What is the CVSS score of CVE-2020-15193?

CVE-2020-15193 has a CVSS 3.1 base score of 7.1 (High). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L. EPSS exploitation probability: 0.7%.

Is there a public PoC exploit available for CVE-2020-15193?

Yes, a public proof-of-concept exploit is available for CVE-2020-15193. Prioritise patching immediately. EPSS: 0.7%.

Is there a patch available for CVE-2020-15193?

Yes, a patch is available for CVE-2020-15193. Update the affected software to the latest version immediately.

Python CVE-2020-15193

HIGH

Use of Uninitialized Resource (CWE-908)

2020-09-25 security-advisories@github.com

Buffer Overflow Python Tensorflow Leap

7.1

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

7.1 HIGH

AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L

Attack Vector

Network

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

None

Integrity

High

Availability

Low

Lifecycle Timeline

CVE Published

Sep 25, 2020 - 19:15 nvd

HIGH 7.1

Blast Radius

ecosystem impact

† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth

2 pypi packages depend on tensorflow-gpu (2 direct, 0 indirect)

Ecosystem-wide dependent count for version 2.2.0.

DescriptionNVD

In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of dlpack.to_dlpack can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a reinterpret_cast Since the PyObject is a Python object, not a TensorFlow Tensor, the cast to EagerTensor fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1.

AnalysisAI

In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of dlpack.to_dlpack can be made to use uninitialized memory resulting in further memory corruption. Rated high severity (CVSS 7.1), this vulnerability is remotely exploitable, low attack complexity. Public exploit code available.

Technical ContextAI

This vulnerability is classified as Use of Uninitialized Resource (CWE-908), which allows attackers to access uninitialized memory causing crashes or information disclosure. In Tensorflow before versions 2.2.1 and 2.3.1, the implementation of dlpack.to_dlpack can be made to use uninitialized memory resulting in further memory corruption. This is because the pybind11 glue code assumes that the argument is a tensor. However, there is nothing stopping users from passing in a Python object instead of a tensor. The uninitialized memory address is due to a reinterpret_cast Since the PyObject is a Python object, not a TensorFlow Tensor, the cast to EagerTensor fails. The issue is patched in commit 22e07fb204386768e5bcbea563641ea11f96ceb8 and is released in TensorFlow versions 2.2.1, or 2.3.1. Affected products include: Google Tensorflow, Opensuse Leap.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Initialize all variables, use compiler warnings for uninitialized access, use memory-safe languages.