CVE-2020-15200

mediumPriorität · verfolgen · 24EPSS 0.009 · 58. PerzentilEUUS
grimoire priorityP3 · Track
Exploitable?
—
no known exploitation
Likely / severe?
0.85% (58th) EPSS
CVSS 4.3 · medium
Is it mine?
9 products
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Who says so?
4 sources
cnnvd · enisa_euvd · osv · nvd

EPSS · bewertet 2026-10-27

In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

01

cvss

Technischer Schweregrad, 0–10. Eine Zeile je Quelle.

5.9
010

Basiswert 0–10 · höher = schwerwiegender · Vektor überfahren zum Auflösen

v2.04.3mediumAV:N/AC:M/Au:N/C:N/I:N/A:Pprimary · NVD / NIST USAusnutzbarkeit 8.6 · Auswirkung 2.9
v3.15.9mediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:Hprimary · NVD / NIST USAusnutzbarkeit 2.2 · Auswirkung 3.6
v3.15.9mediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:Hsecondary · ENISA EU
v3.15.9mediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:Hsecondary · security-advisories@github.comAusnutzbarkeit 2.2 · Auswirkung 3.6
v3.15.9mediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:Hsecondary · OSV
v3.15.4mediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H/E:Usecondary · CVSS-BT (t0sche)
02

schwächen

Die CWE-Schwächeklassen, zu denen dies gehört.

03

betroffene Produkte (9)

Betroffene Produkte und Versionsbereiche.

04

Advisories (5)

Hersteller- und Ökosystem-Meldungen dazu.

  • GHSA-x7rp-74x2-mjf3Segfault in Tensorflow2020-09-25ghsa · osvUS

    ### Impact The `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the [following code](https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L248-L265 ) sets up conditions to cause a heap buffer overflow: ```cc auto per_batch_counts = BatchedMap<W>(num_batches); int batch_idx = 0; for (int idx = 0; idx < num_values; ++idx) { while (idx >= splits_values(batch_idx)) { batch_idx++; } const auto& value = values_values(idx); if (value >= 0 && (maxlength_ <= 0 || value < maxlength_)) { per_batch_counts[batch_idx - 1][value] = 1; } } ``` A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. ### Patches We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release. We recommend users to upgrade to TensorFlow 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability is a variant of [GHSA-p5f8-gfw5-33w4](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4)

  • BIT-tensorflow-2020-15200Segfault in Tensorflow2024-03-06vendor · osvUS

    In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

  • PYSEC-2020-1232020-09-25vendor · osvUS

    In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

  • PYSEC-2020-2802020-09-25vendor · osvUS

    In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

  • PYSEC-2020-3152020-09-25vendor · osvUS

    In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Thus, the code sets up conditions to cause a heap buffer overflow. A `BatchedMap` is equivalent to a vector where each element is a hashmap. However, if the first element of `splits_values` is not 0, `batch_idx` will never be 1, hence there will be no hashmap at index 0 in `per_batch_counts`. Trying to access that in the user code results in a segmentation fault. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

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veröffentlicht 2020-09-25geändert 2026-06-17
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