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pre[class*=language-]{background-color:rgba(var(--ui-12-rgb),.5);color:var(--text-01);text-shadow:none;padding:var(--spacing-00);border-radius:var(--spacing-00);font-size:smaller}",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false},"responsivegrid":{"columnClassNames":{"quickstart_hero":"aem-GridColumn aem-GridColumn--default--12","flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,":items":{"quickstart_hero":{"id":"quickstart-hero-419e202c44","isDeveloperGuidesPage":false,"quickstartHeroFirstCertifiedTag":{"tagText":"Well Architected Framework","tagColor":"#29B5E8","tagPath":"/content/cq:tags/snowflake-site/taxonomy/solution-center/certification/well-architected-framework","tagIcon":""},"quickstartHeroTitle":{"lines":["Security & Governance 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principles of the\n\u003Cstrong\u003EConfidentiality, Integrity, and Availability (CIA)\u003C/strong\u003E triad. The\nrecommendations provided within this framework are based on the \u003Cstrong\u003EShared\nResponsibility Model\u003C/strong\u003E and focus on the security controls that are the\ncustomer's responsibility. The goal is to minimize security risks by\nsecuring the Snowflake perimeter, using the principle of least privilege\nfor data access, responsibly deploying AI, and preparing for security\nincidents.\u003C/p\u003E\n","\u003Ch2\u003EPrinciples\u003C/h2\u003E\n","\u003Ch3\u003ESecure the perimeter\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EA strong security perimeter is built using network, identity, and\npolicy constructs. You should assess network traffic to and from your\nSnowflake accounts to ensure network and endpoint security are in\nplace for all connections. For identities, leverage modern\nauthentication and authorization flows and enforce conditional access\npolicies for Snowflake accounts.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EGovernance\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EGovernance in the security pillar is about enforcing, monitoring, and\nauditing data access, privacy, and compliance controls. This ensures\nthat auditors can prove who can see what, and under what conditions.\nBroader governance concepts like data quality and lineage are\naddressed in other pillars.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EResponsible AI\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EThe rapid adoption of AI capabilities brings security concerns,\nparticularly regarding the protection of sensitive data. It's crucial\nto use AI responsibly and ensure that AI deployments are secure within\nyour Snowflake environment.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EAssume breach\u003C/h3\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003EYou must prepare for security events by having established \u003Cstrong\u003ECyber\nSecurity Incident Response Plans (CSIRP)\u003C/strong\u003E specifically for your\nSnowflake accounts. This includes creating playbooks with actionable\ntasks for different incident scenarios and conducting regular training\nand tabletop exercises. Continuous monitoring of Snowflake accounts\nfor anomalous behavior is also vital.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch2\u003ERecommendations\u003C/h2\u003E\n","\u003Cp\u003EThe following key recommendations are covered within each principle of\nSecurity & Governance:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EShared Responsibility Model\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EReliability and security are shared responsibilities between the\ncloud provider, Snowflake, and the customer. The \u003Cstrong\u003EShared\nResponsibility Model\u003C/strong\u003E outlines this division of responsibilities\nand is the foundation for all security recommendations. It is\nessential for customers to understand, document, and operationalize\nthese specific responsibilities to prevent gaps in security\nownership. You can find more information about this model in the\nSnowflake documentation:\n\u003Ca href=\"/en/resources/report/snowflake-shared-responsibility-model/\"\u003E/en/resources/report/snowflake-shared-responsibility-model/\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENetwork Security\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EYou can build a strong security perimeter by using \u003Cstrong\u003Enetwork\npolicies\u003C/strong\u003E to control network traffic to your Snowflake account.\nNetwork policies are a crucial first step in securing your\nenvironment by allowing or denying user access based on their IP\naddress. It is a best practice to define a clear set of network\npolicies that restrict access to only trusted IP addresses or IP\nranges. For more advanced network control, consider using features\nlike Snowflake's Private Connectivity options.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAuthentication & Authorization\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EAuthentication and authorization are fundamental to securing your\nSnowflake environment. You should use \u003Cstrong\u003ERole-Based Access Control\n(RBAC)\u003C/strong\u003E to manage user permissions and ensure that each user has\nthe minimum level of access required to perform their job duties, a\nprinciple known as \u003Cstrong\u003Eleast privilege\u003C/strong\u003E. Modern authentication\nmethods like federated authentication with SSO (Single Sign-On)\nshould be used whenever possible to simplify user management and\nimprove security.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EData Protection\u003C/strong\u003E\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EData protection involves implementing controls to protect sensitive\ndata at rest and in transit. Snowflake provides native features like\n\u003Cstrong\u003EDefault Encryption at Rest\u003C/strong\u003E and \u003Cstrong\u003EClient-Side Encryption\u003C/strong\u003E. You\ncan enhance this with \u003Cstrong\u003ECustomer-Managed Keys (CMK)\u003C/strong\u003E using\nSnowflake's integration with cloud provider key management services.\nAdditionally, features such as \u003Cstrong\u003ETime Travel\u003C/strong\u003E and \u003Cstrong\u003EFail-safe\u003C/strong\u003E\nprovide data protection and recovery from logical errors by allowing\nyou to restore data to a previous state. For more details, see the\ndocumentation on \u003Ca href=\"https://docs.snowflake.com/en/user-guide/data-time-travel\"\u003ETime\nTravel\u003C/a\u003E.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EData Governance\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EData governance ensures that data access, privacy, and compliance\ncontrols are enforced, auditable, and monitored. This includes the\nuse of \u003Cstrong\u003EDynamic Data Masking\u003C/strong\u003E and \u003Cstrong\u003ERow Access Policies\u003C/strong\u003E to\ncontrol who can see what data under what conditions.\n\u003Cstrong\u003EClassification\u003C/strong\u003E and \u003Cstrong\u003EObject Tracking\u003C/strong\u003E are also critical for\nidentifying and protecting sensitive data and maintaining data\nlineage.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EIncident Response\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EHaving a well-defined \u003Cstrong\u003ECyber Security Incident Response Plan\n(CSIRP)\u003C/strong\u003E is vital for preparing for security events. The plan\nshould include playbooks with actionable tasks and should be\nregularly tested through tabletop exercises to ensure effectiveness.\nRegular monitoring for anomalous behavior in your Snowflake accounts\nis key to early detection and rapid response to potential incidents.\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch2\u003ESecure the Perimeter\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003ESecuring the perimeter of a Snowflake environment is crucial for\nprotecting data and maintaining business continuity. A well-architected\nframework for this involves a multi-layered approach that addresses\nnetwork policies, identity and credential management, and authentication\nhardening. By implementing these controls, you can ensure that access to\nyour data platform is strictly controlled, external threats are\nproactively blocked, and your organization is resilient against\npotential security breaches.