Problem solved

Organizations deploying LLM-based applications face significant security risks from malicious user prompts. These include prompt injection, where attackers manipulate the model to bypass constraints, jailbreak attempts that override safety guidelines, and data leakage that can expose sensitive information. Farfa.tech solves these problems by providing a dedicated firewall that inspects every prompt in real time, applying predefined or custom rules to block harmful inputs before they are processed by the LLM. This reduces the attack surface and ensures that models operate within safe boundaries, protecting both the organization and its users from reputational harm, compliance violations, and data breaches.

Use cases

• Protecting customer-facing chatbots from prompt injection and offensive content generation.
• Preventing jailbreak attempts on internal AI assistants to maintain brand safety and compliance.
• Blocking data exfiltration attempts through crafty prompts that try to extract system instructions or training data.
• Enforcing acceptable use policies in enterprise LLM deployments, such as filtering hate speech or personal information.
• Monitoring and logging all LLM interactions for security audits and anomaly detection.
• Shielding multi-tenant LLM platforms from cross-user prompt attacks and injection.

Audience

• Developers
• ML Engineers
• Data Scientists
• Enterprise

Pros

• Real-time protection with low latency, minimizing impact on user experience.
• Easy integration via API, compatible with major LLM providers and frameworks.
• Customizable security policies to align with specific use cases and compliance requirements.
• Reduces risk of prompt injection, jailbreaking, and data leakage significantly.
• Provides visibility into threat patterns through monitoring and logging.

Cons

• Adds an additional latency overhead to each LLM request, which may be noticeable in latency-sensitive applications.
• Potential for false positives, blocking legitimate prompts and requiring ongoing rule tuning.
• Paid service introduces recurring costs, which may be a barrier for small-scale or hobbyist projects.