connecting governance, lineage, and access control into a single layer across the modern data stack.

This article will explore:

  • Snowflake data security features
  • The role of a metadata control plane in enhancing Snowflake data security

Table of Contents #

  1. How does Snowflake data security work?
  2. How does Atlan enhance Snowflake data security?
  3. Final thoughts on Snowflake data security
  4. Snowflake data security: Frequently asked questions (FAQs)
  5. Snowflake data security: Related reads

How does Snowflake data security work? #

Snowflake provides data security through authentication, authorization, private networking, encryption, and auditing, with additional privacy and governance tools to support industry or regional compliance requirements.

Most of these features are bundled into its Continuous Data Protection (CDP) offering, which safeguards data throughout its lifecycle.

You can use Snowflake’s Trust Center to continuously evaluate and monitor your Snowflake data assets for security risks. It uses scanners, scheduled background processes, to check your account for security risks depending on your account configuration. Scanners are grouped into packages called Security Essentials, CIS Benchmarks, and Threat Intelligence.

Using Snowflake’s Trust Center, you can:

  • Verify that multi-factor authentication (MFA) is enabled for all users relying on password-based logins.
  • Identify roles that may have excessive or unnecessary permissions.
  • Monitor and limit the number of users assigned to high-privilege roles (like ACCOUNTADMIN and SECURITYADMIN).
  • Detect inactive users who haven’t logged in for 90 days.
  • Pinpoint users with potentially risky behavior and reduce authentication-related vulnerabilities.

Snowflake data security: Key features #


Here’s a look at Snowflake’s key security features across different stages:

  • Authentication: Snowflake supports all the major authentication mechanisms, including federated SSO, OAuth, MFA, and key-pair authentication. It allows you to generate and manage programmatic access tokens for authentication. Snowflake data security also supports all the popular identity providers, such as Okta, Microsoft AD FS, Microsoft Entra ID, OneLogin, and Ping Identity.
  • Access control: Snowflake offers fine-grained control over all of your data assets with role-based access control (RBAC), user-based access control (UBAC), and discretionary access control (DAC).
  • End-to-end encryption: To ensure that your data is encrypted at rest and in transit, Snowflake offers end-to-end encryption (E2EE) in internal and external stages. You can use a tool that supports client-side encryption to access the data. Note that you’ll need access to the stage credentials and the encryption key to do that.
  • Network rules: To restrict inbound network traffic from unidentified systems and locations, you can create network rules and enforce them via network policies. This feature also allows you to restrict access to external network locations when working with UDFs and stored procedures.
  • Private networking: Snowflake offers private networking to the core services, internal stages, and also external services. Most of the private networking features are available for all three major cloud platforms – AWS PrivateLink, Azure Private Link, and Google Cloud Private Service Connect.
  • Object tagging and classification: While object tags are primarily used for discovery and governance, they also automatically provide a foundation for enforcing advanced security controls. You can use tags as the basis for masking data in specific tables and columns. Meanwhile, classification is a process you can invoke to create system-defined or custom-made tags for handling PII and PHI data.
  • Data masking and row-level security: Snowflake gives you the option to either use its native data masking feature or outsource it to an external compute resource (AWS Lambda function) using the external tokenization feature.
  • Differential privacy: With the help of privacy domains, budgets, and policies, you can set up differential privacy to help reduce the risk of data exposure. This is achieved by techniques such as noisy aggregates and privacy loss budgeting.
  • Aggregation and projection policies: In addition to data masking and row-level access policies, Snowflake also provides you with the option to prevent certain data from being displayed in the results of a SQL query. Projection policies help you protect certain columns, while aggregation policies help you enforce a specific degree of group by clause for you to get the result.
  • Snowflake Time Travel and Fail-safe: Time Travel helps you maintain historical data (i.e. data that has been changed or deleted), whereas Fail-safe is the feature for disaster recovery (this can only be performed by Snowflake).

How does Atlan enhance Snowflake data security? #

Like Snowflake, Atlan is also committed to data security and prioritizes it with a well-documented security-first approach. This gives you full control over how you manage access, restrictions, and other security considerations with your Snowflake data assets.