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EHardening the perimeter and network access\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EImplementing \u003Cstrong\u003ENetwork Policies\u003C/strong\u003E is a critical first step to securing\nyour Snowflake environment. These policies, such as Network ACLs, should\nbe used to restrict connections to your data platform from only approved\nand trusted IP ranges. Proactively mitigating data exfiltration pathways\nis also essential; this involves securing external stages, restricting\noutbound connectivity, and actively monitoring for high-volume data\negress. You can significantly reduce your attack surface by utilizing a\ncombination of user-level and account-level network policies.\nAccount-level policies prevent the use of stolen credentials from\nexploited IP addresses and ensure all users access the platform from\nknown IPs. User-level policies can be used to prevent end-users from\nusing service accounts and allow for enforced exceptions to\naccount-level policies. For further information, see the Snowflake\ndocumentation on network policies.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EIdentity and credential management\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EA robust security posture requires the \u003Cstrong\u003Eelimination of static\ncredentials\u003C/strong\u003E across your organization. Instead, you should mandate the\nadoption of modern authentication flows like SAML, Key Pair, and OAuth\nfor all identities, including human users, service accounts, and\nmachine-to-machine processes. This approach minimizes the risk of\ncredentials being compromised. It's also vital to establish a\n\u003Cstrong\u003EPrivileged Access Management (PAM) program\u003C/strong\u003E to govern, monitor, and\nstrictly control access for administrative and high-privilege roles.\nThis process helps to mitigate the risk of misuse of administrative\naccess. A formal process should exist for granting, reviewing, and\nrevoking high-privilege access, ideally with a tool to manage and\nmonitor these administrative sessions.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EHardening authentication\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EEnforcing \u003Cstrong\u003EMulti-Factor Authentication (MFA)\u003C/strong\u003E is a key recommendation\nfor hardening your Snowflake environment. Snowflake supports various MFA\nmethods, including TOTP (Time-based One-Time Password) authenticator\napps like Microsoft and Google Authenticator, as well as Passkeys and\nDUO, the only method with a "Push" notification option. It's recommended\nto avoid SMS as a fallback to prevent SIM swapping attacks by selecting\nthe "Tablet" option in DUO instead of "Phone". Additionally, you should\nimplement \u003Cstrong\u003EWorkload Identity Federation (WIF)\u003C/strong\u003E, allows\nfor service-to-service authentication method\nthat lets workloads, such as applications, services, or containers,\nauthenticate with Snowflake using their cloud provider’s native identity\nsystem, such as AWS Identity and Access Management (AWS IAM) roles,\nMicrosoft Entra ID (Managed Principles), and Google Cloud service\naccounts to get an attestation that Snowflake can use and validate.\u003C/p\u003E\n","\u003Ch2\u003EData Governance\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EThe Governance principle defines how sensitive data is accessed,\nprotected, and proven compliant. In Snowflake, this means translating\nbusiness rules into enforceable controls: masking and row policies,\nprojection constraints, role hierarchies, and auditable evidence, so\nthat teams can state with confidence who can see what, under what\nconditions, and how that access is monitored. Governance is most\neffective when it is automated and observable: tags drive policy\nattachment, Access History substantiates usage, and dashboards highlight\ndrift and exceptions. The broader disciplines of lineage, quality, and\ncontinuous improvement are addressed across other pillars, but their\noutcomes are strengthened by a sound governance baseline here.\u003C/p\u003E\n","\u003Ch3\u003EDesired outcome\u003C/h3\u003E\n","\u003Cp\u003EA well‑architected governance posture lets organizations demonstrate that sensitive data is consistently classified and protected across environments, access is role‑based and least‑privilege, row‑level and projection rules limit exposure to the minimal necessary surface, AI/LLM interactions are scoped and logged, and regulatory obligations are mapped to Snowflake‑native controls with reproducible evidence. When governance operates in this manner, audit readiness becomes routine and does not hinder delivery.\u003C/p\u003E\n","\u003Ch3\u003ECommon anti-patterns\u003C/h3\u003E\n","\u003Cp\u003EWeak governance often shows up as direct user‑to‑role grants without\nfederation, unmasked PII in widely used datasets, manual access reviews\nthat miss drift, agentic/LLM activity that is neither logged nor\nconstrained, and uncontrolled role/object growth that accumulates\ntechnical debt. These patterns increase the likelihood of over‑exposure\nand complicate audits.\u003C/p\u003E\n","\u003Ch3\u003EBenefits\u003C/h3\u003E\n","\u003Cp\u003EA cohesive approach reduces breach and compliance risk, accelerates\nonboarding and offboarding through automated RBAC, improves trust in\nanalytics and AI and shortens audit cycles by turning control checks\ninto repeatable queries and evidence packs. Teams gain faster access to\nthe right data because policies are pre‑bound and self‑enforcing.\u003C/p\u003E\n","\u003Ch3\u003ERisks\u003C/h3\u003E\n","\u003Cp\u003EAbsent these practices, unauthorized access to sensitive data becomes\nmore likely, regulatory obligations become hard to prove and model or\nagent outputs may inadvertently reveal protected information. Over time,\nunmanaged roles and objects increase operational drag and obscure\nownership.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003EStart by defining a policy model in business terms:\nwhat constitutes sensitive information, who requires access, and what\ncontextual factors must be considered (role, location, purpose). Express\nthose rules as tags and policies in Snowflake. Classify sensitive\ncolumns, apply masking and row access policies that reference tags, and\nroute consumption through curated views with explicit projection\nconstraints. Integrate with an Identity Provider so users receive\nprivileges via roles, not direct grants. Enable Access History and\nutilize Account Usage to create governance dashboards. Schedule drift\ndetection to flag untagged columns, unused or over‑privileged roles, and\ndetached policies. Finally, connect obligations (GDPR, HIPAA, PCI, SOX)\nto the specific Snowflake controls and the queries that produce\nevidence.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERecommendation checklist\u003C/strong\u003E\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EDefine RBAC hierarchy\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClassify/tag sensitive datasets, bind masking &\nRAP policies\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EEnable \u003Cstrong\u003EAccess History\u003C/strong\u003E and build audit\ndashboards\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EAutomate drift detection (orphan roles, untagged\ncolumns, policy detachment)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EConfigure \u003Cstrong\u003ECortex AI governance\u003C/strong\u003E (prompt\nlogging, redaction, agent scope)\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EBuild control-to-query library for regulatory\nevidence\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EReview governance scorecard quarterly (coverage,\nexceptions, audit readiness)\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EData privacy & protection\u003C/h3\u003E\n","\u003Ch4\u003ECLS (column‑level security)\u003C/h4\u003E\n","\u003Cp\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/security-column-ddm-intro\"\u003EColumn‑level\nsecurity\u003C/a\u003E\nprotects sensitive attributes with masking policies that adapt to\ncontext. In practice, tags like SENSITIVITY and REGULATORY_SCOPE travel\nwith columns and trigger masking automatically, while session attributes\nsuch as role, network location, or declared purpose inform whether data\nis shown in the clear or redacted. Deterministic masking can preserve\njoinability where required, and clear‑text access can be logged via\nsecure UDF patterns when justified. In regulated scenarios, tokenization\nmay be necessary; it should be paired with strict stewardship and\nevidence of necessity.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDesign approach\u003C/strong\u003E\nKeep base tables secured and expose consumers to policy‑protected views.\nSeparate administrative personas from analytical personas to avoid\nprivilege creep and ensure least privilege.