Trust Assessment
bambu-print received a trust score of 43/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.
SkillShield's automated analysis identified 4 findings: 1 critical, 1 high, 2 medium, and 0 low severity. Key findings include Arbitrary command execution, Suspicious import: requests, Dangerous call: subprocess.run().
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.
Last analyzed on February 13, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings4
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| CRITICAL | Arbitrary command execution Python shell execution (os.system, subprocess) Review all shell execution calls. Ensure commands are static (not built from user input), use absolute paths, and are strictly necessary. Prefer library APIs over shell commands. | Manifest | skills/snail3d/clawd/bambu-print/scripts/slice_model.py:77 | |
| HIGH | Dangerous call: subprocess.run() Call to 'subprocess.run()' detected in function 'slice_model'. This can execute arbitrary code. Avoid using dangerous functions like exec/eval/os.system. Use safer alternatives. | Static | skills/snail3d/clawd/bambu-print/scripts/slice_model.py:77 | |
| MEDIUM | Suspicious import: requests Import of 'requests' detected. This module provides network or low-level system access. Verify this import is necessary. Network and system modules in skill code may indicate data exfiltration. | Static | skills/snail3d/clawd/bambu-print/scripts/search_models.py:8 | |
| MEDIUM | Potential Command Injection via External CLI Arguments The `slice_model.py` script constructs and executes a command for the `bambu-studio` CLI tool using `subprocess.run` with user-controlled arguments. While `subprocess.run` with a list of arguments (default `shell=False`) mitigates direct shell injection, it still passes untrusted user input (file paths for input, output, printer, process, and filament profiles) directly to the external `bambu-studio` executable. A malicious user could craft these paths to exploit argument parsing vulnerabilities in `bambu-studio`, potentially leading to arbitrary file reads/writes, or unintended execution if `bambu-studio` itself is not robustly handling malformed or specially crafted arguments. For example, a crafted `output_file` could attempt to write to sensitive system locations, or a malicious profile path could cause `bambu-studio` to load an unintended configuration. Implement strict validation and sanitization for all user-provided file paths (`input_file`, `output_file`, `printer_profile`, `process_profile`, `filament_profile`) before passing them to the `bambu-studio` CLI. Ensure paths are normalized, resolved to absolute paths, and confined to an allowed working directory or a temporary directory. Avoid allowing arbitrary paths that could point to sensitive system locations or lead to path traversal. Consider using a whitelist of allowed file extensions and checking file contents if applicable. | LLM | scripts/slice_model.py:59 |
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