What is the CVSS score of CVE-2020-26271?

CVE-2020-26271 has a CVSS 3.1 base score of 3.3 (Low). CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N. EPSS exploitation probability: 0.2%.

Is there a public PoC exploit available for CVE-2020-26271?

Yes, a public proof-of-concept exploit is available for CVE-2020-26271. Prioritise patching immediately. EPSS: 0.2%.

Is there a patch available for CVE-2020-26271?

Yes, a patch is available for CVE-2020-26271. Update the affected software to the latest version immediately.

Tensorflow CVE-2020-26271

LOW

Out-of-bounds Read (CWE-125)

2020-12-10 security-advisories@github.com

Buffer Overflow Information Disclosure Tensorflow

3.3

CVSS 3.1 · NVD

Severity by source

NVD PRIMARY

3.3 LOW

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

Primary rating from NVD · only source for this CVE.

CVSS VectorNVD

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

Attack Vector

Local

Attack Complexity

Low

Privileges Required

Low

User Interaction

None

Scope

Unchanged

Confidentiality

Low

Integrity

None

Availability

None

Lifecycle Timeline

CVE Published

Dec 10, 2020 - 22:15 nvd

LOW 3.3

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 affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

AnalysisAI

In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. Rated low severity (CVSS 3.3), this vulnerability is 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 affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0. Affected products include: Google Tensorflow.

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.