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAssessment Prompts\u003C/strong\u003E\nWhich roles can view clear PII, and under what context? How are\nexceptions time‑boxed, tracked, and reviewed?\u003C/p\u003E\n","\u003Ch4\u003ERAP (row access policies)\u003C/h4\u003E\n","\u003Cp\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/security-row-intro\"\u003ERow access\npolicies\u003C/a\u003E\nconstrain visibility at the record level based on attributes like\ngeography or line of business. Centralizing rules in secure UDFs and\ndriving entitlements from reference tables makes policies explainable\nand maintainable. Performance should be validated against real\nworkloads, and pruning/clustering strategies used where helpful.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDesign Approach\u003C/strong\u003E\nAdopt a hub‑and‑spoke model: one policy per domain, so all child tables\nand views inherit the same semantics through tags.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAssessment Prompts\u003C/strong\u003E\nAre RAP rules managed from a single source of truth rather than embedded\nin views? What are the policy evaluation latency and cache hit rates\nunder load?\u003C/p\u003E\n","\u003Ch4\u003EProjection policy\u003C/h4\u003E\n","\u003Cp\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/projection-policies\"\u003EProjection\ncontrols\u003C/a\u003E\ndefine which columns (or combinations of columns) may be selected\ntogether, preventing risky joins (e.g., date of birth with ZIP and\ngender). Express these rules in curated secure views and verify them in\nCI so prohibited projections never reach production. Pair projection\nconstraints with\n\u003Ca href=\"https://docs.snowflake.com/en/user-guide/security-access-control-overview\"\u003Emasking\u003C/a\u003E\nand row access for layered protection.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EDesign Approach\u003C/strong\u003E\nPublish approved column bundles per persona and provide redaction views\nfor common but risky analytics patterns.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAssessment Prompts\u003C/strong\u003E\nWhich disallowed column combinations are blocked today? How are\nprojection constraints tested and reported in CI pipelines?\u003C/p\u003E\n","\u003Ch3\u003ERegulatory & compliance\u003C/h3\u003E\n","\u003Cp\u003ERegulatory alignment translates legal obligations into concrete\nSnowflake controls and reproducible evidence. A practical way to manage\nthis is to maintain a control catalog that maps each clause (for GDPR,\n\u003Ca href=\"https://medium.com/snowflake/how-snowflake-helps-with-hipaa-compliance-8e578f353b1a\"\u003EHIPAA\u003C/a\u003E,\nPCI, SOX, and others) to the tags, policies, and queries that\ndemonstrate enforcement. Evidence should be generated from Access\nHistory and Account Usage on a schedule, producing consistent,\nreviewer‑ready artifacts. For high‑risk data, segment databases and\nschemas and apply stricter RAP and masking baselines. This keeps audits\npredictable and allows quick re‑generation of a full evidence set -\nideally in hours rather than weeks.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAssessment Prompts\u003C/strong\u003E\nFor each regulation, which Snowflake controls satisfy which clauses? How\nquickly can a complete evidence pack be re‑built, and how is its\nfreshness tracked?\u003C/p\u003E\n","\u003Ch3\u003EMonitoring & reporting\u003C/h3\u003E\n","\u003Cp\u003EMonitoring proves that controls are effective and alerts teams to drift.\nA governance control center, implemented in Snowsight or an external BI\ntool, should surface tagging and masking coverage, access to sensitive\ndata, RAP evaluations, share usage, data quality scores, and the\nfreshness of audit evidence. Alerting should detect untagged new\ncolumns, policy detachments, anomalous access, and changes to external\nshares. For AI/LLM, track prompt volumes, redactions, tool usage, and\nviolations. Behind the scenes, a metrics lake pulls data from Account\nUsage, Information Schema, and Access History. Tasks and\n\u003Ca href=\"https://docs.snowflake.com/en/sql-reference/account-usage\"\u003Enotifications\u003C/a\u003E\ndrive alerts, and exception workflows integrate with ticketing, ensuring\neach alert has an assigned owner, runbook, and SLA.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAssessment Prompts\u003C/strong\u003E\nWhich risks are trending, which alerts produce action, and what is the\nfalse‑positive rate? Are owners and remediation steps clearly defined in\nevery alert type?\u003C/p\u003E\n","\u003Ch3\u003E\u003Cstrong\u003ESample Governance Scorecard\u003C/strong\u003E\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003ECoverage of tagged sensitive columns\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EPercentage of policy‑protected assets\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ENumber of sensitive reads\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ERAP evaluations\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EPolicy exceptions\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EMTTR for data‑quality and policy incidents\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EEvidence freshness\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003ETreat these as quarterly OKRs and use them to prioritize automation that\nremoves recurring toil.\u003C/p\u003E\n","\u003Ch2\u003EResponsible AI\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EResponsible AI is a crucial component of a comprehensive AI strategy,\nensuring that AI is developed and used in a manner that aligns with an\norganization's core values. It involves a commitment to harnessing the\ntransformative impact of AI to positively contribute to society. A\nwell-architected Responsible AI plan leverages key principles to manage\nrisks, uphold trust, and maintain compliance, ensuring that your\norganization is prepared for the security and ethical challenges that\narise from using AI. For a detailed overview of Snowflake's commitment\nto Responsible AI, refer to \u003Ca href=\"/en/company/responsible-ai/\"\u003Ethis\nstatement\u003C/a\u003E.\u003C/p\u003E\n","\u003Ch3\u003EDesired outcome\u003C/h3\u003E\n","\u003Cp\u003EBy implementing a robust Responsible AI strategy, your organization can\nconfidently innovate with AI while mitigating risks associated with\nprompt injection, insecure output handling, and data poisoning. This\nenables you to safeguard sensitive information, maintain customer trust,\nand fulfill regulatory requirements. Following these recommendations\nensures your data platform is resilient against AI-specific threats, and\nyour business is prepared for the ethical and security challenges of AI\nadoption.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAlignment to OWASP Top 10 for LLM Applications\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EAligning with the \u003Ca href=\"https://genai.owasp.org/resource/owasp-top-10-for-llm-applications-2025/\"\u003EOWASP Top 10 for Large Language Model (LLM)\nApplications\u003C/a\u003E\nis a fundamental best practice for a robust AI security posture. This\nframework provides a comprehensive list of the most critical security\nrisks associated with LLMs, such as Prompt Injection, Insecure Output\nHandling, and Training Data Poisoning. It is paramount to address these\nthreats to protect your applications and data. We recommend that you use\nthe OWASP guidelines as a checklist to assess and mitigate risks in your\nAI implementations, ensuring that your security controls are\ncomprehensive and up-to-date.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERole-Based Access Control (RBAC)\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EUser and Model RBAC provides granular control over who can access and\nuse specific AI models and data objects. This is a critical security\nmeasure because it helps enforce the principle of least privilege,\nensuring that users and applications only have the permissions necessary\nto perform their tasks. For example, Model RBAC can be used to create\nallow-lists or deny-lists for specific models, providing an extra layer\nof control over which LLMs are approved for use within your\norganization. We recommend leveraging the granular roles and\nentitlements available to tightly scope access, ensuring that all\ninteractions are logged and auditable.