Sandbox::https://redirect.github.com/numpy/numpy/issues/31688

AnkitAhlawat7742 · 2026-06-19T05:22:42Z

Fix #31686

PR summary

PR fixes a signed integer overflow in numpy/_core/src/multiarray/datetime.c that occurs when converting datetime64 values near INT64_MIN to Python objects via .item().the days_to_yearsdays() function performs (*days_) - (365*30 + 7) which causes undefined behavior when *days_ is near INT64_MIN . this solution will Reordered arithmetic operations to avoid overflow

First time committer introduction

NA

MaanasArora

Thanks, this would solve the issue I think! Just a refactor suggestion and should improve the test. That said, I actually couldn't reproduce this bug on main, which could be because C behavior with iinfo depends on the environment. Could you check if you can reproduce and if the test fails on main for you? (Fine if not I guess, but then we should maybe try to test this where it does...)

MaanasArora · 2026-06-22T07:40:16Z


+    if (*days_ < NPY_MIN_INT64 + days_offset) {
+        /* Extract 400-year cycles first to reduce magnitude */
+        days = *days_;


I think you could just add days_per_400years here, then we lose the days < 0 check (just always year -= 400). Since days_ is so negative this should be safe.

To make this read even simpler, you could add days_per_400years - days_offset, then you don't need to subtract from days below.

Thanks for the review.
I agree, and I've updated the code accordingly.

MaanasArora · 2026-06-22T07:47:30Z

+        info = np.iinfo(np.int64)
+
+        # Test INT64_MIN + 1
+        dt64 = np.datetime64(info.min + 1, "D")


This can be folded into the below for loop, already is there actually. (Then you could parametrize if you want, the test is not really that big though.)

MaanasArora · 2026-06-22T07:50:27Z

+        result = dt64.item()
+        # For dates outside Python's datetime range (year 1-9999),
+        # NumPy returns the raw integer value
+        assert isinstance(result, (int, datetime.date))


Not sure this is helpful, given those are the only two plausible dtypes and the segfault tested would happen above. For correctness it would be much better to check the actual values equal if int at least. Not sure, is there any reason we are including datetime.date anyway? These all seem to be small enough values that we should expect int?

Agree , Test case has been updated .

AnkitAhlawat7742 · 2026-06-22T14:42:36Z

Thanks, this would solve the issue I think! Just a refactor suggestion and should improve the test. That said, I actually couldn't reproduce this bug on main, which could be because iinfo depends on the environment. Could you check if you can reproduce and if the test fails on main for you? (Fine if not I guess, but then we should maybe try to test this where it does...)

Thanks for the review ...!!
For testing, I've informed the bug reporter(seems like it is happening in panda's side ) to verify it from their side as well, so we can confirm that the issue has been fully resolved.

MaanasArora

Thanks, sorry, my previous comment was a bit misleading - this should be tested with UBSan, in which case this does fail on main for me, so I think CI will catch it and the test looks good. Would be nice to check with pandas but aside from fixing the comment this looks good to me!

Edit: sorry, UBSan actually doesn't run on CI it seems. Not sure here, I'll wait for maintainer review for other opinions on testing.

MaanasArora · 2026-06-22T18:30:39Z

    npy_int64 year;

+    if (*days_ < NPY_MIN_INT64 + days_offset) {
+        /* Extract 400-year cycles first to reduce magnitude */


Suggested change

/* Extract 400-year cycles first to reduce magnitude */

/* Add 400-year cycle to ensure days does not overflow */

Seems clearer!

ngoldbaum

Thanks, I agree that this fixes the bug.

However, doesn't the exact same bug happen elsewhere?

