Change FOR_ITER to have the same stack effect regardless of whether it branches or not.
Performance is unchanged as FOR_ITER (and specialized forms jump over the cleanup code).
Add Python implementations of certain longobject.c functions. These use
asymptotically faster algorithms that can be used for operations on
integers with many digits. In those cases, the performance overhead of
the Python implementation is not significant since the asymptotic
behavior is what dominates runtime. Functions provided by this module
should be considered private and not part of any public API.
Co-author: Tim Peters <tim.peters@gmail.com>
Co-author: Mark Dickinson <dickinsm@gmail.com>
Co-author: Bjorn Martinsson
Work on test coverage for `PyObject_Print` made it clear that some lines can't get executed.
Simplify the function by excluding the checks for non-string types.
Also eliminate creating a temporary bytes object.
The os module and the PyUnicode_FSDecoder() function no longer accept
bytes-like paths, like bytearray and memoryview types: only the exact
bytes type is accepted for bytes strings.
asciilib_count() is the same than ucs1lib_count(): the code is not
specialized for ASCII strings, so it's not worth it to have a
separated function. Remove asciilib_count() function.
It had to live as a global outside of PyConfig for stable ABI reasons in
the pre-3.12 backports.
This removes the `_Py_global_config_int_max_str_digits` and gets rid of
the equivalent field in the internal `struct _is PyInterpreterState` as
code can just use the existing nested config struct within that.
Adds tests to verify unique settings and configs in subinterpreters.
Fix multiplying a list by an integer (list *= int): detect the
integer overflow when the new allocated length is close to the
maximum size. Issue reported by Jordan Limor.
list_resize() now checks for integer overflow before multiplying the
new allocated length by the list item size (sizeof(PyObject*)).
This is a preliminary PR to refactor `PyLong_FromString` which is currently quite messy and has spaghetti like code that mixes up different concerns as well as duplicating logic.
In particular:
- `PyLong_FromString` now only handles sign, base and prefix detection and calls a new function `long_from_string_base` to parse the main body of the string.
- The `long_from_string_base` function handles all string validation and then calls `long_from_binary_base` or a new function `long_from_non_binary_base` to construct the actual `PyLong`.
- The existing `long_from_binary_base` function is simplified by factoring duplicated logic to `long_from_string_base`.
- The new function `long_from_non_binary_base` factors out much of the code from `PyLong_FromString` including in particular the quadratic algorithm reffered to in gh-95778 so that this can be seen separately from unrelated concerns such as string validation.
Converting a large enough `int` to a decimal string raises `ValueError` as expected. However, the raise comes _after_ the quadratic-time base-conversion algorithm has run to completion. For effective DOS prevention, we need some kind of check before entering the quadratic-time loop. Oops! =)
The quick fix: essentially we catch _most_ values that exceed the threshold up front. Those that slip through will still be on the small side (read: sufficiently fast), and will get caught by the existing check so that the limit remains exact.
The justification for the current check. The C code check is:
```c
max_str_digits / (3 * PyLong_SHIFT) <= (size_a - 11) / 10
```
In GitHub markdown math-speak, writing $M$ for `max_str_digits`, $L$ for `PyLong_SHIFT` and $s$ for `size_a`, that check is:
$$\left\lfloor\frac{M}{3L}\right\rfloor \le \left\lfloor\frac{s - 11}{10}\right\rfloor$$
From this it follows that
$$\frac{M}{3L} < \frac{s-1}{10}$$
hence that
$$\frac{L(s-1)}{M} > \frac{10}{3} > \log_2(10).$$
So
$$2^{L(s-1)} > 10^M.$$
But our input integer $a$ satisfies $|a| \ge 2^{L(s-1)}$, so $|a|$ is larger than $10^M$. This shows that we don't accidentally capture anything _below_ the intended limit in the check.
<!-- gh-issue-number: gh-95778 -->
* Issue: gh-95778
<!-- /gh-issue-number -->
Co-authored-by: Gregory P. Smith [Google LLC] <greg@krypto.org>
Integer to and from text conversions via CPython's bignum `int` type is not safe against denial of service attacks due to malicious input. Very large input strings with hundred thousands of digits can consume several CPU seconds.
This PR comes fresh from a pile of work done in our private PSRT security response team repo.
Signed-off-by: Christian Heimes [Red Hat] <christian@python.org>
Tons-of-polishing-up-by: Gregory P. Smith [Google] <greg@krypto.org>
Reviews via the private PSRT repo via many others (see the NEWS entry in the PR).
<!-- gh-issue-number: gh-95778 -->
* Issue: gh-95778
<!-- /gh-issue-number -->
I wrote up [a one pager for the release managers](https://docs.google.com/document/d/1KjuF_aXlzPUxTK4BMgezGJ2Pn7uevfX7g0_mvgHlL7Y/edit#). Much of that text wound up in the Issue. Backports PRs already exist. See the issue for links.
⚠️⚠️ Note for reviewers, hackers and fellow systems/low-level/compiler engineers ⚠️⚠️
If you have a lot of experience with this kind of shenanigans and want to improve the **first** version, **please make a PR against my branch** or **reach out by email** or **suggest code changes directly on GitHub**.
If you have any **refinements or optimizations** please, wait until the first version is merged before starting hacking or proposing those so we can keep this PR productive.
Benjamin Peterson