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ECortex Guard\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ECortex Guard is a powerful control that helps protect against common LLM\nvulnerabilities like Prompt Injection and Insecure Output Handling. It\nfunctions by performing input validation and output encoding to sanitize\npotentially malicious content before it can be executed or cause harm.\nThe importance of this feature cannot be overstated, as it provides a\ncritical defense against threats that could lead to data exfiltration or\ncode execution. We recommend enabling Cortex Guard to automatically\nsanitize and encode outputs, thereby reducing the risk of security\nvulnerabilities and simplifying the recovery process by eliminating the\nneed for manual sanitization.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAuditing & observability\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EAuditing and observability are essential for monitoring AI interactions,\ndetecting anomalies, and ensuring compliance. By logging all\nauthorization decisions, agent interactions, and LLM prompt traffic, you\ncan maintain a clear audit trail for traceability and non-repudiation.\nThe QUERY_HISTORY view, for example, logs function calls and\ninferencing, providing a record of all AI-related activities. We\nrecommend leveraging Snowflake's auditing features to monitor AI usage\nand ensure that all activities are aligned with your security and\ncompliance policies. You should also explore functions like\nSYSTEM$CORTEX_ANALYST_REQUESTS to extend real-time visibility for your\nadministrative and compliance teams.\u003C/p\u003E\n","\u003Ch3\u003EResponsible AI Checklist\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EAlign your AI strategy with the \u003Cstrong\u003EOWASP Top 10 for LLM\nApplications\u003C/strong\u003E to identify and prioritize security risks.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EEstablish \u003Cstrong\u003EUser and Model RBAC\u003C/strong\u003E to control access to AI models and\ndata objects, ensuring least privilege is enforced.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ELeverage \u003Cstrong\u003ECortex Guard\u003C/strong\u003E for input validation and output encoding\nto protect against common LLM vulnerabilities.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EUtilize \u003Cstrong\u003EAuditing and Observability\u003C/strong\u003E tools, such as the\nQUERY_HISTORY view, to monitor and log all AI interactions.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch2\u003EAssume Breach\u003C/h2\u003E\n","\u003Ch3\u003EOverview\u003C/h3\u003E\n","\u003Cp\u003EOrganizations commonly have Cybersecurity Incident Response Plans\n(CSIRP) that document and outline how they respond to and recover from\nsecurity incidents. Snowflake customers should have cybersecurity\nincident response plans in place for handling and responding to\ncybersecurity incidents that may compromise the confidentiality,\nintegrity and availability of their Snowflake Accounts in accordance\nwith industry standards.\u003C/p\u003E\n","\u003Ch3\u003ERecommendations\u003C/h3\u003E\n","\u003Cp\u003ETo be best prepared to deter and respond to threats, consider the\nfollowing recommendations based on industry best practices. These\nrecommendations are important to assess security posture, minimize\ndamage and downtime, prevent future threats, and protect reputational\nbrands. The following recommendations are aligned to industry standards\n(eg. \u003Ca href=\"https://csrc.nist.gov/publications/detail/sp/800-61/rev-2/final\"\u003ENIST 800-61, Rev. 2- Computer Security Incident Handling\nGuide\u003C/a\u003E,\n\u003Ca href=\"https://www.sans.org/media/score/504-incident-response-cycle.pdf\"\u003ESANS 504-B Incident Response\nCycle\u003C/a\u003E,\n\u003Ca href=\"https://attack.mitre.org/\"\u003EMITRE ATT&CK Framework\u003C/a\u003E, MITRE\n\u003Ca href=\"https://attack.mitre.org/matrices/enterprise/cloud/saas/\"\u003ESaaS\nMatrix\u003C/a\u003E,\n\u003Ca href=\"/product/security-and-trust-center/\"\u003ESnowflake’s Security & Trust\nCenter\u003C/a\u003E\n& \u003Ca href=\"https://www.cisecurity.org/benchmark/snowflake\"\u003ESnowflake CIS\nBenchmarks\u003C/a\u003E).\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ECybersecurity Incident Response Planning\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EA Cybersecurity Incident Response Plan (CIRP) is a procedural framework\nfor properly handling and responding to cybersecurity incidents that\ncould compromise the confidentiality, integrity, and availability of\ndata and business operations. The purpose of a CIRP is to minimize the\nadverse impact on business operations, quickly restore normal service,\nassist in meeting contractual and regulatory obligations, and protect\nsensitive data. A CIRP provides a clear strategy and a set of rules for\nan organization to follow, ensuring that all stakeholders know their\nroles and responsibilities during a security event. Organizations must\nconsult with their internal security and legal teams to align the plan\nwith their specific program requirements.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESANS Incident Response Phases\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EThe \u003Ca href=\"https://www.sans.org/security-resources/glossary-of-terms/incident-response\"\u003ESANS Incident Response\nPhases\u003C/a\u003E\nare a structured, six-step cycle for handling cybersecurity incidents.\nThis framework provides a standardized and repeatable process for\nincident handling, which is crucial for a swift and effective response.\nBy following these phases—Preparation, Identification, Containment,\nEradication, Recovery, and Lessons Learned—your organization can ensure\nthat all necessary actions are taken in a logical order, from\npre-incident readiness to post-incident analysis. We strongly advise\nthat your incident response team members receive training on these\nphases and are provided with the necessary access and tools to perform\ntheir duties effectively.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EShared Responsibility Model\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EThe Shared Responsibility Model defines the specific security\nobligations of both the customer and Snowflake. Understanding this model\nis critical for effective cybersecurity, as it clarifies which security\ncontrols you are responsible for implementing and managing, such as\nprotecting against social engineering, hardening account configurations,\nand managing access controls for sensitive data. We recommend you use\nthis model to conduct a thorough risk assessment and ensure that your\nown Governance, Risk, and Compliance teams are aligned with their\nresponsibilities in securing your Snowflake deployment.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EIdentity & Access Management (IAM)\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EIdentity & Access Management (IAM) is a security discipline that ensures\nthe right individuals and applications have the right access to the\nright resources at the right time. Implementing a robust IAM strategy is\nparamount to preventing unauthorized access and mitigating the risk of\ncredential compromise. We recommend enforcing modern authentication\nprotocols, such as SAML 2.0, for human users and OAuth or Key Pair\nauthentication for programmatic use cases, to minimize the use of static\ncredentials. Additionally, apply the Principle of Least Privilege,\nensuring users and roles have only the minimum permissions necessary to\nperform their duties, and limit the number of users with the powerful\nACCOUNTADMIN role.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENetwork security\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ENetwork security involves the use of policies and controls to protect\nyour network and data from unauthorized access and cyberattacks. This is\nimportant for minimizing your attack surface and preventing data\nexfiltration. Snowflake provides customer-configurable Network Policies\nand Network Rules that can restrict access to specific IP ranges (CIDR\nblocks), effectively terminating public access to your Snowflake\naccount. We advise you to leverage private networking services provided\nby cloud providers to ensure all traffic remains within a trusted,\nprivate network. All traffic to Snowflake is encrypted in transit using\nTLS 1.2, providing confidentiality and data integrity.