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145 lines
4.5 KiB
HTML
145 lines
4.5 KiB
HTML
__mitmproxy__ has a powerful scripting API that allows you to modify flows
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on-the-fly or rewrite previously saved flows locally.
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The mitmproxy scripting API is event driven - a script is simply a Python
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module that exposes a set of event methods. Here's a complete mitmproxy script
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that adds a new header to every HTTP response before it is returned to the
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client:
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$!example("examples/add_header.py")!$
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The first argument to each event method is an instance of ScriptContext that
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lets the script interact with the global mitmproxy state. The __response__
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event also gets an instance of Flow, which we can use to manipulate the
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response itself.
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We can now run this script using mitmdump or mitmproxy as follows:
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<pre class="terminal">
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> mitmdump -s add_header.py
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</pre>
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The new header will be added to all responses passing through the proxy.
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## Events
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### start(ScriptContext, argv)
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Called once on startup, before any other events.
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### clientconnect(ScriptContext, ClientConnect)
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Called when a client initiates a connection to the proxy. Note that
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a connection can correspond to multiple HTTP requests.
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### request(ScriptContext, Flow)
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Called when a client request has been received. The __Flow__ object is
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guaranteed to have a non-None __request__ attribute.
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### response(ScriptContext, Flow)
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Called when a server response has been received. The __Flow__ object is
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guaranteed to have non-None __request__ and __response__ attributes.
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### error(ScriptContext, Flow)
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Called when a flow error has occurred, e.g. invalid server responses, or
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interrupted connections. This is distinct from a valid server HTTP error
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response, which is simply a response with an HTTP error code. The __Flow__
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object is guaranteed to have non-None __request__ and __error__ attributes.
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### clientdisconnect(ScriptContext, ClientDisconnect)
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Called when a client disconnects from the proxy.
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### done(ScriptContext)
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Called once on script shutdown, after any other events.
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## API
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The main classes you will deal with in writing mitmproxy scripts are:
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<table class="table">
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<tr>
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<th>libmproxy.flow.ClientConnection</th>
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<td>Describes a client connection.</td>
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</tr>
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<tr>
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<th>libmproxy.flow.ClientDisconnection</th>
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<td>Describes a client disconnection.</td>
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</tr>
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<tr>
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<th>libmproxy.flow.Error</th>
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<td>A communications error.</td>
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</tr>
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<tr>
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<th>libmproxy.flow.Flow</th>
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<td>A collection of objects representing a single HTTP transaction.</td>
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</tr>
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<tr>
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<th>libmproxy.flow.Headers</th>
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<td>HTTP headers for a request or response.</td>
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</tr>
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<tr>
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<th>libmproxy.flow.ODict</th>
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<td>A dictionary-like object for managing sets of key/value data. There
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is also a variant called CaselessODict that ignores key case for some
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calls (used mainly for headers).</td>
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</tr>
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<tr>
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<th>libmproxy.flow.Response</th>
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<td>An HTTP response.</td>
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</tr>
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<tr>
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<th>libmproxy.flow.Request</th>
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<td>An HTTP request.</td>
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</tr>
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<tr>
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<th>libmproxy.flow.ScriptContext</th>
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<td> A handle for interacting with mitmproxy's from within scripts. </td>
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</tr>
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<tr>
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<th>libmproxy.certutils.SSLCert</th>
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<td>Exposes information SSL certificates.</td>
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</tr>
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</table>
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The canonical API documentation is the code. You can view the API documentation
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using pydoc (which is installed with Python by default), like this:
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<pre class="terminal">
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> pydoc libmproxy.flow.Request
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</pre>
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## Running scripts in parallel
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We have a single flow primitive, so when a script is handling something, other requests block.
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While that's a very desirable behaviour under some circumstances, scripts can be run threaded by using the <code>libmproxy.script.concurrent</code> decorator.
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$!example("examples/nonblocking.py")!$
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## Running scripts on saved flows
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Sometimes, we want to run a script on __Flow__ objects that are already
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complete. This happens when you start a script, and then load a saved set of
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flows from a file (see the "scripted data transformation" example on the
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[mitmdump](@!urlTo("mitmdump.html")!@) page). It also happens when you run a
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one-shot script on a single flow through the _|_ (pipe) shortcut in mitmproxy.
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In this case, there are no client connections, and the events are run in the
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following order: __start__, __request__, __response__, __error__, __done__. If
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the flow doesn't have a __response__ or __error__ associated with it, the
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matching event will be skipped.
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