For example:

numpy/numpy/_core/src/multiarray/datetime.c

Line 313 in ec56e82

ret = dts->year - 1970;

numpy/numpy/_core/src/multiarray/datetime.c

Line 317 in ec56e82

ret = 12 * (dts->year - 1970) + (dts->month - 1);

numpy/numpy/_core/src/multiarray/datetime.c

Line 330 in ec56e82

ret = (days - 6) / 7;

numpy/numpy/_core/src/multiarray/datetime.c

Lines 337 to 399 in ec56e82

    
               ret = days * 24 + 
        
                     dts->hour; 
        
               break; 
        
           case NPY_FR_m: 
        
               ret = (days * 24 + 
        
                     dts->hour) * 60 + 
        
                     dts->min; 
        
               break; 
        
           case NPY_FR_s: 
        
               ret = ((days * 24 + 
        
                     dts->hour) * 60 + 
        
                     dts->min) * 60 + 
        
                     dts->sec; 
        
               break; 
        
           case NPY_FR_ms: 
        
               ret = (((days * 24 + 
        
                     dts->hour) * 60 + 
        
                     dts->min) * 60 + 
        
                     dts->sec) * 1000 + 
        
                     dts->us / 1000; 
        
               break; 
        
           case NPY_FR_us: 
        
               ret = (((days * 24 + 
        
                     dts->hour) * 60 + 
        
                     dts->min) * 60 + 
        
                     dts->sec) * 1000000 + 
        
                     dts->us; 
        
               break; 
        
           case NPY_FR_ns: 
        
               ret = ((((days * 24 + 
        
                     dts->hour) * 60 + 
        
                     dts->min) * 60 + 
        
                     dts->sec) * 1000000 + 
        
                     dts->us) * 1000 + 
        
                     dts->ps / 1000; 
        
               break; 
        
           case NPY_FR_ps: 
        
               ret = ((((days * 24 + 
        
                     dts->hour) * 60 + 
        
                     dts->min) * 60 + 
        
                     dts->sec) * 1000000 + 
        
                     dts->us) * 1000000 + 
        
                     dts->ps; 
        
               break; 
        
           case NPY_FR_fs: 
        
               /* only 2.6 hours */ 
        
               ret = (((((days * 24 + 
        
                     dts->hour) * 60 + 
        
                     dts->min) * 60 + 
        
                     dts->sec) * 1000000 + 
        
                     dts->us) * 1000000 + 
        
                     dts->ps) * 1000 + 
        
                     dts->as / 1000; 
        
               break; 
        
           case NPY_FR_as: 
        
               /* only 9.2 secs */ 
        
               ret = (((((days * 24 + 
        
                     dts->hour) * 60 + 
        
                     dts->min) * 60 + 
        
                     dts->sec) * 1000000 + 
        
                     dts->us) * 1000000 + 
        
                     dts->ps) * 1000000 + 
        
                     dts->as;

Can't all of these mathematical operations on signed integers possibly overflow?

I would much rather we solve this generically rather than a one-off fix for this one particular issue.

Another way to fix this is to do intermediate calculations in a higher precision integer. We have a 128 bit integer implementation in NumPy for this purpose. That said, only the year is int64, everything else is int32 so you could cast to int64 cheaply for those cases.

Edit: sorry, UBSan actually doesn't run on CI it seems. Not sure here, I'll wait for maintainer review for other opinions on testing.

Yes it does: https://github.com/numpy/numpy/actions/runs/27960070587/job/82738842115?pr=31688

ngoldbaum · 2026-06-22T20:26:14Z

 {
    const npy_int64 days_per_400years = (400*365 + 100 - 4 + 1);
+    const npy_int64 days_offset = (365*30 + 7);
    /* Adjust so it's relative to the year 2000 (divisible by 400) */


this comment is orphaned now, move it above the if statement?

MaanasArora · 2026-06-22T20:45:16Z

Yes it does:

Ah sorry again, I just noticed that the test in this PR passes on main even on the UBSAN run (I accidentally opened #31713 and was then surprised). So we may need a stronger test. But I suppose we should be taking the generic approach.