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EData exfiltration mitigations\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003EData Exfiltration Mitigations are controls designed to prevent or\nmonitor the unauthorized transfer of data out of your Snowflake\nenvironment. Data exfiltration poses a significant risk to data\nconfidentiality and can lead to severe business consequences. Snowflake\nprovides account-level parameters that can prevent ad-hoc data unload\noperations to external stages and require the use of a storage\nintegration object for stage creation and operations. It is a best\npractice to enable these preventative controls to limit data movement\nand supplement them with continuous monitoring of privileged objects to\ndetect suspicious activity. For more information, please see the\nSnowflake documentation on \u003Ca href=\"https://docs.snowflake.com/en/user-guide/security-encryption-exfiltration-prevention\"\u003Epreventing data\nexfiltration\u003C/a\u003E.\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETri-Secret Secure & Data Replication\u003C/strong\u003E\u003C/p\u003E\n","\u003Cp\u003ETri-Secret Secure is a security feature that provides an additional\nlayer of data protection by enabling you to manage your own\ncustomer-managed key (CMK). This capability is essential for managing\nrisk in an "assume breach" scenario, as revoking the CMK will prevent\nthe decryption of all customer data objects at the account level. We\nrecommend that you also enable data replication to a secondary account\nto support your business continuity plan. This allows for rapid recovery\nin a disaster recovery scenario, ensuring you can meet your Recovery\nTime Objective (RTO) and Recovery Point Objective (RPO) requirements.\u003C/p\u003E\n","\u003Ch2\u003EIdentify and assess threat\u003C/h2\u003E\n","\u003Ch3\u003EIdentification phase - audit\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EAccess your \u003Cstrong\u003EAccount Usage\u003C/strong\u003E database, which provides 365 days of\n"tamper proof" audit logs.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EUse the QUERY_HISTORY and ACCESS_HISTORY views to investigate a\npotentially compromised user.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EQuery the QUERY_HISTORY view to identify any unauthorized changes,\nsuch as privilege escalation, security configuration changes, or\ndata object modifications.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003ECorrelate the compromised user's activity with known threat\nintelligence feeds to identify potential malicious activity.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003EContaining Impact\u003C/h3\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EContainment:\u003C/strong\u003E Immediately disable the identified user account or\nintegration to prevent further compromise.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EEradication:\u003C/strong\u003E Perform a detailed forensic analysis by reviewing\naudit logs to ensure the initial compromise is fully contained and\nthe threat is removed.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ERecovery:\u003C/strong\u003E Restore normal business functionality by leveraging\n\u003Cstrong\u003ETime Travel\u003C/strong\u003E to recover from unintended data object changes.\nAlternatively, use replicated data objects in a secondary account to\nrestore service in a multi-region redundancy scenario.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch2\u003ETradeoffs & considerations\u003C/h2\u003E\n","\u003Cp\u003EUse the following checklist to assess your organization's readiness for\nhandling a cybersecurity incident:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EIncident response plan:\u003C/strong\u003E Is a formal CSIRP in place that aligns\nwith industry standards like NIST and SANS?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ESecurity features:\u003C/strong\u003E Have you implemented Snowflake's recommended\nsecurity features, such as network policies, multi-factor\nauthentication (MFA), and data classification?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EAudit & monitoring:\u003C/strong\u003E Do you have a process to regularly audit and\nmonitor Snowflake's Account Usage logs for indicators of compromise\n(IoCs) and security anomalies?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETabletop exercises:\u003C/strong\u003E Do you conduct regular "tabletop" exercises to\ntest your CIRP and ensure your team can execute the plan efficiently\nunder pressure?\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003EPostmortem & lessons learned:\u003C/strong\u003E Do you have a structured process for\nconducting a postmortem analysis of all security incidents and false\npositives to improve your threat model and security architecture?\u003C/p\u003E\n\u003C/li\u003E\u003C/ul\u003E"],"description":"","title":"Security & Governance Pillar","isDeveloperGuidesPage":false,":items":{},":itemsOrder":[],"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],"elements":{"quickstartArticleBody":{"dataType":"string","value":"## Overview\n\nThe Security & Governance pillar focuses on building a secure and\ncompliant Snowflake environment by implementing the principles of the\n**Confidentiality, Integrity, and Availability (CIA)** triad. The\nrecommendations provided within this framework are based on the **Shared\nResponsibility Model** and focus on the security controls that are the\ncustomer's responsibility. The goal is to minimize security risks by\nsecuring the Snowflake perimeter, using the principle of least privilege\nfor data access, responsibly deploying AI, and preparing for security\nincidents.\n\n## Principles\n\n### Secure the perimeter\n\n\u003E A strong security perimeter is built using network, identity, and\n\u003E policy constructs. You should assess network traffic to and from your\n\u003E Snowflake accounts to ensure network and endpoint security are in\n\u003E place for all connections. For identities, leverage modern\n\u003E authentication and authorization flows and enforce conditional access\n\u003E policies for Snowflake accounts.\n\n### Governance\n\n\u003E Governance in the security pillar is about enforcing, monitoring, and\n\u003E auditing data access, privacy, and compliance controls. This ensures\n\u003E that auditors can prove who can see what, and under what conditions.\n\u003E Broader governance concepts like data quality and lineage are\n\u003E addressed in other pillars.\n\n### Responsible AI\n\n\u003E The rapid adoption of AI capabilities brings security concerns,\n\u003E particularly regarding the protection of sensitive data. It's crucial\n\u003E to use AI responsibly and ensure that AI deployments are secure within\n\u003E your Snowflake environment.\n\n### Assume breach\n\n\u003E You must prepare for security events by having established **Cyber\n\u003E Security Incident Response Plans (CSIRP)** specifically for your\n\u003E Snowflake accounts. This includes creating playbooks with actionable\n\u003E tasks for different incident scenarios and conducting regular training\n\u003E and tabletop exercises. Continuous monitoring of Snowflake accounts\n\u003E for anomalous behavior is also vital.\n\n## Recommendations\n\nThe following key recommendations are covered within each principle of\nSecurity & Governance:\n\n- **Shared Responsibility Model**\n\n  - Reliability and security are shared responsibilities between the\n    cloud provider, Snowflake, and the customer. The **Shared\n    Responsibility Model** outlines this division of responsibilities\n    and is the foundation for all security recommendations. It is\n    essential for customers to understand, document, and operationalize\n    these specific responsibilities to prevent gaps in security\n    ownership. You can find more information about this model in the\n    Snowflake documentation:\n    [/en/resources/report/snowflake-shared-responsibility-model/](/en/resources/report/snowflake-shared-responsibility-model/)\n\n- **Network Security**\n\n  - You can build a strong security perimeter by using **network\n    policies** to control network traffic to your Snowflake account.\n    Network policies are a crucial first step in securing your\n    environment by allowing or denying user access based on their IP\n    address. It is a best practice to define a clear set of network\n    policies that restrict access to only trusted IP addresses or IP\n    ranges. For more advanced network control, consider using features\n    like Snowflake's Private Connectivity options.\n\n- **Authentication & Authorization**\n\n  - Authentication and authorization are fundamental to securing your\n    Snowflake environment. You should use **Role-Based Access Control\n    (RBAC)** to manage user permissions and ensure that each user has\n    the minimum level of access required to perform their job duties, a\n    principle known as **least privilege**. Modern authentication\n    methods like federated authentication with SSO (Single Sign-On)\n    should be used whenever possible to simplify user management and\n    improve security.