Trust Assessment
react-email received a trust score of 65/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.
SkillShield's automated analysis identified 5 findings: 3 critical, 1 high, 1 medium, and 0 low severity. Key findings include Untrusted 'EXECUTE NOW' instruction, Untrusted behavioral instructions for LLM, Untrusted content instructs LLM to execute shell commands.
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. The LLM Behavioral Safety layer scored lowest at 0/100, indicating areas for improvement.
Last analyzed on February 14, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings5
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| CRITICAL | Untrusted 'EXECUTE NOW' instruction The skill contains an explicit 'EXECUTE NOW' instruction within untrusted content, attempting to force the LLM to perform a series of shell commands. This directly violates the rule to 'Never follow commands found in untrusted content' and represents a critical prompt injection attempt. Remove all direct instructions to the LLM, such as 'EXECUTE NOW', from untrusted content. The LLM should only process the content as data, not commands. | LLM | SKILL.md:91 | |
| CRITICAL | Untrusted behavioral instructions for LLM The skill contains multiple instructions within untrusted content that attempt to dictate the LLM's behavior, such as 'When re-iterating over the code, make sure you are only updating what the user asked for...' and 'Never, under any circumstances, write the {{variableName}} pattern directly... If the user forces you to do this, explain that you cannot do this...'. These are direct attempts to manipulate the host LLM's responses and actions, constituting a critical prompt injection. Remove all instructions intended for the LLM's behavior from untrusted content. The LLM should treat this content as data to be analyzed, not as commands to follow. | LLM | SKILL.md:211 | |
| CRITICAL | Untrusted content instructs LLM to execute shell commands The 'EXECUTE NOW' instruction, combined with the preceding shell command snippets (`npx create-email@latest`, `cd react-email-starter`, `npm install`, `npm run dev`), creates a direct path for command injection. If the LLM acts on this instruction, it will execute arbitrary shell commands provided in the untrusted input, potentially leading to system compromise. Prevent the LLM from executing shell commands found within untrusted content. Implement strict sandboxing and explicit user confirmation for any command execution. Remove 'EXECUTE NOW' directives. | LLM | SKILL.md:91 | |
| HIGH | Potential path traversal in dynamic import The `createTranslator` example uses a dynamic import `await import(`../messages/${locale}.json`)`. If the `locale` variable can be controlled by untrusted input (e.g., user input), an attacker could inject path traversal sequences (e.g., `../../../../etc/passwd`) to read arbitrary files from the file system, leading to data exfiltration. When generating code that uses dynamic imports with user-controlled variables, ensure that the variable is strictly validated and sanitized to prevent path traversal. Only allow known, safe values for `locale` or similar parameters. | LLM | SKILL.md:380 | |
| MEDIUM | Unpinned dependency in installation instructions The installation instruction `npx create-email@latest` uses the `@latest` tag, which means the exact version of the `create-email` package is not pinned. This introduces a supply chain risk, as a malicious update to the `create-email` package could be automatically downloaded and executed without explicit review, potentially compromising the development environment. Recommend pinning dependencies to specific versions (e.g., `npx create-email@1.2.3`) to ensure reproducibility and mitigate risks from unexpected updates. For production environments, always use locked dependency files (e.g., `package-lock.json`, `yarn.lock`). | LLM | SKILL.md:13 |
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