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Scan prompts locally and redact sensitive data before sending to LLMs.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ai-security-gateway-mcp" yet — see the docs or source repo.
Before sending the following support chat to an LLM, scan for names, phone numbers, emails, ID numbers, and addresses, then mask them and return a safe-to-send version: {{support chat content}}A masked chat transcript where sensitive fields are replaced but the content remains usable for analysis.
Check this application log for sensitive data such as tokens, emails, IPs, user identifiers, and order numbers. Use redaction mode to remove high-risk fields, then return a version suitable for sending to an LLM for troubleshooting: {{log content}}A redacted log with high-risk sensitive data removed while preserving enough context for technical analysis.
I need to send the following analysis request to an LLM. First, scan it locally for customer names, company names, contract numbers, and bank details, then replace them with consistent placeholders using anonymization mode: {{analysis request content}}A fully anonymized request with preserved structure, ready for analysis without exposing customer privacy.
Secure LLM and MCP tool interactions with zero-trust controls and policy enforcement.
Secure MCP servers with policy checks, redaction, access control, and audit logs
Securely lets AI agents access authenticated services without exposing secrets.
Audit MCP configs for exposed access, secrets, models, and compliance AI-BOMs.
Detect prompt injections and jailbreaks to secure LLM applications and workflows.
Scan codebases for LLM usage, AI frameworks, and exposed secrets.