\n\n- **Data Protection**\n\n  - Data protection involves implementing controls to protect sensitive\n    data at rest and in transit. Snowflake provides native features like\n    **Default Encryption at Rest** and **Client-Side Encryption**. You\n    can enhance this with **Customer-Managed Keys (CMK)** using\n    Snowflake's integration with cloud provider key management services.\n    Additionally, features such as **Time Travel** and **Fail-safe**\n    provide data protection and recovery from logical errors by allowing\n    you to restore data to a previous state. For more details, see the\n    documentation on [Time\n    Travel](https://docs.snowflake.com/en/user-guide/data-time-travel).\n\n- **Data Governance**\n\n  Data governance ensures that data access, privacy, and compliance\n    controls are enforced, auditable, and monitored. This includes the\n    use of **Dynamic Data Masking** and **Row Access Policies** to\n    control who can see what data under what conditions.\n    **Classification** and **Object Tracking** are also critical for\n    identifying and protecting sensitive data and maintaining data\n    lineage.\n\n- **Incident Response**\n\n  Having a well-defined **Cyber Security Incident Response Plan\n    (CSIRP)** is vital for preparing for security events. The plan\n    should include playbooks with actionable tasks and should be\n    regularly tested through tabletop exercises to ensure effectiveness.\n    Regular monitoring for anomalous behavior in your Snowflake accounts\n    is key to early detection and rapid response to potential incidents.\n\n## Secure the Perimeter\n\n### Overview\n\nSecuring the perimeter of a Snowflake environment is crucial for\nprotecting data and maintaining business continuity. A well-architected\nframework for this involves a multi-layered approach that addresses\nnetwork policies, identity and credential management, and authentication\nhardening. By implementing these controls, you can ensure that access to\nyour data platform is strictly controlled, external threats are\nproactively blocked, and your organization is resilient against\npotential security breaches.\n\n### Recommendations\n\n**Hardening the perimeter and network access**\n\nImplementing **Network Policies** is a critical first step to securing\nyour Snowflake environment. These policies, such as Network ACLs, should\nbe used to restrict connections to your data platform from only approved\nand trusted IP ranges. Proactively mitigating data exfiltration pathways\nis also essential; this involves securing external stages, restricting\noutbound connectivity, and actively monitoring for high-volume data\negress. You can significantly reduce your attack surface by utilizing a\ncombination of user-level and account-level network policies.\nAccount-level policies prevent the use of stolen credentials from\nexploited IP addresses and ensure all users access the platform from\nknown IPs. User-level policies can be used to prevent end-users from\nusing service accounts and allow for enforced exceptions to\naccount-level policies. For further information, see the Snowflake\ndocumentation on network policies.\n\n**Identity and credential management**\n\nA robust security posture requires the **elimination of static\ncredentials** across your organization. Instead, you should mandate the\nadoption of modern authentication flows like SAML, Key Pair, and OAuth\nfor all identities, including human users, service accounts, and\nmachine-to-machine processes. This approach minimizes the risk of\ncredentials being compromised. It's also vital to establish a\n**Privileged Access Management (PAM) program** to govern, monitor, and\nstrictly control access for administrative and high-privilege roles.\nThis process helps to mitigate the risk of misuse of administrative\naccess. A formal process should exist for granting, reviewing, and\nrevoking high-privilege access, ideally with a tool to manage and\nmonitor these administrative sessions.\n\n**Hardening authentication**\n\nEnforcing **Multi-Factor Authentication (MFA)** is a key recommendation\nfor hardening your Snowflake environment. Snowflake supports various MFA\nmethods, including TOTP (Time-based One-Time Password) authenticator\napps like Microsoft and Google Authenticator, as well as Passkeys and\nDUO, the only method with a \"Push\" notification option. It's recommended\nto avoid SMS as a fallback to prevent SIM swapping attacks by selecting\nthe \"Tablet\" option in DUO instead of \"Phone\". Additionally, you should\nimplement **Workload Identity Federation (WIF)**, allows\nfor service-to-service authentication method\nthat lets workloads, such as applications, services, or containers,\nauthenticate with Snowflake using their cloud provider’s native identity\nsystem, such as AWS Identity and Access Management (AWS IAM) roles,\nMicrosoft Entra ID (Managed Principles), and Google Cloud service\naccounts to get an attestation that Snowflake can use and validate.\n\n## Data Governance\n\n### Overview\n\nThe Governance principle defines how sensitive data is accessed,\nprotected, and proven compliant. In Snowflake, this means translating\nbusiness rules into enforceable controls: masking and row policies,\nprojection constraints, role hierarchies, and auditable evidence, so\nthat teams can state with confidence who can see what, under what\nconditions, and how that access is monitored. Governance is most\neffective when it is automated and observable: tags drive policy\nattachment, Access History substantiates usage, and dashboards highlight\ndrift and exceptions. The broader disciplines of lineage, quality, and\ncontinuous improvement are addressed across other pillars, but their\noutcomes are strengthened by a sound governance baseline here.\n\n### Desired outcome\n\nA well‑architected governance posture lets organizations demonstrate that sensitive data is consistently classified and protected across environments, access is role‑based and least‑privilege, row‑level and projection rules limit exposure to the minimal necessary surface, AI/LLM interactions are scoped and logged, and regulatory obligations are mapped to Snowflake‑native controls with reproducible evidence. When governance operates in this manner, audit readiness becomes routine and does not hinder delivery.\n\n### Common anti-patterns\n\nWeak governance often shows up as direct user‑to‑role grants without\nfederation, unmasked PII in widely used datasets, manual access reviews\nthat miss drift, agentic/LLM activity that is neither logged nor\nconstrained, and uncontrolled role/object growth that accumulates\ntechnical debt. These patterns increase the likelihood of over‑exposure\nand complicate audits.\n\n### Benefits\n\nA cohesive approach reduces breach and compliance risk, accelerates\nonboarding and offboarding through automated RBAC, improves trust in\nanalytics and AI and shortens audit cycles by turning control checks\ninto repeatable queries and evidence packs. Teams gain faster access to\nthe right data because policies are pre‑bound and self‑enforcing.\n\n### Risks\n\nAbsent these practices, unauthorized access to sensitive data becomes\nmore likely, regulatory obligations become hard to prove and model or\nagent outputs may inadvertently reveal protected information. Over time,\nunmanaged roles and objects increase operational drag and obscure\nownership.\n\n### Recommendations\n\nStart by defining a policy model in business terms:\nwhat constitutes sensitive information, who requires access, and what\ncontextual factors must be considered (role, location, purpose). Express\nthose rules as tags and policies in Snowflake. Classify sensitive\ncolumns, apply masking and row access policies that reference tags, and\nroute consumption through curated views with explicit projection\nconstraints. Integrate with an Identity Provider so users receive\nprivileges via roles, not direct grants. Enable Access History and\nutilize Account Usage to create governance dashboards. Schedule drift\ndetection to flag untagged columns, unused or over‑privileged roles, and\ndetached policies. Finally, connect obligations (GDPR, HIPAA, PCI, SOX)\nto the specific Snowflake controls and the queries that produce\nevidence.\n\n**Recommendation checklist**\n\n1.  Define RBAC hierarchy\n\n2.  Classify/tag sensitive datasets, bind masking &\n    RAP policies\n\n3.  Enable **Access History** and build audit\n    dashboards\n\n4.  