验证并清理所有内容
将模型提供的输入视为不可信内容。
验证并清理所有内容 是 CoddyKit 上的免费 MCP Academy 课时。 这是第 3 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 MCP Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 MCP Academy 课程共包含 4 节课。
本课时的部分内容尚未翻译，以英文显示。
Inputs Are Untrusted
Every argument the model passes to a tool is untrusted input. The model may be honest, but its arguments can be shaped by injected text, so verify them. 🔎
Validate Before You Act
Check shape, type, and range before a tool does anything real. Validation at the door turns a vague bad call into a clear, safe rejection.
Let Pydantic Help
Type hints and Pydantic models reject malformed arguments before your code runs. This input must be a positive int, so a string or a negative value is refused early.
from pydantic import Field
@mcp.tool()
def get_page(n: int = Field(gt=0, le=100)) -> str:
return load(n)Bound the Values
Cap sizes, lengths, and counts. A limit field on a query keeps the model from asking for a million rows and turning one call into a denial of service.
Sanitize for the Destination
Sanitizing means making input safe for where it lands. A value safe in a log can be dangerous in a shell, a SQL string, or a file path.
Never Build SQL by Hand
String-concatenated SQL invites injection. Use parameterized queries so the database treats model input strictly as a value, never as executable code.
cur.execute(
"SELECT * FROM orders WHERE id = ?",
(order_id,),
)Guard the Shell
If a tool runs a command, never paste arguments into a shell string. Pass an argument list and avoid shell parsing so input cannot smuggle in extra commands.
Resolve and Confine Paths
For file tools, resolve the path to its canonical form and confirm it stays inside your allowed root. Reject anything with a path traversal like dot-dot.
p = (ROOT / name).resolve()
if not p.is_relative_to(ROOT):
raise ValueError("path escapes root")Fail Closed
When input does not pass a check, stop and return a clear error. Failing closed beats guessing, because a wrong guess can be exactly what an attacker wants.
Do Not Trust Tool Output Either
Data your tool returns can carry injected instructions onward. Where it matters, label or escape fetched content so the model treats it as data, not orders.
Validate at Every Boundary
Check input as it enters your tool and again before it hits a database, file, or API. Each boundary is a fresh chance to catch something unsafe.
Quick Check
Which choice best protects a SQL query from injection?
Recap
Treat all tool inputs as untrusted: validate types and ranges, sanitize for the destination, confine paths, and fail closed. Distrust the input. ✅
常见问题解答
「验证并清理所有内容」课时是免费的吗？
是的 — 「验证并清理所有内容」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 MCP Academy 课程的其余内容，请升级到 CoddyKit PRO。 MCP Academy 课程共包含 4 节课。
「验证并清理所有内容」这节课中我会学到什么？
将模型提供的输入视为不可信内容。 你通过在浏览器中直接运行的动手代码来练习 MCP Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 MCP Academy 需要有经验吗？
无需任何先前经验。CoddyKit 上的 MCP Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 3 节课，共 4 节。
「验证并清理所有内容」课时需要多长时间？
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。
我能在这节 MCP Academy 课中编写并运行代码吗？
能。每节 MCP Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。