numpy: crafted serialized object passed in numpy.load() in pickle python module allows arbitrary code execution
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
| Vendor | Product | Default status | Versions | ||||||
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| n/a | n/a | affected |
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Configuration 1 [-]
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Configuration 2 [-]
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| Package | CPE | Advisory | Released Date |
|---|---|---|---|
| Red Hat Enterprise Linux 8 | |||
| python27:2.7-8010020190903182548.51c94b97 | cpe:/a:redhat:enterprise_linux:8 | RHSA-2019:3335 | 2019-11-05T00:00:00Z |
| numpy-1:1.14.3-9.el8 | cpe:/a:redhat:enterprise_linux:8 | RHSA-2019:3704 | 2019-11-05T00:00:00Z |
No data available yet.
| Source | ID | Title |
|---|---|---|
Github GHSA |
GHSA-9fq2-x9r6-wfmf | Numpy Deserialization of Untrusted Data |
No CVSS v4.0
No CVSS v3.1
This CVE is not in the KEV list.
Exploit prediction score: 27.3% (27.266% probability within 30 days)
Key SSVC decision points have not yet been added.
| Type | Values Removed | Values Added |
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| Description | An issue was discovered in NumPy 1.16.0 and earlier. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources | An issue was discovered in NumPy before 1.16.3. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources. |
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