AI data leak prevention

Every day, employees share sensitive data with AI tools — often without realizing it. PromptWall prevents this data from reaching external providers with real-time detection, masking, and policy enforcement across every AI surface.

The scale of the problem

Research shows 11% of enterprise AI prompts contain sensitive data — customer PII, source code, credentials, and internal documents. In a 1,000-person organization, this means hundreds of potential data leaks every day. Without controls, this data is sent directly to third-party AI providers like OpenAI, Anthropic, and Google.

The problem is compounded by the variety of AI access points: ChatGPT in the browser, Copilot in the editor, API calls from scripts, and a growing ecosystem of AI-powered tools. Each is an unmonitored data channel.

Detection mechanisms

PromptWall uses three complementary detection mechanisms to identify sensitive data in AI prompts:

1. Named entity recognition — NLP models identify PII entities in natural language: names, emails, phone numbers, credit cards, SSNs, and 30+ entity types.
2. Pattern matching — Regex patterns detect credentials, API keys, connection strings, and structured data formats that NER models may miss.
3. Semantic similarity — Document leak detection compares prompts against protected corpora using embedding similarity — catching even paraphrased content.

Prevention vs monitoring

Many tools only log data exposure after the fact. PromptWall prevents leaks by intercepting and masking sensitive content before it leaves your organization. This is the critical difference:

• Monitoring — tells you yesterday that data leaked. The data is already at the provider.
• Prevention — stops the leak in real-time. The data never reaches the provider.

PromptWall provides both: real-time prevention through masking and blocking, plus comprehensive audit trails for monitoring and compliance.