[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-03-02 Thread Serhiy Storchaka

Serhiy Storchaka added the comment:

May be apply the fix to 3.3?

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-03-02 Thread Benjamin Peterson

Benjamin Peterson added the comment:

That would be nice.

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-02-28 Thread Arfrever Frehtes Taifersar Arahesis

Changes by Arfrever Frehtes Taifersar Arahesis arfrever@gmail.com:


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nosy: +Arfrever
versions: +Python 2.7, Python 3.4

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-02-16 Thread Serhiy Storchaka

Changes by Serhiy Storchaka storch...@gmail.com:


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resolution:  - fixed
stage: patch review - resolved
status: open - closed

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-02-16 Thread Roundup Robot

Roundup Robot added the comment:

New changeset d83884b3a427 by Serhiy Storchaka in branch '2.7':
Issue #23446: Use PyMem_New instead of PyMem_Malloc to avoid possible integer
https://hg.python.org/cpython/rev/d83884b3a427

New changeset 036a2aceae93 by Serhiy Storchaka in branch '3.4':
Issue #23446: Use PyMem_New instead of PyMem_Malloc to avoid possible integer
https://hg.python.org/cpython/rev/036a2aceae93

New changeset d12c7938c4b0 by Serhiy Storchaka in branch 'default':
Issue #23446: Use PyMem_New instead of PyMem_Malloc to avoid possible integer
https://hg.python.org/cpython/rev/d12c7938c4b0

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-02-12 Thread Serhiy Storchaka

Serhiy Storchaka added the comment:

 In _testbuffer.c:  ndim = 64, so the changes aren't really necessary.

Indeed, I'll remove these changes.

 The reason is of course that even an array with only 2 elements per
dimension gets quite large with ndim=64. :)

But an array can be with 1 element per dimension. In any case it is good that 
there is strict limitation on ndim values.

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-02-12 Thread Stefan Krah

Stefan Krah added the comment:

Yes, but these (degenerate) arrays tend to arise only as a result of slicing.
Last time I looked NumPy had MAX_NDIM=32, so we should be fine.

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-02-11 Thread Serhiy Storchaka

New submission from Serhiy Storchaka:

Proposed patch replaces PyMem_Malloc with PyMem_New if the former is used in 
the form PyMem_Malloc(len * sizeof(type)). This can fix possible overflow 
errors and makes the code cleaner.

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components: Extension Modules, Interpreter Core
files: pymem_new.patch
keywords: patch
messages: 235758
nosy: benjamin.peterson, haypo, serhiy.storchaka
priority: normal
severity: normal
stage: patch review
status: open
title: Use PyMem_New instead of PyMem_Malloc
type: enhancement
versions: Python 3.5
Added file: http://bugs.python.org/file38099/pymem_new.patch

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-02-11 Thread Stefan Krah

Stefan Krah added the comment:

In _testbuffer.c:  ndim = 64, so the changes aren't really necessary.
Somehow this fact needs to get widely known, since it does not make
sense to check for overflow anytime ndim is used.

The reason is of course that even an array with only 2 elements per
dimension gets quite large with ndim=64. :)

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[issue23446] Use PyMem_New instead of PyMem_Malloc

2015-02-11 Thread Benjamin Peterson

Benjamin Peterson added the comment:

Very nice. I think you should also apply it to older versions, since (as we 
now) this sort of thing is very liable to cause security problems.

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