Prompt injection attacks slip past many AI apps, letting users hijack LLMs with phrases like “ignore all previous instructions.” Matt Matthews, founder of PromptLock, spent months building a tool that spots and sanitizes such tricks before data reaches the model. The result is a single‑line API call that flags or redacts malicious input.

Regex filters fail when attackers encode or rephrase commands, and custom classifiers add maintenance overhead. PromptLock uses a dedicated DeBERTa‑v3 model trained on thousands of real injection attempts, catching obfuscated patterns that simple rules miss. It also performs entity recognition, masking SSNs or credit cards before the LLM sees them.

Compliance turns the problem into a regulatory risk. Under HIPAA, leaking PHI via a prompt injection can trigger fines; PCI‑DSS and GDPR impose similar duties on payment and personal data. PromptLock’s dashboard logs every detection, giving auditors a clear paper trail of how sensitive information was handled.

Integrating PromptLock is straightforward: a POST request plugs into any stack, and community nodes exist for n8n, Retool, and Bubble. The free tier offers 3,000 prompts per month, while paid plans add analytics and audit logs. For regulated industries, this layer can prevent costly breaches and satisfy compliance teams.