Security●●●Banger
YoloAI: A sandbox and diff/apply workflow your agent can't escape
External enforcement stops agents escaping sandboxes like Claude Code.
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kstenerud
102mo ago
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Secure CLI proxy for AI agents — HCL-defined operation templates with OS keychain secrets, MCP integration, and prompt injection protection
113 starsRust
The only CLI your AI agent will need
by jrandolf·Feb 22, 2026·2 points·0 comments
AI Analysis
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Sandboxes AI agents with keychain secrets and egress allowlists instead of raw shell access.
Strengths
- •Addresses a genuine safety gap: agents today expose creds in env vars and make unsafe network calls.
- •HCL template-driven model lets teams review and control all agent operations before execution.
- •Multi-platform (macOS, Linux, Windows) with MCP server integration for native agent compatibility.
Weaknesses
- •Early adoption risk: agent safety is new; unclear how many teams will adopt template overhead vs. trust models.
- •Limited real-world case studies showing this catches actual breaches or reduces agent-caused incidents.
Category
Target Audience
AI/ML engineers building agentic systems, DevOps teams managing agent infrastructure
Similar To
OpenClaw · Anthropic's tool-use sandbox model · traditional API gateway / policy enforcement patterns
Post Description
I started digging into OpenClaw, then found this: https://clawhub.ai/steipete/trello. They are literally telling people that it's okay to expose credentials, just as long as it's in an env var.
If we’re building with AI, safety has to be a product principle, not an afterthought. AI makes coding more accessible, but it also strips away the guardrails you usually get from experienced mentors and hard-earned production lessons.
So we built Earl: an AI-safe CLI for LLM agents. Instead of giving agents raw shell + network access, Earl enforces template-driven calls, stores secrets in the OS keychain, blocks SSRF/private IP targets, supports egress allowlists, and sandboxes Bash/JS/SQL execution.
It also runs as an MCP server so agents can use those same controls natively.
Get started: https://github.com/brwse/earl?tab=readme-ov-file#quick-start
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