Alvaro-Kothe · 2026-06-22T22:30:09Z

Yes it does: https://github.com/numpy/numpy/actions/runs/27960070587/job/82738842115?pr=31688

It seems that NumPy suppresses signed integer overflow in CI.

numpy/.github/workflows/compiler_sanitizers.yml

Line 82 in ccfa057

    
                   UBSAN_OPTIONS=halt_on_error=1:suppressions=${GITHUB_WORKSPACE}/tools/ci/ubsan_suppressions_arm64.txt \

numpy/tools/ci/ubsan_suppressions_arm64.txt

Line 8 in ccfa057

signed-integer-overflow:*

ngoldbaum · 2026-06-22T23:52:32Z

Yeah, we want to eventually delete all those suppressions by fixing these bugs!

AnkitAhlawat7742 · 2026-06-25T05:56:24Z

Thank you for the feedback, @ngoldbaum and @MaanasArora
can we take this fix for the issue which is raised by @Alvaro-Kothe ? and I can create a follow-up PR for a comprehensive overflow
what you guys say ?

ngoldbaum · 2026-07-03T20:21:01Z

Please go ahead. Also for future notice, you don't need to ask to take up PRs like that. It just causes delays.

BUG: Fix signed integer overflow in datetime.c (#31688)

This MR contains the following updates: | Package | Type | Update | Change | OpenSSF | |---|---|---|---|---| | [numpy](https://github.com/numpy/numpy) ([changelog](https://numpy.org/doc/stable/release)) | dependencies | patch | `2.5.0` → `2.5.2` | [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/numpy/numpy/badge)](https://securityscorecards.dev/viewer/?uri=github.com/numpy/numpy) | | [uvicorn](https://github.com/Kludex/uvicorn) ([changelog](https://uvicorn.dev/release-notes)) | dependencies | patch | `0.52.1` → `0.52.3` | [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/Kludex/uvicorn/badge)](https://securityscorecards.dev/viewer/?uri=github.com/Kludex/uvicorn) | --- ### Release Notes <details> <summary>numpy/numpy (numpy)</summary> ### [`v2.5.2`](https://github.com/numpy/numpy/releases/tag/v2.5.2): (Aug 9, 2026) [Compare Source](numpy/numpy@v2.5.1...v2.5.2) ### NumPy 2.5.2 Release Notes The NumPy 2.5.2 is a patch release that fixes bugs discovered after the 2.5.1 release. The big news is that it includes wheels for the newly released Python 3.15.0rc1. This release supports Python versions 3.12-3.15 #### C API changes ##### `PyArray_StringDTypeObject` is opaque under the abi3t stable ABI The `PyArray_StringDTypeObject` was accidentally exposed in NumPy 2.5 when targeting the free-threading-compatible stable ABI (`Py_TARGET_ABI3T`). `PyArray_StringDTypeObject` is now an opaque struct: extensions compiled that way cannot access its fields, since the struct layout depends on the size of the object header. Any code that accessed `PyArray_StringDTypeObject` fields in an abi3t build would have crashed, so we are making this API change in a bugfix release. The `NpyString` allocator API remains usable by passing the descriptor object pointer, e.g. `NpyString_acquire_allocator((PyArray_StringDTypeObject *)descr)`. ([gh-31771](numpy/numpy#31771)) #### Contributors A total of 16 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Abhijeetsingh Meena + - Charalampos Stratakis - Charles Harris - Chris Ninham + - David Woods - Geonho + - Gopu Yeshwanth Reddy + - Iason Krommydas - Ijtihed Kilani - Jelle Zijlstra + - Joren Hammudoglu - Kumar Aditya - Mike Boyle - Nathan Goldbaum - Raghuveer Devulapalli - Sebastian Berg #### Pull requests merged A total of 28 pull requests were merged for this release. - [#31864](numpy/numpy#31864): MAINT: Prepare 2.5.x for further