// For flags

CVE-2021-29521

Segfault in SparseCountSparseOutput

Severity Score

5.5
*CVSS v3.1

Exploit Likelihood

*EPSS

Affected Versions

*CPE

Public Exploits

1
*Multiple Sources

Exploited in Wild

-
*KEV

Decision

-
*SSVC
Descriptions

TensorFlow is an end-to-end open source platform for machine learning. Specifying a negative dense shape in `tf.raw_ops.SparseCountSparseOutput` results in a segmentation fault being thrown out from the standard library as `std::vector` invariants are broken. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) assumes the first element of the dense shape is always positive and uses it to initialize a `BatchedMap<T>` (i.e., `std::vector<absl::flat_hash_map<int64,T>>`(https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) data structure. If the `shape` tensor has more than one element, `num_batches` is the first value in `shape`. Ensuring that the `dense_shape` argument is a valid tensor shape (that is, all elements are non-negative) solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3.

TensorFlow es una plataforma de código abierto de extremo a extremo para el aprendizaje automático.&#xa0;Especificar una forma densa negativa en "tf.raw_ops.SparseCountSparseOutput" resulta en un error de segmentación que es eliminado de la biblioteca estándar ya que los invariantes "std::vector" son rotos.&#xa0;Esto es debido a que la implementación (https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L199-L213) asume que el primer elemento de la forma densa es siempre positivo y lo usa para inicializar un "BatchedMap(T)" (es decir, "std::vector (absl::flat_hash_map(int64, T))" (https://github.com/tensorflow/tensorflow/blob/8f7b60ee8c0206a2c99802e3a4d1bb55d2bc0624/tensorflow/core/kernels/count_ops.cc#L27)) estructura de datos.&#xa0;Si el tensor de "shape" presenta más de un elemento,"num_batches" es el primer valor en "shape".&#xa0;Asegurarse de que el argumento "dense_shape" sea una forma de tensor válida (es decir, que todos los elementos no sean negativos) resuelve este problema.&#xa0;La corrección será incluida en TensorFlow versión 2.5.0.&#xa0;También seleccionaremos este commit en TensorFlow versión 2.4.2 y TensorFlow versión 2.3.3

*Credits: N/A
CVSS Scores
Attack Vector
Local
Attack Complexity
Low
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High
Attack Vector
Local
Attack Complexity
High
Privileges Required
Low
User Interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
Low
Attack Vector
Local
Attack Complexity
Low
Authentication
None
Confidentiality
None
Integrity
None
Availability
Partial
* Common Vulnerability Scoring System
SSVC
  • Decision:-
Exploitation
-
Automatable
-
Tech. Impact
-
* Organization's Worst-case Scenario
Timeline
  • 2021-03-30 CVE Reserved
  • 2021-05-14 CVE Published
  • 2023-03-08 EPSS Updated
  • 2024-08-03 CVE Updated
  • 2024-08-03 First Exploit
  • ---------- Exploited in Wild
  • ---------- KEV Due Date
CWE
  • CWE-131: Incorrect Calculation of Buffer Size
CAPEC
Affected Vendors, Products, and Versions
Vendor Product Version Other Status
Vendor Product Version Other Status <-- --> Vendor Product Version Other Status
Google
Search vendor "Google"
 Tensorflow
Search vendor "Google" for product "Tensorflow"
 >= 2.3.0 < 2.3.3
Search vendor "Google" for product "Tensorflow" and version " >= 2.3.0 < 2.3.3"
-
Affected
Google
Search vendor "Google"
 Tensorflow
Search vendor "Google" for product "Tensorflow"
 >= 2.4.0 < 2.4.2
Search vendor "Google" for product "Tensorflow" and version " >= 2.4.0 < 2.4.2"
-
Affected