Trust Assessment
clip received a trust score of 82/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 4 findings: 0 critical, 0 high, 2 medium, and 2 low severity. Key findings include Network egress to untrusted endpoints, Covert behavior / concealment directives, Unpinned Git repository installation.
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 12, 2026 (commit 458b1186). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings4
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Network egress to untrusted endpoints HTTP request to raw IP address Review all outbound network calls. Remove connections to webhook collectors, paste sites, and raw IP addresses. Legitimate API calls should use well-known service domains. | Manifest | cli-tool/components/mcps/devtools/figma-dev-mode.json:4 | |
| MEDIUM | Unpinned Git repository installation The skill's installation instructions recommend installing a package directly from a Git repository URL (`git+https://github.com/openai/CLIP.git`) without specifying a commit hash or tag. This practice introduces a supply chain risk, as the content of the repository's default branch could change at any time, potentially introducing malicious code, breaking changes, or vulnerabilities without explicit version control. Pin the Git installation to a specific commit hash or tag (e.g., `pip install git+https://github.com/openai/CLIP.git@<commit_hash>`). Alternatively, if an official PyPI package exists and is maintained, prefer installing from PyPI with a version specifier. | LLM | SKILL.md:30 | |
| LOW | Covert behavior / concealment directives Multiple zero-width characters (stealth text) Remove hidden instructions, zero-width characters, and bidirectional overrides. Skill instructions should be fully visible and transparent to users. | Manifest | cli-tool/components/mcps/devtools/jfrog.json:4 | |
| LOW | Unpinned dependencies in manifest The skill's manifest specifies dependencies (`transformers`, `torch`, `pillow`) without pinning them to exact versions. This can lead to non-deterministic builds, compatibility issues, or the accidental installation of a vulnerable or malicious version if a dependency maintainer introduces one. While these are well-known libraries, best practice dictates pinning versions for reproducibility and security. Pin all dependencies to exact versions (e.g., `transformers==4.30.0`, `torch==2.0.0`, `pillow==9.5.0`) to ensure consistent and secure installations. | LLM | SKILL.md:1 |
Scan History
Embed Code
[](https://skillshield.io/report/1e81c2570543c099)
Powered by SkillShield