LLM API Security
Secure every LLM API call
before it reaches the model.
FirewaLLM acts as a security proxy for your LLM API integrations. Inspect, filter, and control every request and response flowing between your application and providers like OpenAI, Anthropic, and Mistral — with zero code changes.
THE CHALLENGE
LLM APIs are powerful
and dangerously exposed.
Every API key you deploy is an attack surface. Without a dedicated security layer, your LLM integrations are vulnerable to prompt injection, token abuse, and sensitive data exfiltration through model responses. Traditional API gateways were not built for the unique threats of generative AI traffic.
Prompt Injection via API
Attackers craft malicious payloads that bypass your application logic and manipulate the underlying model. A single unfiltered API call can override system instructions, extract training data, or force the model to execute unintended actions across your entire pipeline.
Token Abuse & Cost Explosion
Without per-user and per-key controls, a compromised or misused API key can generate thousands of expensive completions in minutes. Automated scripts and bots target exposed endpoints, burning through token budgets and inflating costs before alerts trigger.
Sensitive Data in Responses
LLMs can inadvertently include PII, credentials, internal system details, or proprietary information in their outputs. Without response-level filtering, this data reaches end users or downstream systems, creating compliance violations and data breach risks.
THE SOLUTION
A purpose-built firewall
for LLM API traffic.
FirewaLLM intercepts every request and response at the API boundary. Our analysis engine evaluates prompts for injection patterns, enforces token budgets, and scans model outputs for sensitive data — all in real time with sub-10ms overhead.
Prompt Injection Detection
Every inbound prompt is analyzed for injection patterns, jailbreak attempts, and obfuscated payloads before it reaches the LLM provider. Malicious requests are blocked instantly with detailed threat classification.
Intelligent Rate Limiting
Define granular rate limits per user, API key, or endpoint. Set token-level budgets with automatic throttling and alerting so you control costs and prevent abuse without impacting legitimate traffic.
Response Content Filtering
Scan every model response for PII, credentials, internal URLs, and proprietary data before delivery. Configurable policies let you redact, block, or flag sensitive content in real time.
API Key Governance
Centralize API key management across all LLM providers. Rotate keys automatically, enforce scoped permissions, and audit which keys are used for which workloads with full traceability.
Real-Time Traffic Analytics
Monitor request volume, token consumption, error rates, and threat scores across every endpoint in a unified dashboard. Detect anomalies and usage spikes before they become incidents.
Provider-Agnostic Policies
Write security policies once and apply them across OpenAI, Anthropic, Mistral, Azure, and any OpenAI-compatible endpoint. Switch providers without rewriting your security rules.
WHY FIREWALLM
Built for real-world AI security.
Block prompt injection attacks before they reach the LLM provider
Enforce per-user token budgets to prevent unexpected cost spikes
Filter sensitive data from model responses in real time
Maintain full audit logs of every API request and response
Deploy as a proxy layer with zero application code changes
Support for every major LLM provider and custom endpoints
Sub-10ms analysis latency for production-grade performance
Generate compliance reports for SOC 2 and ISO 27001 audits
LLM API Security FAQ
How does FirewaLLM protect LLM API endpoints from prompt injection attacks?+
FirewaLLM inspects every inbound request before it reaches your LLM provider. Our analysis engine detects known injection patterns, obfuscated payloads, and novel attack vectors using a combination of heuristic rules and classifier models. Malicious prompts are blocked or sanitized in real time, so your OpenAI, Anthropic, or Mistral integration never processes a harmful request.
Can FirewaLLM enforce rate limiting and quota management across multiple LLM providers?+
Yes. FirewaLLM sits as a proxy layer between your application and any number of LLM APIs. You can define per-user, per-key, or per-endpoint rate limits, set monthly token budgets, and receive alerts when consumption approaches your thresholds. This prevents both abuse and unexpected cost spikes regardless of which provider you use.
Does FirewaLLM add latency to LLM API calls?+
FirewaLLM is engineered for minimal overhead. Request analysis typically completes in under 10 milliseconds at the edge, which is negligible compared to the hundreds of milliseconds an LLM inference call takes. For latency-critical paths you can also run FirewaLLM in async audit mode, where requests are forwarded immediately and analyzed in parallel.
What LLM providers and APIs are compatible with FirewaLLM?+
FirewaLLM works with any HTTP-based LLM API. Out of the box we support OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, Mistral, Cohere, and any OpenAI-compatible endpoint including self-hosted models via vLLM or Ollama. Custom provider adapters can be configured in minutes.
How does response filtering work for LLM API outputs?+
After the LLM generates a response, FirewaLLM scans the output for sensitive data patterns such as PII, credentials, internal URLs, or proprietary information before it is returned to the client. You configure policies that redact, block, or flag responses that contain disallowed content, ensuring your API never leaks data it should not.
Can I use FirewaLLM to audit and log all LLM API traffic for compliance?+
Absolutely. Every request and response passing through FirewaLLM is logged with full metadata including timestamps, user identifiers, token counts, policy decisions, and threat scores. Logs can be exported to your SIEM, stored in your own infrastructure for retention policies, and used to generate compliance reports for SOC 2, ISO 27001, or internal security audits.
Secure your LLM APIs
starting today.
Deploy FirewaLLM as a security proxy in front of your LLM integrations. Full protection against prompt injection, data leakage, and abuse — with zero latency overhead and zero code changes.