PyPI: python

CVE-2018-1000030

Safety vulnerability ID: SFTY-20180208-82008

Safety legacy ID: pyup.io-45645

Python 2.7.15 includes a fix for CVE-2018-1000030: Python 2.7.14 is vulnerable to a Heap-Buffer-Overflow as well as a Heap-Use-After-Free. Python versions prior to 2.7.14 may also be vulnerable and it appears that Python 2.7.17 and prior may also be vulnerable however this has not been confirmed. The vulnerability lies when multiply threads are handling large amounts of data. In both cases there is essentially a race condition that occurs. For the Heap-Buffer-Overflow, Thread 2 is creating the size for a buffer, but Thread1 is already writing to the buffer without knowing how much to write. So when a large amount of data is being processed, it is very easy to cause memory corruption using a Heap-Buffer-Overflow. As for the Use-After-Free, Thread3->Malloc->Thread1->Free's->Thread2-Re-uses-Free'd Memory. The PSRT has stated that this is not a security vulnerability due to the fact that the attacker must be able to run code, however in some situations, such as function as a service, this vulnerability can potentially be used by an attacker to violate a trust boundary, as such the DWF feels this issue deserves a CVE. https://bugs.python.org/issue31530

Created at: Oct 8, 2026Updated at: Oct 8, 2026

Overview

Python 2.7.15 includes a fix for CVE-2018-1000030: Python 2.7.14 is vulnerable to a Heap-Buffer-Overflow as well as a Heap-Use-After-Free. Python versions prior to 2.7.14 may also be vulnerable and it appears that Python 2.7.17 and prior may also be vulnerable however this has not been confirmed. The vulnerability lies when multiply threads are handling large amounts of data. In both cases there is essentially a race condition that occurs. For the Heap-Buffer-Overflow, Thread 2 is creating the size for a buffer, but Thread1 is already writing to the buffer without knowing how much to write. So when a large amount of data is being processed, it is very easy to cause memory corruption using a Heap-Buffer-Overflow. As for the Use-After-Free, Thread3->Malloc->Thread1->Free's->Thread2-Re-uses-Free'd Memory. The PSRT has stated that this is not a security vulnerability due to the fact that the attacker must be able to run code, however in some situations, such as function as a service, this vulnerability can potentially be used by an attacker to violate a trust boundary, as such the DWF feels this issue deserves a CVE. https://bugs.python.org/issue31530

Advisory

Python 2.7.15 includes a fix for CVE-2018-1000030: Python 2.7.14 is vulnerable to a Heap-Buffer-Overflow as well as a Heap-Use-After-Free. Python versions prior to 2.7.14 may also be vulnerable and it appears that Python 2.7.17 and prior may also be vulnerable however this has not been confirmed. The vulnerability lies when multiply threads are handling large amounts of data. In both cases there is essentially a race condition that occurs. For the Heap-Buffer-Overflow, Thread 2 is creating the size for a buffer, but Thread1 is already writing to the buffer without knowing how much to write. So when a large amount of data is being processed, it is very easy to cause memory corruption using a Heap-Buffer-Overflow. As for the Use-After-Free, Thread3->Malloc->Thread1->Free's->Thread2-Re-uses-Free'd Memory. The PSRT has stated that this is not a security vulnerability due to the fact that the attacker must be able to run code, however in some situations, such as function as a service, this vulnerability can potentially be used by an attacker to violate a trust boundary, as such the DWF feels this issue deserves a CVE. https://bugs.python.org/issue31530

Affected Package

Affecting python package, versions<2.7.15

Also affects

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How to Fix

Upgradepythonto2.7.15or higher.

Mitigation and Workarounds

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Vulnerable Functions

Functions linked to known vulnerabilities.

Vulnerable function data is available for Enterprise customers

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Safety

Verified by Safety

Our Cybersecurity Intelligence Team reviewed this vulnerability. We combine public data with our own research to find issues not yet reported to public sources.

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