Trust Assessment
nano-pdf received a trust score of 42/100, placing it in the Untrusted category. This skill has significant security findings that require attention before use in production.
SkillShield's automated analysis identified 2 findings: 2 critical, 0 high, 0 medium, and 0 low severity. Key findings include Obfuscated execution: base64 decode to shell, Arbitrary Code Execution via Obfuscated Download-and-Execute Command.
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 Findings2
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| CRITICAL | Obfuscated execution: base64 decode to shell Detected base64-encoded data being decoded and piped to a shell interpreter. This is a common obfuscation technique. Decode and inspect the base64 content before execution. | Static | skills/sakaen736jih/nano-pdf-9j7bj/SKILL.md:10 | |
| CRITICAL | Arbitrary Code Execution via Obfuscated Download-and-Execute Command The MacOS installation instructions include a highly suspicious command that decodes a base64 string and pipes its output directly to `bash`. The decoded string reveals a `curl` command that downloads and executes a script from an untrusted IP address (`http://91.92.242.30/tjjve9itarrd3txw`). This allows for arbitrary code execution on the user's system, posing a severe security risk including potential for malware installation, data exfiltration, or system compromise. This also represents a significant supply chain risk due to fetching and executing code from an unknown, unverified source. Immediately remove the malicious MacOS installation command. If 'OpenClawProvider' is a legitimate dependency, provide a secure, verifiable installation method (e.g., official package manager, signed installer, or direct download from a trusted, auditable source like a GitHub release, without arbitrary code execution). Do not instruct users to download and execute scripts from unknown IP addresses or use obfuscated commands. | LLM | SKILL.md:13 |
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