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Please rotate your device To continue exploring this website, please rotate your device to a vertical orientation Security at the foundation. Safety across the stack. Talk to an engineerRead the security docs model safety Understand model behavior Baseten and Goodfire are working to surface safety signals inside supported open models during inference - helping teams identify risky behavior and decide when to intervene. Stay up to date on Project Beacon Secure Agent Runtime Set boundaries for agents Baseten supports NVIDIA OpenShell in its sandbox cloud so teams can apply boundaries around credentials, files, network access, and tools outside the agent’s own code. Learn about our partnership with NVIDIA Open research Advance safer open models Base Labs develops and shares research on training, monitoring, and evaluating open models. Baseten connects that work to production infrastructure, helping turn research into practical approaches to model safety. Explore Base Labs' safety research Security built into the whole stack Trust across the entire AI stack 01 Protect the workload Run sensitive inference with encryption, workload isolation, and clear data-retention practices. Align networking and deployment choices with your security requirements. Baseten Enterprise Security 02 Govern access and change Control who can deploy, configure, and operate production AI. Use enterprise identity, role-based permissions, and reviewed release workflows to keep access and changes accountable. Baseten Enterprise Security 03 Address model risk Safety extends beyond protecting data. Evaluate models for your use case, define acceptable behavior, and plan how your application should respond to unsafe outputs, sensitive-data exposure, or attempts to redirect it. Model safety 04 Put boundaries around actions A model’s response should not become unrestricted permission to act. Define which tools, data, and systems an agent can reach—and where sensitive actions require validation or human approval. Agent safety Secure Foundation Enterprise security controls. Zero data retention by default Serve models with zero retention of inference inputs and outputs, plus encryption in transit and at rest. Protect sensitive customer and proprietary data as models run. Learn more about data privacy Manage access Centralize authentication with SSO and manage permissions with role-based access controls. Use service accounts to automate workflows without sharing human credentials. Read about access controls Deploy in your region Select a region for your GPU model deployment and keep every replica in that region. Route requests through a regional endpoint to support your data residency and compliance requirements. Explore regional deployments Protect data and artifacts Securely connect your data with native cloud IAM integrations. With BYOK encryption, exercise independent control over access to model weights and payloads. Read about secure cloud access Constrain network exposure Enforce isolation and segregation through fine-grained network policies. Control how workloads connect to keep production traffic aligned with your security guidelines. Explore network security Simplify the security review Streamline your security review with SOC 2 Type II attestation, HIPAA support with a BAA, and supporting documentation in the Baseten Trust Center. Visit the trust center Secure production Restrict who can change production, keep experimentation separate, and version, promote, and roll back deployments with supported workflows. Read the docs Networking & deployment Scale fast. In our cloud, or in yours. Baseten Cloud Fully managed AWS GCP 30+ Providers 50+ Regions Baseten operates the infrastructure on its multi-cloud capacity pool. Traffic to your endpoints is encrypted in transit. The fastest path to production with no infrastructure to run, encryption in transit and ZDR by default. 30+ Cloud providers 50+ Regions Scaling and Performance Scale with demand Configure autoscaling to match your workload, and scale to zero when a model has no traffic. Baseten’s global compute fleet supports rapid scaling without capacity planning. Read the docs Data Security Protect inference data Inference traffic routes directly to your workload plane, and Baseten does not store synchronous inference inputs or outputs. For asynchronous requests, inputs are stored until the request runs. Read the docs Compliance and trust resources Security that scales with you. Visit the Trust Center SOC 2 Type II SOC 3 HIPAA GDPR PCI DSS CCPA Related resources News Securing the open frontier with NVIDIA OpenShell and Blaxel sandboxes Nicolas Lecomte News Project Beacon: Bringing safety signals to open models at scale Sai Maddali Infrastructure How we built RBAC that scales for the enterprise Matt Howard, Samiksha Pal, Rachel Rapp AI engineering Private, secure DeepSeek-R1 in production in US & EU data centers Yineng Zhang, Amir Haghighat, Philip Kiely See all posts FAQ Frequently asked questions about security on Baseten Baseten provides zero data retention for model inputs and outputs on synchronous inference, across Model APIs and Dedicated Inference. Async inference inputs are temporarily stored until processing completes, for up to 72 hours, then deleted; outputs are not stored. Operational metadata, such as latency and request size, is retained separately from inference content. Customer content, such as model inputs, outputs, and weights, is your data. Baseten does not use customer content to train or fine-tune models. No. Your prompts and outputs aren't sent to the model developer. When you run a model on Baseten, including an open-weight model, inference is served on Baseten infrastructure. Production data stored on Baseten-managed volumes is encrypted at rest. Customer content sent to Model APIs or Dedicated Inference is encrypted in transit. Zero data retention applies to model inputs and outputs—not every operational record. Baseten retains inference metadata, such as response times, request sizes, and request volume, to support platform operations. Yes. Baseten supports SSO and role-based access controls to help govern access to production AI systems. Teams can centralize authentication and manage permissions for the people operating their deployments. Baseten offers private connectivity and deployment options for workloads that require tighter network boundaries. Self-hosted inference runs the workload plane inside your VPC, with requests to your own domain routed directly to it while Baseten operates the control plane. Our engineers can help scope the network architecture and connectivity options for your environment. Yes. Dedicated deployments can be configured for regional requirements, including US or EU deployment. Baseten-managed compliance policies can restrict the regions where inference workloads run. Model API availability and residency commitments depend on the endpoint and agreement, so discuss your requirements with our team before deploying. Baseten uses encryption, access controls, and workload isolation to protect model artifacts and production deployments. Model weights can be loaded from sources such as Hugging Face, GCS, or S3; weight caching is separate from inference input/output retention, and deleting a model automatically permanently deletes any cached weights. Security protects the systems AI runs on: data, identities, networks, and deployments. Safety addresses how models and agents behave, including risky outputs, prompt injection, and actions outside policy. Baseten combines a secure serving foundation with work on model-behavior monitoring, agent-runtime controls, and open safety research. These layers complement one another; no single control guarantees safe behavior. Baseten and Goodfire have announced a partnership to bring activation-based safety monitoring into inference for selected open models. The productized offering is in development, not generally available. The goal is to give applications signals about risky model behavior that they can use according to customer-defined policy. Contact our team to discuss your use case and current availability. Baseten supports running NVIDIA OpenShell inside its sandboxes through a template. OpenShell applies policy around credentials, file access, and outbound networking outside the agent’s own code. The Carbon sandbox infrastructure described in our launch is in private preview. Talk to our team about the runtime controls and availability for your workload. Visit the Baseten Trust Center to view public materials and request access to security documentation, including our SOC 2 report, penetration-test report, and data-retention policy. Access to restricted documents requires approval and an NDA. Our team can also help with security questionnaires, architecture reviews, and BAA or DPA requests. Ready to bring AI to production securely? Talk through your security review with our team, or get a live walkthrough of the controls on this page. Talk to securityVisit the trust center