Automate drift detection (orphan roles, untagged\n    columns, policy detachment)\n\n5.  Configure **Cortex AI governance** (prompt\n    logging, redaction, agent scope)\n\n6.  Build control-to-query library for regulatory\n    evidence\n\n7.  Review governance scorecard quarterly (coverage,\n    exceptions, audit readiness)\n\n### Data privacy & protection\n\n#### CLS (column‑level security)\n\n[Column‑level\nsecurity](https://docs.snowflake.com/en/user-guide/security-column-ddm-intro)\nprotects sensitive attributes with masking policies that adapt to\ncontext. In practice, tags like SENSITIVITY and REGULATORY_SCOPE travel\nwith columns and trigger masking automatically, while session attributes\nsuch as role, network location, or declared purpose inform whether data\nis shown in the clear or redacted. Deterministic masking can preserve\njoinability where required, and clear‑text access can be logged via\nsecure UDF patterns when justified. In regulated scenarios, tokenization\nmay be necessary; it should be paired with strict stewardship and\nevidence of necessity.\n\n**Design approach**\nKeep base tables secured and expose consumers to policy‑protected views.\nSeparate administrative personas from analytical personas to avoid\nprivilege creep and ensure least privilege.\n\n**Assessment Prompts**\nWhich roles can view clear PII, and under what context? How are\nexceptions time‑boxed, tracked, and reviewed?\n\n#### RAP (row access policies)\n\n[Row access\npolicies](https://docs.snowflake.com/en/user-guide/security-row-intro)\nconstrain visibility at the record level based on attributes like\ngeography or line of business. Centralizing rules in secure UDFs and\ndriving entitlements from reference tables makes policies explainable\nand maintainable. Performance should be validated against real\nworkloads, and pruning/clustering strategies used where helpful.\n\n**Design Approach**\nAdopt a hub‑and‑spoke model: one policy per domain, so all child tables\nand views inherit the same semantics through tags.\n\n**Assessment Prompts**\nAre RAP rules managed from a single source of truth rather than embedded\nin views? What are the policy evaluation latency and cache hit rates\nunder load?\n\n#### Projection policy\n\n[Projection\ncontrols](https://docs.snowflake.com/en/user-guide/projection-policies)\ndefine which columns (or combinations of columns) may be selected\ntogether, preventing risky joins (e.g., date of birth with ZIP and\ngender). Express these rules in curated secure views and verify them in\nCI so prohibited projections never reach production. Pair projection\nconstraints with\n[masking](https://docs.snowflake.com/en/user-guide/security-access-control-overview)\nand row access for layered protection.\n\n**Design Approach**\nPublish approved column bundles per persona and provide redaction views\nfor common but risky analytics patterns.\n\n**Assessment Prompts**\nWhich disallowed column combinations are blocked today? How are\nprojection constraints tested and reported in CI pipelines?\n\n### Regulatory & compliance\n\nRegulatory alignment translates legal obligations into concrete\nSnowflake controls and reproducible evidence. A practical way to manage\nthis is to maintain a control catalog that maps each clause (for GDPR,\n[HIPAA](https://medium.com/snowflake/how-snowflake-helps-with-hipaa-compliance-8e578f353b1a),\nPCI, SOX, and others) to the tags, policies, and queries that\ndemonstrate enforcement. Evidence should be generated from Access\nHistory and Account Usage on a schedule, producing consistent,\nreviewer‑ready artifacts. For high‑risk data, segment databases and\nschemas and apply stricter RAP and masking baselines. This keeps audits\npredictable and allows quick re‑generation of a full evidence set -\nideally in hours rather than weeks.\n\n**Assessment Prompts**\nFor each regulation, which Snowflake controls satisfy which clauses? How\nquickly can a complete evidence pack be re‑built, and how is its\nfreshness tracked?\n\n### Monitoring & reporting\n\nMonitoring proves that controls are effective and alerts teams to drift.\nA governance control center, implemented in Snowsight or an external BI\ntool, should surface tagging and masking coverage, access to sensitive\ndata, RAP evaluations, share usage, data quality scores, and the\nfreshness of audit evidence. Alerting should detect untagged new\ncolumns, policy detachments, anomalous access, and changes to external\nshares. For AI/LLM, track prompt volumes, redactions, tool usage, and\nviolations. Behind the scenes, a metrics lake pulls data from Account\nUsage, Information Schema, and Access History. Tasks and\n[notifications](https://docs.snowflake.com/en/sql-reference/account-usage)\ndrive alerts, and exception workflows integrate with ticketing, ensuring\neach alert has an assigned owner, runbook, and SLA.\n\n**Assessment Prompts**\nWhich risks are trending, which alerts produce action, and what is the\nfalse‑positive rate? Are owners and remediation steps clearly defined in\nevery alert type?\n\n### **Sample Governance Scorecard**\n\n- Coverage of tagged sensitive columns\n\n- Percentage of policy‑protected assets\n\n- Number of sensitive reads\n\n- RAP evaluations\n\n- Policy exceptions\n\n- MTTR for data‑quality and policy incidents\n\n- Evidence freshness\n\nTreat these as quarterly OKRs and use them to prioritize automation that\nremoves recurring toil.\n\n## Responsible AI\n\n### Overview\n\nResponsible AI is a crucial component of a comprehensive AI strategy,\nensuring that AI is developed and used in a manner that aligns with an\norganization's core values. It involves a commitment to harnessing the\ntransformative impact of AI to positively contribute to society. A\nwell-architected Responsible AI plan leverages key principles to manage\nrisks, uphold trust, and maintain compliance, ensuring that your\norganization is prepared for the security and ethical challenges that\narise from using AI. For a detailed overview of Snowflake's commitment\nto Responsible AI, refer to [this\nstatement](/en/company/responsible-ai/).\n\n### Desired outcome\n\nBy implementing a robust Responsible AI strategy, your organization can\nconfidently innovate with AI while mitigating risks associated with\nprompt injection, insecure output handling, and data poisoning. This\nenables you to safeguard sensitive information, maintain customer trust,\nand fulfill regulatory requirements. Following these recommendations\nensures your data platform is resilient against AI-specific threats, and\nyour business is prepared for the ethical and security challenges of AI\nadoption.\n\n### Recommendations\n\n**Alignment to OWASP Top 10 for LLM Applications**\n\nAligning with the [OWASP Top 10 for Large Language Model (LLM)\nApplications](https://genai.owasp.org/resource/owasp-top-10-for-llm-applications-2025/)\nis a fundamental best practice for a robust AI security posture. This\nframework provides a comprehensive list of the most critical security\nrisks associated with LLMs, such as Prompt Injection, Insecure Output\nHandling, and Training Data Poisoning. It is paramount to address these\nthreats to protect your applications and data. We recommend that you use\nthe OWASP guidelines as a checklist to assess and mitigate risks in your\nAI implementations, ensuring that your security controls are\ncomprehensive and up-to-date.\n\n**Role-Based Access Control (RBAC)**\n\nUser and Model RBAC provides granular control over who can access and\nuse specific AI models and data objects. This is a critical security\nmeasure because it helps enforce the principle of least privilege,\nensuring that users and applications only have the permissions necessary\nto perform their tasks. For example, Model RBAC can be used to create\nallow-lists or deny-lists for specific models, providing an extra layer\nof control over which LLMs are approved for use within your\norganization. We recommend leveraging the granular roles and\nentitlements available to tightly scope access, ensuring that all\ninteractions are logged and auditable.\n\n**Cortex Guard**\n\nCortex Guard is a powerful control that helps protect against common LLM\nvulnerabilities like Prompt Injection and Insecure Output Handling. It\nfunctions by performing input validation and output encoding to sanitize\npotentially malicious content before it can be executed or cause harm.\nThe importance of this feature cannot be overstated, as it provides a\ncritical defense against threats that could lead to data exfiltration or\ncode execution. We recommend enabling Cortex Guard to automatically\nsanitize and encode outputs, thereby reducing the risk of security\nvulnerabilities and simplifying the recovery process by eliminating the\nneed for manual sanitization.