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    ⚠️ Dangerous Command Linter

    ⚠️ Dangerous Command Linter

    by JustHandled Labs

    Flag the destructive operations in a shell command or script before anyone runs it. Catches recursive force deletes, force pushes and history rewrites, database drops and truncates, disk-wipe commands (mkfs, dd to a device), permission blowouts (chmod 777), remote content piped into a shell, broad wildcard deletes, and prod-targeting or disabled-safety flags. Each finding comes with a severity and a safer alternative.

    Updated Jun 2026
    Security scanned
    Cursor

    $12

    · or 60 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Audit third-party install scripts before running them locally
    • Identify recursive delete commands that lack specific path targets
    • terminal, file_read, network automation included
    • Ready for Cursor
    • Instant install

    Sample input

    Is it safe to run this? curl -sSL https://install.example.com | sudo bash

    Sample output

    Findings:

    [High] Pipe-to-Shell: Remote content is piped directly to sudo bash.

    • Evidence: curl ... | sudo bash
    • Risk: Unverified remote execution.
    • Alternative: Download script, inspect manually, then run: curl -O [URL] && less [file]

    Scope:

    1 command string.

    About This Skill

    Safety First for Shell Operations

    The Dangerous Command Linter is a specialized security tool designed for developers and DevOps engineers who want an extra layer of protection before executing shell commands or scripts. It identifies destructive, irreversible, or high-risk operations that could lead to data loss or system instability.

    What it does

    This skill performs a heuristic analysis on shell scripts (.sh, .bash, .zsh, .ps1) and raw CLI strings. It scans for patterns including recursive deletions, force pushes, database drops, permission overrides (chmod 777), and the "curl | sh" anti-pattern. Unlike a standard LLM prompt, it utilizes a dedicated Python scanner and a curated JSON database of dangerous patterns to ensure consistent, rule-based detection.

    Supported Tools & Frameworks

    • Bash, Zsh, and PowerShell scripts
    • Git, Docker, and Cloud CLI commands
    • Standard Linux/Unix system utilities (rm, chmod, chown)
    • Database CLI tools

    Why use this skill?

    While an AI can "guess" if a command is bad, this skill follows a structured audit workflow. It provides a formal report categorizing findings by severity, identifies the exact line of concern, and suggests safe alternatives or remediation snippets. It acts as a pre-execution linting layer for your terminal workflow, reducing the risk of "fat-finger" errors in production environments.

    Use Cases

    • Audit third-party install scripts before running them locally
    • Identify recursive delete commands that lack specific path targets
    • Flag 'force' flags in Git and Cloud CLI commands to prevent data loss
    • Scan PowerShell scripts for permission 'blowouts' and security risks

    Reviews

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell
    Read Files
    Network Access

    Allowed Hosts

    example.com

    File Scopes

    dangerous-command-linter/**
    **/*.sh
    **/*.bash
    **/*.zsh
    **/*.ps1
    --command "<text>"
    --stdin

    Read-only. It never runs the command it inspects. The dangerous-pattern set loads from an editable references/dangerous-patterns.json, so you can add patterns without touching code. Reads no environment variables.

    Tags

    devops
    security
    shell-scripting
    bash
    automation

    Works with any agent that can run a local Python script (Claude Code, Cursor, Codex CLI, and other SKILL.md-compatible agents). Standard library only, no install step. It inspects the command text and never executes it. No network.

    Creator

    JustHandled Labs

    JustHandled Labs builds focused agent skills for the work nobody wants to do by hand. Each one is a single repeatable job done well: catching the security and data mistakes that quietly ship, keeping docs and tests honest, gating the commands an agent is about to run, sharpening writing, and handling the founder chores around launches, outreach, and brand setup. Not generic AI productivity. Specific workflows that are easy to run, review, and repeat. Maintained by H.J. Westerfield, with a background in communications, editing, project coordination, customer support, and practical AI systems. Tools for people who want useful automation without theatrical complexity.

    Frequently Asked Questions

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