CVE-2022-23593

mediumPriorität · verfolgen · 30EPSS 0.009 · 59. PerzentilEUUS
grimoire priorityP3 · Track
Exploitable?
—
no known exploitation
Likely / severe?
0.87% (59th) EPSS
CVSS 5 · medium
Is it mine?
8 products
Prüfe deine Angriffsfläche
Who says so?
4 sources
cnnvd · enisa_euvd · osv · nvd

EPSS · bewertet 2026-10-27

Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version.

01

cvss

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

7.5
010

Basiswert 0–10 · höher = schwerwiegender · Vektor überfahren zum Auflösen⚠ Quellen uneinig · medium–high · 5–7.5

v2.05mediumAV:N/AC:L/Au:N/C:N/I:N/A:Pprimary · NVD / NIST USAusnutzbarkeit 10 · Auswirkung 2.9
v3.17.5highCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:Hprimary · NVD / NIST USAusnutzbarkeit 3.9 · 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
v3.16.9mediumCVSS:3.1/AV:N/AC:L/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 (8)

Betroffene Produkte und Versionsbereiche.

04

Advisories (5)

Hersteller- und Ökosystem-Meldungen dazu.

  • GHSA-gwcx-jrx4-92w2Segfault in `simplifyBroadcast` in Tensorflow2022-02-09ghsa · osvUS

    ### Impact The [`simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow](https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205) is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. ```cc size_t maxRank = 0; for (auto shape : llvm::enumerate(shapes)) { auto found_shape = analysis.dimensionsForShapeTensor(shape.value()); if (!found_shape) return {}; shapes_found.push_back(*found_shape); maxRank = std::max(maxRank, found_shape->size()); } SmallVector<const ShapeComponentAnalysis::SymbolicDimension*> joined_dimensions(maxRank); ``` If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. ### Patches We have patched the issue in GitHub commit [35f0fabb4c178253a964d7aabdbb15c6a398b69a](https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a). The fix will be included in TensorFlow 2.8.0. This is the only affected version. ### 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.

  • BIT-tensorflow-2022-23593Segfault in `simplifyBroadcast` in Tensorflow2024-03-06vendor · osvUS

    Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version.

  • PYSEC-2022-1022022-02-04vendor · osvUS

    Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version.

  • PYSEC-2022-1572022-02-04vendor · osvUS

    Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version.

  • PYSEC-2026-3193Segfault in `simplifyBroadcast` in Tensorflow2026-07-09vendor · osvUS

    ### Impact The [`simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow](https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205) is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. ```cc size_t maxRank = 0; for (auto shape : llvm::enumerate(shapes)) { auto found_shape = analysis.dimensionsForShapeTensor(shape.value()); if (!found_shape) return {}; shapes_found.push_back(*found_shape); maxRank = std::max(maxRank, found_shape->size()); } SmallVector<const ShapeComponentAnalysis::SymbolicDimension*> joined_dimensions(maxRank); ``` If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. ### Patches We have patched the issue in GitHub commit [35f0fabb4c178253a964d7aabdbb15c6a398b69a](https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a). The fix will be included in TensorFlow 2.8.0. This is the only affected version. ### 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.

05

auch bekannt als (11)

Weitere Namen und Kennungen dieser Entität.

06

quellen

Welche Quellen diesen Datensatz belegen und wann.

veröffentlicht 2022-02-04geändert 2026-06-17
08

Referenzen (10)

Externe Belege — Patches, Meldungen, Analysen.

scry

Angreifer nutzen Schwachstellen wie diese gegen im Internet exponierte Dienste aus. Sehen Sie mit einem kostenlosen Passiv-Scan, was exponiert ist.

Kostenloser Scan