The problem
Traditional honeypots have a fatal flaw: they all look the same. Once an attacker (or AI agent) learns the signature of a particular honeypot, they can avoid every identical deployment worldwide.The solution
On first run, Sundew generates a deployment persona -a coherent identity that shapes every aspect of the honeypot:- Endpoint paths -
/api/v2/transactionsvs/v1/patientsvs/graphql - Response bodies -financial data, healthcare records, SaaS metrics
- HTTP headers -
Server,X-Powered-By, error formats - Timing profiles -simulated latency matching real-world services
- Auth schemes -bearer JWT, API keys, OAuth2, basic auth
- MCP tool names -
query_transactionsvsget_patient_records - Error formats -RFC 7807, simple JSON, HTML, XML
Generation methods
Personas can be generated three ways:- LLM-powered (recommended)
- Pre-built packs
- Custom
Use a local or cloud LLM to generate rich, realistic response templates:Templates are generated at deploy time and cached. Zero LLM latency during operation.
Supported industries
Anti-detection
Sundew’s test suite (test_anti_detection.py) deploys 5 instances with different personas and verifies zero cross-instance correlation across:
- Response body structure and field names
- HTTP header combinations
- Error message formatting
- Endpoint path patterns
- Timing distributions