development - [#31889](numpy/numpy#31889): TYP: Backport multiple static typing fixes 1. - [#31900](numpy/numpy#31900): TST: add tests for stable ABI numpy extensions ([#31822](numpy/numpy#31822)) - [#31901](numpy/numpy#31901): BUG: fix `StringDType` coerce flag in binary ufunc promotion... - [#31902](numpy/numpy#31902): BLD: fix meson deprecation warnings ([#31892](numpy/numpy#31892)) - [#31921](numpy/numpy#31921): TYP: Backport multiple typing fixes 2. - [#31947](numpy/numpy#31947): MAINT: Update x86-simd-sort subproject ([`5adb334`](numpy/numpy@5adb334) → [`fa944ef`](numpy/numpy@fa944ef)) ([#31908](numpy/numpy#31908)) - [#31949](numpy/numpy#31949): BUG: fix crash on 32 bit systems using abi3t ([#31771](numpy/numpy#31771)) - [#31950](numpy/numpy#31950): MNT: remove some obsolete string to bool workarounds ([#31859](numpy/numpy#31859)) - [#31952](numpy/numpy#31952): BUG: centralized helper for output coerce and na\_object in stringdtype... - [#31953](numpy/numpy#31953): BUG: fix CPU feature env diagnostic buffer overruns ([#31905](numpy/numpy#31905)) - [#31954](numpy/numpy#31954): BUG: restore ndarray.conjugate() for legacy user-defined dtypes... - [#31955](numpy/numpy#31955): TYP: Avoid shadowed dtype annotations - [#32077](numpy/numpy#32077): MAINT: Update verdored-meson/meson to match main. - [#32114](numpy/numpy#32114): BUG: fix refcount leak on overlapping copyto with where=False - [#32115](numpy/numpy#32115): BUG: fix swallowed cast error in fancy indexing assignment ([#31975](numpy/numpy#31975)) - [#32116](numpy/numpy#32116): BUG: Fix buffered iterator stride after removing multi-index - [#32117](numpy/numpy#32117): BUG: fix `np.fromiter` corruption when reusing a `StringDType`... - [#32119](numpy/numpy#32119): BUG: add a special case for StringDType in np.isdtype ([#32030](numpy/numpy#32030)) - [#32121](numpy/numpy#32121): BUG: reference leak in `simd_sequence_from_iterable` ([#32038](numpy/numpy#32038)) - [#32122](numpy/numpy#32122): BUG: ensure lock is held when accessing or writing to RNG state... - [#32123](numpy/numpy#32123): BUG: fully reset cached RNG state for non-MT19937 RNGs ([#32062](numpy/numpy#32062)) - [#32135](numpy/numpy#32135): TYP: type capabilities max dimensions - [#32158](numpy/numpy#32158): BUG: avoid possible stack overflow in arraydescr\_dealloc ([#32133](numpy/numpy#32133)) - [#32206](numpy/numpy#32206): MAINT: Update cibuildwheel to v4.2.0 - [#32214](numpy/numpy#32214): MAINT: Skip limited\_api tests on some platforms. - [#32220](numpy/numpy#32220): TYP: `isclose` shape-typing fix for 2d array-likes ([#32205](numpy/numpy#32205)) - [#32221](numpy/numpy#32221): BUG: avoid segfaults when legacy copyswap slot is not defined... ### [`v2.5.1`](https://github.com/numpy/numpy/releases/tag/v2.5.1): (July 4, 2026) [Compare Source](numpy/numpy@v2.5.0...v2.5.1) ### NumPy 2.5.1 Release Notes The NumPy 2.5.1 is a patch release that fixes bugs discovered after the 2.5.0 release. The most noticeable is the fix is to the numpy datetime cython API which should allow downstream to support NumPy versions older than 2.5. Preparation for Python 3.15 continues along with typing improvements. This release supports Python versions 3.12-3.14 #### Changes - The minimum supported GCC version has been updated from 9.3.0 to 10.3.0 ([gh-31843](numpy/numpy#31843)) #### Contributors A total of 10 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Adhyan Gupta + - Ankit Ahlawat - Charles