Security Audit

tavily-search-pro

github.com/openclaw/skills

AI SkillCommit 13146e6a3d46

CAUTION

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

tavily-search-pro received a trust score of 72/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 3 findings: 0 critical, 1 high, 2 medium, and 0 low severity. Key findings include Dangerous tool allowed: exec, Suspicious import: urllib.request, Unpinned Python dependency.

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

78%

Dependency Graph

100%

LLM Behavioral Safety

93%

Behavioral Risk Signals

Network Access

1 finding

Shell Execution

1 finding

Excessive Permissions

1 finding

Security Findings3

Severity	Finding	Layer	Location
HIGH	Dangerous tool allowed: exec The skill allows the 'exec' tool without constraints. This grants arbitrary command execution. Remove unconstrained shell/exec tools from allowed-tools, or add specific command constraints.	Static	skills/shaharsha/tavily-search-pro/SKILL.md:1
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/shaharsha/tavily-search-pro/lib/tavily_search.py:24
MEDIUM	Unpinned Python dependency The `install.sh` script installs the `tavily-python` package without specifying a version. This can lead to supply chain attacks if a malicious or vulnerable version of the package is published in the future. It is best practice to pin dependencies to a specific version or at least a major version range. Pin the `tavily-python` dependency to a specific version (e.g., `tavily-python==X.Y.Z`) or a compatible version range (e.g., `tavily-python~=X.Y`) in the `install.sh` script.	LLM	install.sh:9

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