What is the CVSS score of CVE-2020-15198?

CVE-2020-15198 has a CVSS 3.1 base score of 5.4 (Medium). CVSS vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N. EPSS exploitation probability: 0.5%.

Is there a public PoC exploit available for CVE-2020-15198?

Yes, a public proof-of-concept exploit is available for CVE-2020-15198. Prioritise patching immediately. EPSS: 0.5%.

Is there a patch available for CVE-2020-15198?

Yes, a patch is available for CVE-2020-15198. Update the affected software to the latest version immediately.

Tensorflow CVE-2020-15198

Q: Which versions of Tensorflow are affected by CVE-2020-15198?

In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor.. A patch is available.

MEDIUM

Buffer Overflow (CWE-119)

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

Buffer Overflow Tensorflow

5.4

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

5.4 MEDIUM

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

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

Attack Vector

Network

Attack Complexity

High

Privileges Required

None

User Interaction

None

Scope

Changed

Confidentiality

Low

Integrity

Low

Availability

None

Lifecycle Timeline

CVE Published

Sep 25, 2020 - 19:15 nvd

MEDIUM 5.4

Blast Radius

ecosystem impact

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

50 pypi packages depend on tensorflow (49 direct, 1 indirect)
1 pypi packages depend on tensorflow-gpu (1 direct, 0 indirect)

Ecosystem-wide dependent count for version 2.3.1 and other introduced versions.

DescriptionNVD

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

AnalysisAI

In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. Rated medium severity (CVSS 5.4), this vulnerability is remotely exploitable, no authentication required. Public exploit code available.

Technical ContextAI

This vulnerability is classified as Buffer Overflow (CWE-119), which allows attackers to corrupt memory to execute arbitrary code or crash the application. In Tensorflow before version 2.3.1, the SparseCountSparseOutput implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the indices tensor has the same shape as the values one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1. Affected products include: Google Tensorflow. Version information: version 2.3.1.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Use memory-safe languages or bounds-checking. Enable ASLR, DEP/NX, stack canaries. Use safe string functions.