AI tools will fail. Your junior devs will make mistakes. Caro provides deterministic safety validation that catches what AI hallucinations and permission flags miss— without you having to review every command.
Real incidents from AI coding assistants
Deleted project files when asked to "clean up the repo"
Executed rm -rf in wrong directory after misunderstanding context
Generated curl | bash command that downloaded malicious script
Suggested chmod 777 to "fix permissions" on /etc
Pattern-based validation doesn't depend on AI judgement.
When the AI marks rm -rf / as "Safe", Caro's deterministic
patterns still catch it.
What you hire Caro to do for your team
Deploy org-wide safety patterns without micromanaging individual engineers.
Trigger: New team member or after incident
Catch when AI tools suggest dangerous commands before they can execute.
Trigger: Team using AI coding assistants
Give AI agents safe shell command capabilities with guardrails.
Trigger: Deploying AI agents that need shell access
Set it up once, protect the whole team
Define organization-specific dangerous patterns. Block commands that are risky in YOUR environment.
Block deploys to prod on Fridays: deploy.*production.*--no-backup Log every command generated and every pattern matched. Full visibility for compliance.
Export: caro logs --json > audit.json Set team-wide safety levels. Strict mode blocks, moderate warns, permissive logs.
Config: safety_level = "strict" Pre-approve specific patterns or block them entirely. No runtime decisions needed.
allowlist = ["kubectl get", "docker ps"] [safety] level = "strict" # strict | moderate | permissive # Custom patterns for your organization [[safety.custom_patterns]] pattern = "deploy.*production.*--force" risk_level = "Critical" description = "Force deploy to production" [[safety.custom_patterns]] pattern = "kubectl delete namespace production" risk_level = "Critical" description = "Delete production namespace" # Allowlist safe operations [safety.allowlist] patterns = [ "kubectl get", "docker ps", "terraform plan" ] [logging] enabled = true path = "/var/log/caro/commands.log" format = "json" # For SIEM integration
Flags fail. Patterns don't.
If your AI tool is 99.9% accurate and your team runs 1,000 commands/day:
Caro provides a deterministic layer that catches the 0.1%. 52 patterns × 0 hallucination = 0 bypasses.
Give AI agents safe shell capabilities
Let Claude generate shell commands through Caro's MCP server. Every command validated before execution.
Add Caro as a safety layer for Claude Code. Catch hallucinations before they execute.
Any AI agent using MCP can route shell commands through Caro for validation.
From individual to enterprise
Each engineer installs Caro locally
Team-wide config file in repo
Centralized management and logging
No account. No API key. No data collection. Just safer shell commands.
bash <(curl --proto '=https' --tlsv1.2 -sSfL https://setup.caro.sh) Then run:
caro "find files modified in the last 7 days" Prefer to build from source? See all installation options →