Security has emerged as the most critical factor in selecting enterprise AI gateway security infrastructure. This guide evaluates leading platforms across guardrails, access control, compliance, and data governance.
Security considerations are now the primary driver behind AI infrastructure decisions at the executive level. A 2025 industry analysis highlights that security and compliance remain the biggest barriers to deploying AI agents across global enterprises. Since every LLM request may include personally identifiable information, internal system context, or regulated financial data, the gateway layer becomes the enforcement point that determines whether an AI deployment is secure and compliant.
This guide reviews leading enterprise AI gateways based on the security capabilities that matter most: content guardrails, access control, secrets management, audit logging, and deployment isolation. For organizations operating in cybersecurity, financial services, healthcare, or other regulated sectors, these capabilities are essential.
Key Takeaways
- Security is now the top criterion for choosing enterprise AI gateway infrastructure, driven by concerns over compliance and data protection.
- Key security features for an AI gateway include content guardrails, access control, secrets management, audit logging, and deployment isolation.
- Bifrost is an open-source AI gateway designed for security, integrating various safeguards to ensure safe and compliant AI deployments.
- Other options like Kong, Cloudflare, and AWS Bedrock offer some security features but come with limitations in flexibility and scope.
- Bifrost provides a robust security stack and a 14-day trial for organizations to assess its effectiveness in securing AI infrastructure.
Table of contents
What Security Features an Enterprise AI Gateway Must Have
An enterprise-grade AI gateway must address five core security dimensions:
- Content guardrails: Real-time validation of inputs and outputs to detect harmful content, prompt injection attempts, and PII leakage before data reaches or exits LLM providers
- Access control and governance: Virtual keys, RBAC, SAML-based SSO, and per-consumer rate limits and budget enforcement at the infrastructure level
- Secrets management: Native integration with enterprise vault systems to ensure API keys are never exposed in configuration files or logs
- Audit logging: Immutable, compliance-ready records of all requests, responses, guardrail decisions, and access events
- Deployment isolation: In-VPC or on-premises deployment models that keep sensitive data within organizational boundaries
Gateways that satisfy all five criteria are suitable for production use in regulated environments. Partial coverage introduces gaps that require additional engineering effort or increase operational risk.
Bifrost: Comprehensive Security Built Into the Gateway Layer
Bifrost, the open-source AI gateway from Maxim AI, is designed with enterprise security as a foundational principle. Security features are built directly into the platform rather than added through external integrations.
Guardrails
Bifrost’s enterprise guardrails enforce inline content validation for both requests and responses. The platform integrates with AWS Bedrock Guardrails, Azure Content Safety, Patronus AI, and GraySwan Cygnal, enabling layered protection across multiple providers.
A CEL-based rule engine allows administrators to define policies using conditions such as message role, model type, content length, and keyword patterns. Guardrail decisions include metadata such as violation type, severity, action taken, and latency, all of which are logged and available for analysis. Input guardrails prevent sensitive data from reaching external providers, while output guardrails filter unsafe responses before they reach end users.
Governance and Access Control
Bifrost’s governance architecture uses virtual keys as the primary unit of control. Each key defines provider permissions, model allowlists, rate limits, budget caps, and MCP tool access.
The platform integrates with SAML-based SSO and OpenID Connect providers such as Okta, Zitadel and Entra (Azure AD), ensuring that enterprise identity policies extend to gateway access. Role-based access control supports custom roles for fine-grained permission management. MCP tool filtering at the virtual key level restricts agent capabilities to approved tools, reducing exposure in case of credential compromise.
Vault Support and Secrets Management
Bifrost’s vault integration connects with HashiCorp Vault, AWS Secrets Manager, Google Secret Manager, and Azure Key Vault. API keys are retrieved dynamically at runtime and rotated without downtime, eliminating the risk of credential exposure in static configurations.
Audit Logs
Audit logs capture all user activity, model interactions, token usage, and guardrail events in immutable records. The logging framework is aligned with SOC 2 Type II, GDPR, HIPAA, and ISO 27001 requirements, allowing compliance teams to generate complete audit trails without additional infrastructure.
Logs can be exported to external systems through Bifrost’s log export capabilities, supporting integration with data lakes and enterprise storage platforms.
In-VPC, Air-gapped and On-Premises Deployment
Bifrost supports secure deployment through its enterprise deployment model, enabling execution within private cloud environments on AWS, GCP, Azure, or self-hosted infrastructure. This ensures that sensitive data remains within organizational boundaries.
For industries with strict security requirements, Bifrost’s cybersecurity industry page outlines additional controls tailored for high-security environments.
Despite its security depth, performance remains efficient. Benchmarks at 5,000 requests per second show an added latency of only 11 microseconds per request.
Kong AI Gateway
Kong extends its API management platform to support AI workloads through plugin-based capabilities. Organizations already using Kong benefit from consolidating API and AI traffic governance within a single control plane.
Security features include OAuth 2.0, JWT, mTLS, and RBAC, along with integration into enterprise identity providers. Version 3.12 introduced MCP-specific metrics and centralized policy enforcement.
However, protection against AI-specific threats such as prompt injection, PII leakage, and unsafe content requires custom plugins or third-party integrations. Pricing complexity is also a consideration at scale.
Cloudflare AI Gateway
Cloudflare applies guardrails and access controls at the edge, leveraging its global network of points of presence to maintain low latency. Integration with Cloudflare Access and DLP tools enables zero-trust enforcement across web, API, and AI traffic.
This model is effective for geographic access control, bot mitigation, and DDoS protection. However, it offers limited flexibility for runtime customization, including guardrail provider selection, vault integration, and MCP governance. The lack of in-VPC deployment makes it unsuitable for environments with strict data residency requirements.
AWS Bedrock Guardrails
AWS Bedrock Guardrails provides managed content filtering, PII detection, and contextual validation for workloads running on AWS. It integrates with CloudWatch and Security Hub for logging and monitoring, and benefits from unified AWS billing.
The limitation is its scope. Guardrails apply only to models hosted within AWS Bedrock. Organizations using multiple providers cannot enforce consistent policies across all traffic using Bedrock alone.
ServiceNow AI Gateway
ServiceNow’s AI Gateway focuses on governance within its ecosystem. It provides centralized management of MCP servers, runtime policy enforcement, and integration with the AI Control Tower.
This approach works well for organizations building AI workflows entirely within ServiceNow. However, it lacks the flexibility required for multi-provider environments, including cross-platform guardrails, failover routing, and broader LLM support.
Conclusion
Bifrost offers a comprehensive enterprise AI gateway security stack, including multi-provider guardrails, vault-based secrets management, immutable audit logs, in-VPC deployment, SAML SSO, RBAC, and centralized governance.
Deployment takes less than 30 seconds, with a free 14-day enterprise trial available. To evaluate how Bifrost can secure your AI infrastructure, book a demo with the team.