Harris - Iason Krommydas - Joren Hammudoglu - Kumar Aditya - Nathan Goldbaum - Sebastian Berg - Ties Jan Hefting + - Vineet Kumar #### Pull requests merged A total of 20 pull requests were merged for this release. - [#31707](numpy/numpy#31707): MAINT: Prepare 2.5.x for further development - [#31721](numpy/numpy#31721): CI: fix new `cython-lint` errors ([#31711](numpy/numpy#31711)) - [#31723](numpy/numpy#31723): MAINT: Update meson to match main - [#31729](numpy/numpy#31729): TST: use setup-sde instead of curl to get SDE binaries ([#31727](numpy/numpy#31727)) - [#31829](numpy/numpy#31829): BUG: Relax finfo to be easier accessible for all user dtypes... - [#31831](numpy/numpy#31831): TYP: Fix `flatiter.__next__` return type for `object_` and... - [#31832](numpy/numpy#31832): BUG: avoid deadlocks using NpyString API ([#31682](numpy/numpy#31682)) - [#31833](numpy/numpy#31833): BUG: fix out array leak in reduceat and accumulate when dtype... - [#31835](numpy/numpy#31835): BUG: fix numpy datetime cython APIs to be compatible with older... - [#31836](numpy/numpy#31836): TYP: Fix incorrect dtype inference of `asarray([])` ([#31732](numpy/numpy#31732)) - [#31837](numpy/numpy#31837): TYP: Fix `np.ma.masked_array` 2.5.0 regression - [#31838](numpy/numpy#31838): FIX: Refactor error handling in array\_setstate to prevent typecode... - [#31839](numpy/numpy#31839): TST: xfail multithreaded BLAS test more generously - [#31840](numpy/numpy#31840): MAINT: Rename subroutine for crackfortran tests - [#31842](numpy/numpy#31842): BUG: fix leak in reductions when a ufunc override errors or is... - [#31849](numpy/numpy#31849): BLD: set minimum required gcc version to 10.3 ([#31843](numpy/numpy#31843)) - [#31855](numpy/numpy#31855): CI: fix hangs on MacOS ASan CI ([#31853](numpy/numpy#31853)) - [#31856](numpy/numpy#31856): BUG: fix several bugs in StringDType operations ([#31846](numpy/numpy#31846)) - [#31857](numpy/numpy#31857): BUG: Fix segfault in MT19937 by preventing recursive seed lists... - [#31858](numpy/numpy#31858): BUG: Fix signed integer overflow in datetime.c ([#31688](numpy/numpy#31688)) </details> <details> <summary>Kludex/uvicorn (uvicorn)</summary> ### [`v0.52.3`](https://github.com/Kludex/uvicorn/releases/tag/0.52.3): Version 0.52.3 [Compare Source](Kludex/uvicorn@0.52.2...0.52.3) ##### Changed - Update `zttp` to 0.0.24 and use its combined receive path, improving HTTP/1.1 request parsing performance ([#3067](Kludex/uvicorn#3067)) **Full Changelog**: <Kludex/uvicorn@0.52.2...0.52.3> ### [`v0.52.2`](https://github.com/Kludex/uvicorn/releases/tag/0.52.2): Version 0.52.2 [Compare Source](Kludex/uvicorn@0.52.1...0.52.2) ##### Fixed - Update `zttp` to 0.0.22, fixing bodyless request receives and improving HTTP/1 request parsing performance ([#3063](Kludex/uvicorn#3063)) **Full Changelog**: <Kludex/uvicorn@0.52.1...0.52.2> </details> --- - [ ] If you want to rebase/retry this MR, check this box --- This MR has been generated by [Mend Renovate CLI](https://github.com/renovatebot/renovate).  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test_datetime64_item_int64_min_edge_case asserted that .item() on a datetime64 near int64 min returns a Python int, which no longer holds. Assert the datetime64 round-trip instead, and reach the conversion that used to overflow through str(), which still goes through days_to_yearsdays. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01YF8EFz6MfYRc2whjZEiDtu