\n\n**Auditing & observability**\n\nAuditing and observability are essential for monitoring AI interactions,\ndetecting anomalies, and ensuring compliance. By logging all\nauthorization decisions, agent interactions, and LLM prompt traffic, you\ncan maintain a clear audit trail for traceability and non-repudiation.\nThe QUERY_HISTORY view, for example, logs function calls and\ninferencing, providing a record of all AI-related activities. We\nrecommend leveraging Snowflake's auditing features to monitor AI usage\nand ensure that all activities are aligned with your security and\ncompliance policies. You should also explore functions like\nSYSTEM\\$CORTEX_ANALYST_REQUESTS to extend real-time visibility for your\nadministrative and compliance teams.\n\n### Responsible AI Checklist\n\n1.  Align your AI strategy with the **OWASP Top 10 for LLM\n    Applications** to identify and prioritize security risks.\n\n2.  Establish **User and Model RBAC** to control access to AI models and\n    data objects, ensuring least privilege is enforced.\n\n3.  Leverage **Cortex Guard** for input validation and output encoding\n    to protect against common LLM vulnerabilities.\n\n4.  Utilize **Auditing and Observability** tools, such as the\n    QUERY_HISTORY view, to monitor and log all AI interactions.\n\n## Assume Breach\n\n### Overview\n\nOrganizations commonly have Cybersecurity Incident Response Plans\n(CSIRP) that document and outline how they respond to and recover from\nsecurity incidents. Snowflake customers should have cybersecurity\nincident response plans in place for handling and responding to\ncybersecurity incidents that may compromise the confidentiality,\nintegrity and availability of their Snowflake Accounts in accordance\nwith industry standards.\n\n### Recommendations\n\nTo be best prepared to deter and respond to threats, consider the\nfollowing recommendations based on industry best practices. These\nrecommendations are important to assess security posture, minimize\ndamage and downtime, prevent future threats, and protect reputational\nbrands. The following recommendations are aligned to industry standards\n(eg. [NIST 800-61, Rev. 2- Computer Security Incident Handling\nGuide](https://csrc.nist.gov/publications/detail/sp/800-61/rev-2/final),\n[SANS 504-B Incident Response\nCycle](https://www.sans.org/media/score/504-incident-response-cycle.pdf),\n[MITRE ATT&CK Framework](https://attack.mitre.org/), MITRE\n[SaaS\nMatrix](https://attack.mitre.org/matrices/enterprise/cloud/saas/),\n[Snowflake’s Security & Trust\nCenter](/product/security-and-trust-center/)\n& [Snowflake CIS\nBenchmarks](https://www.cisecurity.org/benchmark/snowflake)).\n\n**Cybersecurity Incident Response Planning**\n\nA Cybersecurity Incident Response Plan (CIRP) is a procedural framework\nfor properly handling and responding to cybersecurity incidents that\ncould compromise the confidentiality, integrity, and availability of\ndata and business operations. The purpose of a CIRP is to minimize the\nadverse impact on business operations, quickly restore normal service,\nassist in meeting contractual and regulatory obligations, and protect\nsensitive data. A CIRP provides a clear strategy and a set of rules for\nan organization to follow, ensuring that all stakeholders know their\nroles and responsibilities during a security event. Organizations must\nconsult with their internal security and legal teams to align the plan\nwith their specific program requirements.\n\n**SANS Incident Response Phases**\n\nThe [SANS Incident Response\nPhases](https://www.sans.org/security-resources/glossary-of-terms/incident-response)\nare a structured, six-step cycle for handling cybersecurity incidents.\nThis framework provides a standardized and repeatable process for\nincident handling, which is crucial for a swift and effective response.\nBy following these phases—Preparation, Identification, Containment,\nEradication, Recovery, and Lessons Learned—your organization can ensure\nthat all necessary actions are taken in a logical order, from\npre-incident readiness to post-incident analysis. We strongly advise\nthat your incident response team members receive training on these\nphases and are provided with the necessary access and tools to perform\ntheir duties effectively.\n\n**Shared Responsibility Model**\n\nThe Shared Responsibility Model defines the specific security\nobligations of both the customer and Snowflake. Understanding this model\nis critical for effective cybersecurity, as it clarifies which security\ncontrols you are responsible for implementing and managing, such as\nprotecting against social engineering, hardening account configurations,\nand managing access controls for sensitive data. We recommend you use\nthis model to conduct a thorough risk assessment and ensure that your\nown Governance, Risk, and Compliance teams are aligned with their\nresponsibilities in securing your Snowflake deployment.\n\n**Identity & Access Management (IAM)**\n\nIdentity & Access Management (IAM) is a security discipline that ensures\nthe right individuals and applications have the right access to the\nright resources at the right time. Implementing a robust IAM strategy is\nparamount to preventing unauthorized access and mitigating the risk of\ncredential compromise. We recommend enforcing modern authentication\nprotocols, such as SAML 2.0, for human users and OAuth or Key Pair\nauthentication for programmatic use cases, to minimize the use of static\ncredentials. Additionally, apply the Principle of Least Privilege,\nensuring users and roles have only the minimum permissions necessary to\nperform their duties, and limit the number of users with the powerful\nACCOUNTADMIN role.\n\n**Network security**\n\nNetwork security involves the use of policies and controls to protect\nyour network and data from unauthorized access and cyberattacks. This is\nimportant for minimizing your attack surface and preventing data\nexfiltration. Snowflake provides customer-configurable Network Policies\nand Network Rules that can restrict access to specific IP ranges (CIDR\nblocks), effectively terminating public access to your Snowflake\naccount. We advise you to leverage private networking services provided\nby cloud providers to ensure all traffic remains within a trusted,\nprivate network. All traffic to Snowflake is encrypted in transit using\nTLS 1.2, providing confidentiality and data integrity.\n\n**Data exfiltration mitigations**\n\nData Exfiltration Mitigations are controls designed to prevent or\nmonitor the unauthorized transfer of data out of your Snowflake\nenvironment. Data exfiltration poses a significant risk to data\nconfidentiality and can lead to severe business consequences. Snowflake\nprovides account-level parameters that can prevent ad-hoc data unload\noperations to external stages and require the use of a storage\nintegration object for stage creation and operations. It is a best\npractice to enable these preventative controls to limit data movement\nand supplement them with continuous monitoring of privileged objects to\ndetect suspicious activity. For more information, please see the\nSnowflake documentation on [preventing data\nexfiltration](https://docs.snowflake.com/en/user-guide/security-encryption-exfiltration-prevention).\n\n**Tri-Secret Secure & Data Replication**\n\nTri-Secret Secure is a security feature that provides an additional\nlayer of data protection by enabling you to manage your own\ncustomer-managed key (CMK). This capability is essential for managing\nrisk in an \"assume breach\" scenario, as revoking the CMK will prevent\nthe decryption of all customer data objects at the account level. We\nrecommend that you also enable data replication to a secondary account\nto support your business continuity plan. This allows for rapid recovery\nin a disaster recovery scenario, ensuring you can meet your Recovery\nTime Objective (RTO) and Recovery Point Objective (RPO) requirements.\n\n## Identify and assess threat\n\n### Identification phase - audit\n\n1.  Access your **Account Usage** database, which provides 365 days of\n    \"tamper proof\" audit logs.\n\n2.  Use the QUERY_HISTORY and ACCESS_HISTORY views to investigate a\n    potentially compromised user.\n\n3.  Query the QUERY_HISTORY view to identify any unauthorized changes,\n    such as privilege escalation, security configuration changes, or\n    data object modifications.\n\n4.  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