Trust Assessment
twilio received a trust score of 86/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 1 finding: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Potential Command Injection via unsanitized user input in `curl` arguments.
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 | |
|---|---|---|---|---|
| HIGH | Potential Command Injection via unsanitized user input in `curl` arguments The skill provides `curl` command examples that directly embed variables and string literals (e.g., `To=+1recipient`, `Body=Hello from Twilio!`). If an LLM constructs these commands by substituting user-provided input into parameters like `To`, `Body`, or `Url` without proper shell escaping, an attacker could inject arbitrary shell commands. For instance, a malicious `Body` value containing `$(evil_command)` could lead to arbitrary code execution on the host system when the command is executed. When generating and executing `curl` commands based on user input, ensure all user-controlled parameters (e.g., `To`, `Body`, `Url`) are properly shell-escaped to prevent command injection. Use a robust shell escaping mechanism for all dynamic parts of the command before execution. | LLM | SKILL.md:15 |
Scan History
Embed Code
[](https://skillshield.io/report/3fcded0bfa93a6ce)
Powered by SkillShield