Security Audit

Cloudinary Automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 27904475d127

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

Cloudinary Automation received a trust score of 81/100, 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 Arbitrary Webhook URL allows data exfiltration, Unpinned dependency in manifest.

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 20, 2026 (commit 27904475). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis

100%

Static Code Analysis

100%

Dependency Graph

100%

LLM Behavioral Safety

78%

Behavioral Risk Signals

Network Access

1 finding

Security Findings2

Severity	Finding	Layer	Location
HIGH	Arbitrary Webhook URL allows data exfiltration The skill exposes tools (`CLOUDINARY_CREATE_TRIGGER` and the `notification_url` parameter in `CLOUDINARY_CREATE_UPLOAD_PRESET`) that allow specifying an arbitrary URL for webhook notifications. An attacker who can control the input to these tools could configure webhooks to send Cloudinary event data (e.g., upload notifications, asset metadata) to an external server under their control, leading to data exfiltration. Implement strict validation or allowlisting for webhook URLs. If arbitrary URLs are necessary, ensure that the data sent to these webhooks is minimal and does not contain sensitive information, or require explicit user confirmation for external URLs.	LLM	SKILL.md:150
MEDIUM	Unpinned dependency in manifest The skill's manifest specifies a dependency on the `rube` MCP server without a version constraint (`"mcp": ["rube"]`). This means that any new version of `rube` could be automatically used, potentially introducing breaking changes, vulnerabilities, or malicious code without explicit review, increasing supply chain risk. Pin the `rube` dependency to a specific version or version range (e.g., `["rube@1.2.3"]` or `["rube@^1.0.0"]`) to ensure deterministic builds and allow for controlled updates.	LLM	manifest.json:1

Scan History

Embed Code

[![SkillShield](https://skillshield.io/api/v1/badge/f9b404dcb1cdf393.svg)](https://skillshield.io/report/f9b404dcb1cdf393)