farfa.tech

Secure Your LLM Applications with Farfa's Real-Time Prompt Application Firewall

Farfa.tech provides a real-time prompt application firewall (PAF) that acts as a critical security layer between your users and your Large Language Models (LLMs). By intercepting and inspecting every prompt, Farfa ensures that only safe prompts reach your model, preventing malicious actors from hijacking your AI systems.

The platform is built for production-ready security with high performance and developer-friendly features.

How It Works: The Multi-Stage Pipeline

Every prompt passes through a rigorous multi-stage inspection pipeline. A request must survive all filters to reach your LLM, one red flag anywhere stops it cold.

• Vectorize: Embed the prompt into semantic space for deeper analysis.
• Static Analysis: Perform pattern and signature matching against known attack vectors.
• LLM Analysis: Utilize neural classifier scores to detect jailbreak intent.
• More Filters: Additional stages in the pipeline ensure comprehensive protection.
• Low Latency: Average request processing time is under 500ms across all stages.
• Safe Prompts Only: Only prompts that pass every filter are forwarded to your model.

Capabilities and Features

Farfa provides everything you need to secure your LLM from day one, designed for fast integration and transparent security.

• Real-Time Threat Blocking: Neutralize malicious prompts before they ever reach your model.
• Quick Integration: Route prompts through PAF in a few lines of code—minutes, not days.
• Low-Latency Filtering: Average request under 500ms, ensuring your users never feel the firewall.
• Staging Friendly: Validate integrations with a test API key (paf_sk_test_) for staging environments without production costs.
• Sandbox Playground: Try attack vectors against your configuration in the security-isolated sandbox playground.
• Team Collaboration & RBAC: Invite your team, engineers,s and developers to manage access at scale with Role-Based Access Control (RBAC).
• Usage-Based Pricing: Pay only for what you use with a flat fee plus usage costs, no hidden costs.

Why Security Matters Now

Prompt injection is not theoretical; it is a real vulnerability that has already been assigned critical CVEs in production tools like GitHub Copilot and Visual Studio.

• CVE-2025-53773: Command Injection in GitHub Copilot.
• CVE-2025-53773: Improper neutralization of special elements used in a command (command injection) in GitHub Copilot and Visual Studio allows an unauthorized attacker to execute code locally.
• Security Audit Exposure: 0% of AI systems assessed in security audits showed exposure to prompt injection vulnerabilities.

Integration Workflow

Integrating Farfa into your application is straightforward. Simply route prompts through the PAF API before forwarding them to your model.

1. Send a POST request to the Farfa API with the user's prompt text.
2. Include your unique API key in the headers.
3. Receive a JSON response containing any detected matches.
4. If the matches array is empty, the prompt is safe to forward to your LLM.