boostsecurityio/bagel — Bagel, a CLI that inventories security-relevant metadata on developer workstations

Description and use

**Brief Summary (2‑3 sentences)**
Bagel is an open‑source Go‑based CLI that scans developer workstations and collects security‑relevant metadata (e.g., language runtimes, installed SDKs, API keys, and other implementation signals). By exposing this data in a structured form, it enables teams to quickly prototype AI‑driven security features such as RAG (retrieval‑augmented generation) or autonomous agents without building a data‑collection layer from scratch.

**Value**

• **Accelerates AI security projects** – Bagel supplies the “observability” layer that AI models need to understand the tooling and configurations present on a workstation, turning raw environment data into ready‑to‑use prompts or feature flags.
• **Reduces engineering overhead** – Instead of writing custom scripts to inventory runtimes, dependencies, and credentials, teams can invoke a single CLI and obtain a consistent, machine‑readable report.
• **Supports a wide range of use cases** – From prototype “what‑if” security checks to full‑scale RAG pipelines that answer developer questions based on local context, Bagel’s output can be fed directly into LLM prompts, policy engines, or CI/CD gates.

**Practical Adoption Path**

1. **Pilot Installation** – Add Bagel to a small set of developer machines (or CI agents) via its pre‑built binary or Docker image.
2. **Data Integration** – Pipe the JSON/YAML output into your existing security telemetry platform or into a prompt‑construction service for LLMs.
3. **Feature Development** – Build prototype AI workflows (e.g., “show me all outdated dependencies” or “detect hard‑coded secrets”) using the collected metadata as context.
4. **Scale & Automate** – Embed the CLI in onboarding scripts, CI pipelines, or scheduled jobs to keep the metadata current across the organization.

**Production Readiness**
Bagel scores 65/100 and shows strong OSS health signals: 124 ★, recent commits (last updated 2026‑05‑11), active maintainers, and a Go codebase that is easy to audit and embed. The project’s modest dependency surface, clear CLI contract, and focus on security‑relevant signals make it a solid candidate for a serious pilot. The remaining due‑diligence items are a final review of the license, a security audit of the binary distribution, and confirmation of long‑term maintainer commitment, but no blocking issues have been identified.

Problem

boostsecurityio/bagel helps add AI capability without starting from a blank model stack.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

bagel, a CLI that inventories security-relevant metadata on developer workstations

Source