AI Security Pipeline
That Never Sleeps
Every AI request passes through 14 security checkpoints before reaching the LLM and 14 more on the way back. Authentication, injection detection, content filtering, tool validation, and full audit trail — in under 50ms of overhead.
The 14-Step Security Pipeline
Every AI request is inspected, validated, and secured at each stage. No shortcuts. No bypasses.
Authentication
Step 1JWT + API key verification with tenant isolation
Every request is authenticated via JWT bearer tokens or API keys. Tenant context is extracted and bound to the request lifecycle, enabling Row-Level Security across all downstream operations.
Rate Limiting
Step 2Redis sliding-window rate limiter per tenant/user
Redis-backed sliding window algorithm enforces configurable rate limits per tenant, user, and endpoint. Burst allowances, backoff headers, and 429 responses with retry-after timing.
Request Validation
Step 3Schema validation, payload size limits, encoding checks
Pydantic v2 strict validation ensures every request matches the expected schema. Payload size limits, content-type verification, and Unicode normalization prevent malformed inputs.
Policy Evaluation
Step 4Tenant-specific policies, model allowlists, content rules
Evaluates tenant-specific gateway policies: allowed models, blocked providers, content categories, token budget enforcement, and custom business rules defined by administrators.
Prompt Injection Detection
Step 59 attack techniques detected with heuristic + encoding analysis
Detects direct injection, indirect injection, jailbreak attempts, DAN prompts, role-playing exploits, Unicode tricks, Base64 encoding, RTL override attacks, and homoglyph substitution.
Content Filtering
Step 6PII detection, toxicity screening, topic blocking
ML-based content classification screens for PII (SSN, credit cards, Aadhaar, PAN), toxic language, NSFW content, and tenant-configured blocked topics before reaching the LLM.
Token Budget Enforcement
Step 7Per-tenant, per-model token quotas with cost tracking
Enforces per-tenant and per-model token budgets with real-time cost tracking. Supports daily, weekly, and monthly quotas with configurable hard/soft limits and overage alerts.
Cache Check
Step 8Semantic cache lookup for repeated queries
Redis-backed response cache with configurable TTL. Semantic similarity matching reduces redundant LLM calls, cutting costs and latency for repeated or near-identical prompts.
Provider Routing
Step 9Intelligent routing across 18+ LLM providers
UniversalLLMAdapter routes requests to the optimal provider based on model availability, latency, cost, and failover priority. Supports load balancing and automatic provider fallback.
LLM Execution
Step 10Proxied request with timeout, retry, and circuit breaker
Request is forwarded to the selected LLM provider with configurable timeouts, exponential backoff retry, and circuit breaker protection. Streaming responses are supported end-to-end.
Response Validation
Step 11Output safety checks, hallucination flags, format verification
LLM responses pass through output safety filters: PII leak detection, hallucination risk scoring, format compliance verification, and content policy re-evaluation before delivery.
Tool Call Validation
Step 1238 injection patterns across SSRF, SQLi, path traversal
When LLMs invoke tools, every parameter is scanned against 38 regex-based injection patterns covering SSRF, command injection, path traversal, SQL injection, template injection, and encoded payloads.
Cache Store
Step 13Validated responses stored for future retrieval
Validated responses are stored in the semantic cache with computed embeddings for future similarity matching. Cache eviction follows LRU with configurable per-tenant TTL policies.
Audit Trail
Step 14Full request/response audit with CloudEvents logging
Complete request/response pair logged as CloudEvents v1.0 with tenant context, latency metrics, token usage, cost, policy decisions, and security findings. Immutable audit trail for compliance.
9 Attack Techniques Neutralized
The HeuristicPromptInjectionDetector analyzes every prompt for known attack vectors using pattern matching, encoding detection, and character-level analysis.
Tool Call Validator — 38 Injection Patterns
When LLMs invoke external tools, every parameter is scanned against 38 regex-based patterns covering the most dangerous injection categories. No tool call reaches your infrastructure without validation.
33 Providers Across 5 Categories
The UniversalLLMAdapter provides a single, unified interface to every major LLM provider. One API, any model, anywhere.
US / Western
12 providersChinese / APAC
10 providersCloud Platform
3 providersSelf-Hosted
5 providersCustom
1 providersKill Switch Scope Hierarchy
Instant shutdown at any level of granularity. From killing a single rogue agent to halting all AI operations platform-wide in under 100ms.
Global Kill Switch
Kill all AI operations across entire platform instantly
Provider Kill Switch
Disable a specific LLM provider (e.g., block all OpenAI calls)
Model Kill Switch
Block a specific model version (e.g., quarantine gpt-4-turbo)
Agent Kill Switch
Terminate a single AI agent while others continue operating
Enterprise Security Built In
Not bolted on as an afterthought. Every security control is a first-class citizen in the pipeline architecture.
Redis Rate Limiting
Sliding-window rate limiter backed by Redis. Per-tenant, per-user, and per-endpoint quotas with burst allowances and automatic 429 responses with retry-after headers.
Semantic Caching
Intelligent response cache with semantic similarity matching. Reduces redundant LLM calls by up to 40%, cutting both latency and cost while maintaining response freshness.
Immutable Audit Trail
Every request, response, policy decision, and security finding logged as CloudEvents v1.0. Immutable, tenant-isolated audit trail supporting compliance assessments across multiple frameworks.
Policy Engine
Configurable per-tenant policies governing model access, content rules, token budgets, and provider routing. Version-controlled policy definitions with rollback capability.
Token Budget Management
Real-time token usage tracking with configurable daily, weekly, and monthly quotas. Hard limits prevent overspend; soft limits trigger alerts for proactive cost management.
Circuit Breaker
Automatic circuit breaker protection for every LLM provider. Detects failures, opens circuit to prevent cascade, and auto-recovers with half-open state testing.
Secure Your AI Pipeline
14 security checkpoints. 33 LLM providers. 38 injection patterns. Zero trust by default. Deploy the most comprehensive AI security gateway in under 15 minutes.