fix:Signed integer overflow in datetime.c

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MaanasArora reviewed Jun 22, 2026

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ENH: code and test case imp

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MaanasArora approved these changes Jun 22, 2026

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MaanasArora added the 00 - Bug label Jun 22, 2026

ngoldbaum reviewed Jun 22, 2026

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ngoldbaum mentioned this pull request Jun 23, 2026

BUG: Signed integer overflow in datetime.c:days_to_yearsdays on near-minimum np.datetime64 #31686

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ngoldbaum merged commit cd1cfb8 into numpy:main Jul 3, 2026
84 of 87 checks passed

charris added the 09 - Backport-Candidate PRs tagged should be backported label Jul 3, 2026

charris changed the title ~~fix:Signed integer overflow in datetime.c~~ BUG: Fix signed integer overflow in datetime.c Jul 4, 2026

charris mentioned this pull request Jul 4, 2026

BUG: Fix signed integer overflow in datetime.c (#31688) #31858

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charris removed the 09 - Backport-Candidate PRs tagged should be backported label Jul 4, 2026

charris pushed a commit that referenced this pull request Jul 4, 2026

fix:Signed integer overflow in datetime.c (#31688)

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charris added a commit that referenced this pull request Jul 4, 2026

Merge pull request #31858 from charris/backport-31688

9df8516

BUG: Fix signed integer overflow in datetime.c (#31688)

MaanasArora pushed a commit to MaanasArora/numpy that referenced this pull request Jul 7, 2026

fix:Signed integer overflow in datetime.c (numpy#31688)

064b75c

AnkitAhlawat7742 mentioned this pull request Jul 9, 2026

BUG: Signed integer overflow in datetime.c - comprehensive fix needed for all arithmetic operations #31926

Open

AnkitAhlawat7742 mentioned this pull request Aug 7, 2026

BUG: Fix signed integer overflow in datetime #32218

Open

	/* Extract 400-year cycles first to reduce magnitude */
	/* Add 400-year cycle to ensure days does not overflow */

	ret = days * 24 +
	dts->hour;
	break;
	case NPY_FR_m:
	ret = (days * 24 +
	dts->hour) * 60 +
	dts->min;
	break;
	case NPY_FR_s:
	ret = ((days * 24 +
	dts->hour) * 60 +
	dts->min) * 60 +
	dts->sec;
	break;
	case NPY_FR_ms:
	ret = (((days * 24 +
	dts->hour) * 60 +
	dts->min) * 60 +
	dts->sec) * 1000 +
	dts->us / 1000;
	break;
	case NPY_FR_us:
	ret = (((days * 24 +
	dts->hour) * 60 +
	dts->min) * 60 +
	dts->sec) * 1000000 +
	dts->us;
	break;
	case NPY_FR_ns:
	ret = ((((days * 24 +
	dts->hour) * 60 +
	dts->min) * 60 +
	dts->sec) * 1000000 +
	dts->us) * 1000 +
	dts->ps / 1000;
	break;
	case NPY_FR_ps:
	ret = ((((days * 24 +
	dts->hour) * 60 +
	dts->min) * 60 +
	dts->sec) * 1000000 +
	dts->us) * 1000000 +
	dts->ps;
	break;
	case NPY_FR_fs:
	/* only 2.6 hours */
	ret = (((((days * 24 +
	dts->hour) * 60 +
	dts->min) * 60 +
	dts->sec) * 1000000 +
	dts->us) * 1000000 +
	dts->ps) * 1000 +
	dts->as / 1000;
	break;
	case NPY_FR_as:
	/* only 9.2 secs */
	ret = (((((days * 24 +
	dts->hour) * 60 +
	dts->min) * 60 +
	dts->sec) * 1000000 +
	dts->us) * 1000000 +
	dts->ps) * 1000000 +
	dts->as;

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AnkitAhlawat7742 commented Jun 19, 2026

Fix #31686

PR summary

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