Atlan tightly integrates with Snowflake’s metadata layer, capturing the metadata for all the security-related features you learned about in the previous section. Atlan, then, layers those with another set of security features, which include (but aren’t limited to):

  • No caching or storing of data: Atlan allows you to preview data and run queries from the UI, but it never caches or stores any of the data. Atlan stores only the metadata (table structure, roles, groups) it collects in a secure VPC and various backend databases.
  • Advanced authentication and authorization: Atlan lets you manage identity and authentication using SSO with SAML 2.0 and SSO with SCIM. It supports all the popular identity providers, while also allowing you to use your custom IdP.
  • Data access control: Atlan implements its own fine-grained role-based access control model adhering to the principle of least privilege by denying access by default. Access to data assets in Atlan is controlled by defining three types of access policies: data, metadata, and glossary. Additionally, Atlan’s Transparency Center helps you monitor and control access to data, enforce policies, and even drive other areas of data governance from a singular place.
  • Personas and purposes: Atlan enables you to define policies based on the data governance model that you have in place at your organization. For instance, you can create team-based personas. Doing so helps curate and control access to the data assets better. You can also use purposes to define domains and enable tag-based data protection, especially when you have to protect data assets containing PII and PHI data.
  • Infrastructure security guarantees: Atlan has advanced networking and security controls with several lines of defense to ensure that all your data assets are secure. On top of that, Atlan also provides security monitoring, which you can access using a Grafana endpoint.
  • Encryption: Atlan applies encryption at rest and in transit. It encrypts moving data over HTTPS using TLS. It also encrypts any data stored in object-based storage in your cloud platform with their native server-side storage using the industry-standard AES-256 data encryption.

By using Atlan as a metadata control plane, you can manage consistent security across Snowflake and other tools in your data ecosystem, setting up a unified security posture that is scalable, auditable, and reliable.

Final thoughts on Snowflake data security #

Snowflake offers a strong foundation for securing your cloud data through authentication, access controls, encryption, and governance tools. But to achieve end-to-end security across the modern data stack, organizations need visibility, context, and coordination.

Atlan bridges these gaps with a metadata control plane that connects governance and security across Snowflake and other tools in your data ecosystem, creating a stronger, unified security posture.

To learn more about the benefits, visit the Atlan + Snowflake connectivity documentation. You can also explore how Atlan helps with better data governance in Snowflake.

Snowflake data security: Frequently asked questions (FAQs) #

1. What is Snowflake’s approach to data security? #


Snowflake follows a multi-layered, end-to-end model that spans authentication, access control, encryption, private networking, and continuous monitoring to protect data across its lifecycle.

2. How does Snowflake secure data? #


Snowflake secures data through role-based access control (RBAC), end-to-end encryption, network rules, private connectivity options, and the Trust Center for real-time security posture monitoring.

3. Is Snowflake data safe? #


Yes. Snowflake is built with enterprise-grade security, including always-on encryption, strong identity management, activity logging, and compliance with frameworks like SOC 2 Type II, HIPAA, and FedRAMP.

4. How is data encrypted in Snowflake? #


All data in Snowflake is encrypted using AES-256 both at rest and in transit. It also supports client-side encryption and encrypted file storage for enhanced security.

5. What are the security layers that Snowflake takes care of? #


Snowflake covers multiple layers including authentication, authorization, network access, encryption, user/session management, private connectivity, and continuous risk monitoring via the Trust Center.

6. What is Snowflake’s Trust Center and how does it work? #


The Trust Center continuously evaluates your Snowflake account for vulnerabilities using automated scanners. It helps enforce MFA, flag inactive users, detect risky permissions, and monitor authentication methods.

7. What is continuous data protection in Snowflake? #


Continuous Data Protection (CDP) refers to Snowflake’s native capabilities like Time Travel, Fail-safe, automatic backups, and point-in-time restoration to ensure data durability and recoverability.

8. What is Fail-safe and Time Travel in Snowflake? #


Time Travel allows users to access historical data for up to 90 days, while Fail-safe is a 7-day recovery window managed by Snowflake to recover from serious operational failures.

9. Can Snowflake support zero-trust architecture? #


Yes. Snowflake enables zero-trust through fine-grained RBAC, MFA, network policies, private endpoints, and real-time threat detection using its Trust Center.

10. Why do I need a metadata control plane like Atlan with Snowflake? #


Snowflake handles platform security, but Atlan provides unified visibility, lineage, and cross-platform policy enforcement. These are crucial for consistent governance, trust signals, and access control at scale.

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