Security audit
Security checks for vulnerabilities and agentic risk
This skill is framed as an LLM prompt enhancer, but it asks an agent to fetch remote system-style instructions, stores an API key in a local .env file, and contains mismatched service identity details that deserve manual review.
Install only if you intentionally want an external XiaoBenYang service to provide prompt or system-instruction text to your agent. Treat anything returned by the service as untrusted content, do not let it override system/developer/user instructions, and avoid storing valuable API keys in the project .env file unless you accept the plaintext local-storage risk.
default_year: int = 2025
def model_post_init(self, __context):
# 强制从 .env 文件读取 XBY_APIKEY
env_path = Path(".env")
if env_path.exists():
content = env_path.read_text(encoding="utf-8")def save_api_key_to_env(api_key: str) -> bool:
"""将API key保存到.env文件"""
try:
env_path = Path(".env")
lines = []
if env_path.exists():
lines = env_path.read_text(encoding="utf-8").splitlines()def set_api_key(api_key: str) -> bool:
"""设置API key并持久化到.env"""
if not api_key or not api_key.strip():
return False
api_key = api_key.strip()requests>=2.31.0 pydantic>=2.7.0 pydantic-settings>=2.2.0 python-dotenv>=1.0.1
requests>=2.31.0 pydantic>=2.7.0 pydantic-settings>=2.2.0 python-dotenv>=1.0.1
requests>=2.31.0 pydantic>=2.7.0 pydantic-settings>=2.2.0 python-dotenv>=1.0.1
requests>=2.31.0 pydantic>=2.7.0 pydantic-settings>=2.2.0 python-dotenv>=1.0.1
No suspicious patterns detected.