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SANDWORM_MODE: Shai-Hulud-Style npm Worm Hijacks CI Workflows and Poisons AI Toolchains
An emerging npm supply chain attack that infects repos, steals CI secrets, and targets developer AI toolchains for further compromise.
hypothesis
Advanced tools
Hypothesis is the property-based testing library for Python. With Hypothesis, you write tests which should pass for all inputs in whatever range you describe, and let Hypothesis randomly choose which of those inputs to check - including edge cases you might not have thought about. For example:
from hypothesis import given, strategies as st
@given(st.lists(st.integers()))
def test_matches_builtin(ls):
assert sorted(ls) == my_sort(ls)
This randomized testing can catch bugs and edge cases that you didn't think of and wouldn't have found. In addition, when Hypothesis does find a bug, it doesn't just report any failing example — it reports the simplest possible one. This makes property-based tests a powerful tool for debugging, as well as testing.
For instance,
def my_sort(ls):
return sorted(set(ls))
fails with the simplest possible failing example:
Falsifying example: test_matches_builtin(ls=[0, 0])
To install Hypothesis:
pip install hypothesis
There are also optional extras available.
FAQs
The property-based testing library for Python
We found that hypothesis demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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Research
An emerging npm supply chain attack that infects repos, steals CI secrets, and targets developer AI toolchains for further compromise.

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