What is the CVSS score of CVE-2020-15210?

CVE-2020-15210 has a CVSS 3.1 base score of 6.5 (Medium). CVSS vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H. EPSS exploitation probability: 0.7%.

Is there a public PoC exploit available for CVE-2020-15210?

Yes, a public proof-of-concept exploit is available for CVE-2020-15210. Prioritise patching immediately. EPSS: 0.7%.

Is there a patch available for CVE-2020-15210?

Yes, a patch is available for CVE-2020-15210. Update the affected software to the latest version immediately.

Tensorflow CVE-2020-15210

MEDIUM

Improper Input Validation (CWE-20)

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

Buffer Overflow Tensorflow Leap

6.5

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

6.5 MEDIUM

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

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

Attack Vector

Network

Attack Complexity

High

Privileges Required

None

User Interaction

None

Scope

Unchanged

Confidentiality

None

Integrity

Low

Availability

High

Lifecycle Timeline

CVE Published

Sep 25, 2020 - 19:15 nvd

MEDIUM 6.5

Blast Radius

ecosystem impact

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

46 pypi packages depend on tensorflow (41 direct, 5 indirect)
11 pypi packages depend on tensorflow-gpu (11 direct, 0 indirect)

Ecosystem-wide dependent count for version 2.0.0 and other introduced versions.

DescriptionNVD

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

AnalysisAI

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can. Rated medium severity (CVSS 6.5), this vulnerability is remotely exploitable, no authentication required. Public exploit code available.

Technical ContextAI

This vulnerability is classified under CWE-20. In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 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. Apply vendor patches when available. Implement network segmentation and monitoring as interim mitigations.