ClawHub
Back to skill

Security audit

Auto Video Cut

Security checks for vulnerabilities and agentic risk

Overview

This skill appears to be a real local video-trimming tool, but batch mode can recursively delete a user-specified work directory without containment checks.

Review before installing. Use only a dedicated empty work directory, do not point the third batch argument at your home, project, downloads, or any directory containing files you care about, and treat generated reports/work files as sensitive because they may contain transcripts. Pin and review the Whisper dependency if reproducible installs matter.

SkillSpector

Vulnerability Patterns
  • Supply ChainUnpinned Dependencies, External Script Fetching, Obfuscated Code
  • Behavioral ASTexec() Call, eval() Call, Dynamic Import
  • Prompt InjectionInstruction Override, Hidden Instructions, Exfiltration Commands
  • Data ExfiltrationExternal Transmission, Env Variable Harvesting, File System Enumeration
  • Privilege EscalationExcessive Permissions, Sudo/Root Execution, Credential Access
Findings (3)

subprocess module call

Medium
Category
Dangerous Code Execution
Content
"-c:a", "aac", "-b:a", CONFIG['audio_bitrate'],
        output_path
    ]
    ok = subprocess.run(cmd, capture_output=True, text=True).returncode == 0
    if os.path.exists(list_file):
        os.remove(list_file)
    return ok
Confidence
89% confidence
Finding
The concatenation flow writes unescaped file paths into an ffmpeg concat list using the syntax file '...'. If a clip path contains a single quote, newline, or specially crafted content, ffmpeg may misparse the list and ingest unintended files or directives, creating a file-format injection issue at the tool boundary.

Missing User Warnings

Medium
Confidence
94% confidence
Finding
Batch mode unconditionally deletes generated clip files and recursively removes the working directory. If output_dir or work_dir are user-supplied or misconfigured, this can destroy data unexpectedly, and there are no guardrails such as confirmation, path validation, or containment checks.

Unpinned Dependencies

Low
Category
Supply Chain
Content
openai-whisper
Confidence
97% confidence
Finding
The dependency is unpinned, so installs may pull different upstream versions over time. This creates supply-chain and reproducibility risk: a future release could introduce a vulnerability, breaking change, or malicious code and the skill would consume it automatically.

Static analysis

No suspicious patterns detected.