| Version | Supported |
|---|---|
| 0.1.x | ✅ Current release |
Please do NOT open a public GitHub issue for security vulnerabilities.
Instead, report vulnerabilities privately via one of these channels:
-
GitHub Security Advisory (preferred):
- Go to github.com/rememhq/remem/security/advisories/new
- Fill out the advisory form with as much detail as possible
-
Email:
- Send details to the maintainer via GitHub's private messaging
- Description of the vulnerability
- Steps to reproduce
- Affected versions
- Potential impact
- Suggested fix (if any)
| Action | Timeline |
|---|---|
| Acknowledge receipt | 48 hours |
| Initial assessment | 5 business days |
| Patch development | 14 business days |
| Public disclosure (coordinated) | After patch release |
remem requires API keys for cloud LLM providers (Anthropic, OpenAI). These are sensitive credentials:
- Never commit API keys to version control
- Use environment variables (
ANTHROPIC_API_KEY,OPENAI_API_KEY) - The REST API supports bearer token auth via
REMEM_API_KEY - In production, always set
REMEM_API_KEYto restrict access
- Memory data is stored locally in SQLite databases
- Vector indices are stored as JSON files on disk
- No data is transmitted except to configured LLM providers
- All LLM API calls use HTTPS/TLS
- Dependencies are monitored via GitHub Dependabot
cargo auditis run in CI to check for known vulnerabilities- The
rusqlitecrate uses a bundled SQLite build to avoid system library issues
The following are in scope for security reports:
- Authentication bypass in the REST API
- Memory data leakage between projects/sessions
- Injection attacks via memory content
- Dependency vulnerabilities with exploitable impact
- Insecure default configurations
The following are out of scope:
- Denial of service via large memory stores (expected behavior)
- LLM prompt injection via stored memory content (inherent to LLM usage)
- Vulnerabilities in upstream LLM provider APIs