A collection of test vectors that can be used to verify if a TUF or Uptane client conforms to the specification with regards to processing metadata and targets.
This repo contains server.py which provides an interactive API that directs
clients on how to perform updates. A client should use the following steps to
run through all the test vectors.
Client does a GET on / to receive a JSON array of strings naming the rest of
the vectors.
$ curl localhost:8080/
["vector_1", "another_vector", ... ]Because the vectors need to simulate time (via a "step"), each vector needs to
be intialized with a POST.
$ curl -X POST localhost:8080/$vector_name/step
{
"update": {
"is_success": true
},
"targets": {
"file.txt": {
"is_success": true
}
}
}The response will tell you what the result of an update cycle should be as well
as what targets to download and whether or not they should validate. If there
are errors, both the update and target object will have err and err_msg
along with is_success. err will be machine parseable and attempts to
enumerate common types and err_msg is a plain English sentance.
The client should attempt to do a full update of all metadata as defined in the
spec, and the success of this update should match update.is_success.
The client should download and verify the target. The success of this should
match targets.$target_name.is_success.
The client should POST to the same endpoint /$vector_name/step and repeate.
If the call to "step" returns HTTP 204, then the client is done.
To reset the vector, the client may POST to /$vector_name/reset. The client
may run tests in parallel, but the client may not run many tests against the
same one vector in parallel.
This code is licensed under the MIT license, a copy of which can be found in this repository. All code is copyright HERE Europe B.V., 2017-2020.
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