A secure, self-destructing message service using HashiCorp Vault for temporary secret storage.
sup3rS3cretMes5age is a secure web service for sharing confidential information that automatically deletes itself after being accessed once. It solves the problem of securely transmitting sensitive data by storing messages in HashiCorp Vault with one-time tokens and configurable expiration times, ensuring no permanent record remains.
Developers, security teams, and organizations needing a simple, self-hostable solution for ephemeral secret sharing, such as sharing passwords, API keys, or confidential documents internally or with external parties.
Developers choose sup3rS3cretMes5age for its strong security foundation using HashiCorp Vault, ease of deployment with Docker and Kubernetes, and lightweight, privacy-focused design with no external dependencies or tracking.
Simple to use, simple to deploy, one time self destruct messaging service, with hashicorp vault as a backend
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Leverages HashiCorp Vault's cubbyhole backend with one-time tokens for tamper-proof storage, ensuring messages are securely handled and automatically deleted upon retrieval.
The frontend uses only 8.9KB of self-hosted JavaScript with no external CDNs or tracking, prioritizing performance and privacy as highlighted in the README.
Provides Docker images, Kubernetes Helm charts, and AWS deployment guides, making it straightforward to deploy in various environments with minimal setup.
Includes built-in Let's Encrypt integration for automatic TLS certificates, reducing the hassle of manual SSL configuration in production.
Requires setting up and maintaining a production HashiCorp Vault server, which adds operational overhead and may be daunting for teams without existing Vault expertise.
The rate limiting is hardcoded at 10 requests per second and isn't configurable via environment variables, limiting flexibility for high-traffic deployments without code changes.
File uploads are capped at 50MB with base64 encoding, which may be insufficient for sharing larger media files or datasets, as admitted in the features list.