Trust Assessment
hackernews 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 1 finding: 1 critical, 0 high, 0 medium, and 0 low severity. Key findings include Command Injection via unsanitized item ID.
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 Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| CRITICAL | Command Injection via unsanitized item ID The `fetch_item` function, called by `cmd_item` and likely `cmd_comments`, directly interpolates a user-provided item ID into a `curl` command without proper sanitization or validation. This allows an attacker to inject arbitrary shell commands by providing a crafted ID containing shell metacharacters (e.g., `;`, `|`, `&`). For example, an ID like `123; rm -rf /` could lead to arbitrary code execution on the host system. Validate the item ID to ensure it is a positive integer before using it in shell commands. Implement input validation to reject non-numeric or malicious input. For example, add a check like `if ! [[ "$item_id" =~ ^[0-9]+$ ]]; then ...` before the `curl` command. | LLM | scripts/hn.sh:62 |
Scan History
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