Security Audit

fitbit-analytics

github.com/openclaw/skills

AI SkillCommit 13146e6a3d46

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

fitbit-analytics received a trust score of 79/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.

SkillShield's automated analysis identified 2 findings: 0 critical, 1 high, 1 medium, and 0 low severity. Key findings include Suspicious import: urllib.request, Skill modifies shared system secrets file.

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

Manifest Analysis

100%

Static Code Analysis

93%

Dependency Graph

100%

LLM Behavioral Safety

85%

Behavioral Risk Signals

Network Access

1 finding

Filesystem Write

1 finding

Excessive Permissions

2 findings

Security Findings2

Severity	Finding	Layer	Location
HIGH	Skill modifies shared system secrets file The `_save_tokens` function in `scripts/fitbit_api.py` directly reads and modifies `~/.config/systemd/user/secrets.conf`. This file is typically used by `systemd --user` services and may contain sensitive credentials for other applications. A skill should ideally manage its own dedicated secrets file or rely solely on environment variables, rather than modifying a potentially shared system configuration file. While file permissions are correctly set to `0o600` (owner read/write only), modifying a file that might be used by other services introduces unnecessary risk of data corruption or unintended side effects for other system components. Store Fitbit tokens in a dedicated skill-specific secrets file (e.g., `~/.fitbit-analytics/tokens.conf`) instead of modifying `~/.config/systemd/user/secrets.conf`. Alternatively, rely solely on environment variables and instruct the user to manage `secrets.conf` manually or via `systemd` tools.	LLM	scripts/fitbit_api.py:200
MEDIUM	Suspicious import: urllib.request Import of 'urllib.request' 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/kesslerio/fitbit-analytics/scripts/fitbit_api.py:18

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