B — Some risk signals Graded October 16, 2026Minor concerns worth a quick check.Based on public adoption and transparency signals as of October 16, 2026. Our opinion, not a code audit or security guarantee.
App connector · Memory & knowledge
screenpipe
YC (S26) | Open Computer History | Continuously record your company computer work, map your workflows, help you find work worth automating, and power your agents' context
Bottom line: Signal-based grade (4/7 points): very widely starred on GitHub, public source code. This reflects adoption and transparency, not a code review.
- Popularity score
- 48/100
- Rank
- #145 of 500
- GitHub stars
- 22k
What it does
Screenpipe continuously records your computer screen and audio to create a searchable history of work activity, then uses that context to help identify automation opportunities and power AI agents with rich workflow understanding. It maps how you actually work rather than relying on manual logging.
Who it’s for
Engineering teams and builders looking to instrument their own work for AI-agent context; companies exploring workflow automation ROI. Likely most useful for organizations comfortable with local screen recording and open-source tooling.
Copy-paste setup
Check these steps against the project’s own instructions before running anything.
Verify against the repo README at https://github.com/screenpipe/screenpipe (opens external site) for the latest install method. Likely involves cloning the repo and running a local daemon; MCP server integration details should be confirmed in official documentation.
Risks
- Credential exposure: Continuous screen recording captures everything typed, including passwords, API keys, and auth tokens unless actively filtered
- Data exfiltration: Recording files could be accessed by malicious actors or inadvertently shared; unclear how data is stored and encrypted at rest
- Prompt injection: If recordings are fed into agent prompts without sanitization, sensitive information could be leaked to LLM APIs
- Supply chain: Young project (YC S26, early stage); limited track record for security audits or responsible disclosure process
- Audio recording compliance: Depending on jurisdiction, recording audio (especially in meetings) may require explicit consent from all participants
How to stay secure
Least-privilege permissions
- Run screenpipe in a dedicated, unprivileged user account with no sudo access or elevated capabilities
- Restrict file system access to a single isolated directory; deny access to
/home,/root, credential managers, and SSH key directories - Disable screen recording during sensitive activities (VPN login, password managers, banking) using application whitelists/blacklists
- Revoke API keys and tokens used by any LLM agent that consumes screenpipe data; rotate credentials weekly
Network isolation
- Deploy screenpipe on an air-gapped machine or behind a restrictive firewall that blocks outbound connections except to explicitly whitelisted LLM endpoints
- Disable cloud sync and telemetry; verify no data leaves the local machine without explicit manual export
- Use a dedicated VPN or proxy to inspect all traffic from screenpipe agents to third-party LLM APIs before sensitive data reaches external services
- Encrypt local recording storage with full-disk encryption (LUKS/BitLocker) and apply per-file encryption for data at rest
Monitoring
- Log all screenpipe process activity (file access, memory dumps, subprocess spawning) to a separate, write-once storage device
- Alert on any attempt to access credential files, SSH keys, or browser caches by screenpipe or child processes
- Audit every prompt sent to external LLM APIs; flag queries containing hostnames, email addresses, or alphanumeric sequences >16 characters
- Track screenpipe version updates and cross-reference against CVE databases and GitHub security advisories weekly
Red flags to watch for
- Screenpipe recording sensitive windows (password managers, banking sites, SSH terminals) without user interaction or bypass mechanisms
- Recordings uploaded to cloud storage or external servers without explicit user configuration or transparent logging
- No clear data retention policy or absence of automatic purging of recordings older than N days
- Unresponsive maintainers or no published security contact/responsible disclosure policy on GitHub or official documentation
Alternatives
- Codeium/Cursor built-in context: IDE-native code history and context without screen recording
- LogRocket or Hotjar: Session replay tools designed with privacy controls and compliance in mind
- ActivityWatch: Open-source time-tracking with local recording; more privacy-focused but less AI-agent integration
- Manual workflow documentation + Claude context window: Lower automation discovery but simpler security model