skills

Least-privilege permissions

• Restrict skill access: Only grant skills permission to access the specific files and systems they absolutely need. For example, a code-review skill shouldn't have access to credential storage or deployment systems.
• Limit code execution scope: Run skills in isolated sandboxes (separate, contained environments) that prevent them from accessing the main system, similar to running apps in a secure container.
• Control agent prompts: Implement guardrails that prevent users from tricking the AI agent into using skills in unintended ways or accessing restricted information.
• Review user input: Validate and filter what data users can feed into skills to prevent injection of malicious instructions.

Network isolation

• Disable unnecessary connections: Configure skills to only connect to approved internal systems and public services; block internet access unless required for the skill's function.
• Use internal-only networks: Run the AI agent and its skills on isolated network segments that cannot reach production systems, databases, or credential vaults.
• Monitor outbound traffic: Log and alert on any unexpected network requests from skills to detect if a compromised skill tries to exfiltrate (steal) data.

Monitoring

• Audit skill execution: Log every action each skill performs—what files it accessed, what code it ran, and what data it returned—to detect suspicious behavior.
• Track dependency updates: Monitor the repository and all linked code libraries for security patches and updates; apply them promptly to prevent known vulnerabilities.
• Alert on anomalies: Set up automated notifications for unusual activity, such as skills accessing files outside their normal scope or executing unexpected code.

Red flags to watch for

• Unreviewed skill changes: Before deploying any new or updated skill, have a security expert review the code to ensure it doesn't contain hidden malicious functionality.
• Overly broad permissions: Skills requesting access to sensitive areas (credentials, production databases, payment systems) without clear justification are high risk.
• Vague or missing documentation: If a skill's purpose or code is unclear or undocumented, it's harder to trust—require clear documentation before use.
• Suspicious repository activity: Watch for unusual account access, rapid changes from unfamiliar contributors, or updates that don't match the skill's intended purpose.