What is the CVSS score of CVE-2020-15208?

CVE-2020-15208 has a CVSS 3.1 base score of 9.8 (Critical). CVSS vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H. EPSS exploitation probability: 0.9%.

Is there a public PoC exploit available for CVE-2020-15208?

Yes, a public proof-of-concept exploit is available for CVE-2020-15208. Prioritise patching immediately. EPSS: 0.9%.

Is there a patch available for CVE-2020-15208?

Yes, a patch is available for CVE-2020-15208. Update the affected software to the latest version immediately.

Leap CVE-2020-15208

CRITICAL

Out-of-bounds Read (CWE-125)

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

Buffer Overflow Information Disclosure Google Leap Tensorflow Opensuse

9.8

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

9.8 CRITICAL

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

None

Scope

Unchanged

Confidentiality

High

Integrity

High

Availability

High

Lifecycle Timeline

CVE Published

Sep 25, 2020 - 19:15 nvd

CRITICAL 9.8

Blast Radius

ecosystem impact

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

43 pypi packages depend on tensorflow (38 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, when determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 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, when determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation. Rated critical severity (CVSS 9.8), this vulnerability is remotely exploitable, no authentication required, low attack complexity. Public exploit code available.

Technical ContextAI

This vulnerability is classified as Out-of-bounds Read (CWE-125), which allows attackers to read data from memory outside the intended buffer boundaries. In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 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. Validate array indices and buffer lengths. Use memory-safe languages. Enable AddressSanitizer during testing.