Common Weakness Enumeration

CWE-125

Allowed

Out-of-bounds Read

Abstraction: Base · Status: Draft

API response cwe.mitre.org

The product reads data past the end, or before the beginning, of the intended buffer.

11362 vulnerabilities reference this CWE, most recent first.

CVE-2022-42254 (GCVE-0-2022-42254)

Vulnerability from cvelistv5 – Published: 2022-12-30 00:00 – Updated: 2025-04-10 19:49
VLAI
Summary
NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer (nvidia.ko), where an out-of-bounds array access may lead to denial of service, data tampering, or information disclosure.
Severity
5.3 (Medium)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
NVIDIA vGPU software (guest driver) - Linux, vGPU software (Virtual GPU Manager), NVIDIA Cloud Gaming (guest driver), NVIDIA Cloud Gaming (Virtual GPU Manager) Affected: All versions prior to and including 14.2, 13.4, and 11.9, and all versions prior to the November 2022 release
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CVE-2022-41988 (GCVE-0-2022-41988)

Vulnerability from cvelistv5 – Published: 2022-12-23 23:03 – Updated: 2025-04-14 19:11
VLAI
Summary
An information disclosure vulnerability exists in the OpenImageIO::decode_iptc_iim() functionality of OpenImageIO Project OpenImageIO v2.3.19.0. A specially-crafted TIFF file can lead to a disclosure of sensitive information. An attacker can provide a malicious file to trigger this vulnerability.
Severity
5.3 (Medium)
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Show details on NVD website
To clipboard 

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CVE-2022-41977 (GCVE-0-2022-41977)

Vulnerability from cvelistv5 – Published: 2022-12-23 23:03 – Updated: 2025-04-14 19:12
VLAI
Summary
An out of bounds read vulnerability exists in the way OpenImageIO version v2.3.19.0 processes string fields in TIFF image files. A specially-crafted TIFF file can lead to information disclosure. An attacker can provide a malicious file to trigger this vulnerability.
Severity
5.3 (Medium)
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N
SSVC
Exploitation: poc Automatable: yes Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
OpenImageIO Project OpenImageIO Affected: master-branch-9aeece7a
Affected: v2.3.19.0
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CVE-2022-41910 (GCVE-0-2022-41910)

Vulnerability from cvelistv5 – Published: 2022-12-06 00:00 – Updated: 2025-04-23 16:32
VLAI
Title
Heap out of bounds read in `QuantizeAndDequantizeV2` in Tensorflow
Summary
TensorFlow is an open source platform for machine learning. The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered. We have patched the issue in GitHub commit a65411a1d69edfb16b25907ffb8f73556ce36bb7. The fix will be included in TensorFlow 2.11.0. We will also cherrypick this commit on TensorFlow 2.8.4, 2.9.3, and 2.10.1.
Severity
4.8 (Medium)
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.10.0, < 2.10.1
Affected: >= 2.9.0, < 2.9.3
Affected: < 2.8.4
Create a notification for this product.
Show details on NVD website
To clipboard 

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CVE-2022-41900 (GCVE-0-2022-41900)

Vulnerability from cvelistv5 – Published: 2022-11-18 00:00 – Updated: 2025-04-22 16:03
VLAI
Title
FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow
Summary
TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.
Severity
7.1 (High)
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
SSVC
Exploitation: poc Automatable: no Technical Impact: total
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.10.0, < 2.10.1
Affected: >= 2.9.0, < 2.9.3
Affected: < 2.8.4
Create a notification for this product.
Show details on NVD website
To clipboard 

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CVE-2022-41897 (GCVE-0-2022-41897)

Vulnerability from cvelistv5 – Published: 2022-11-18 00:00 – Updated: 2025-04-22 16:04
VLAI
Title
`FractionalMaxPoolGrad` Heap out of bounds read in Tensorflow
Summary
TensorFlow is an open source platform for machine learning. If `FractionMaxPoolGrad` is given outsize inputs `row_pooling_sequence` and `col_pooling_sequence`, TensorFlow will crash. We have patched the issue in GitHub commit d71090c3e5ca325bdf4b02eb236cfb3ee823e927. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Severity
4.8 (Medium)
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.10.0, < 2.10.1
Affected: >= 2.9.0, < 2.9.3
Affected: < 2.8.4
Create a notification for this product.
Show details on NVD website
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CVE-2022-41895 (GCVE-0-2022-41895)

Vulnerability from cvelistv5 – Published: 2022-11-18 00:00 – Updated: 2025-04-22 16:04
VLAI
Title
`MirrorPadGrad` heap out of bounds read in Tensorflow
Summary
TensorFlow is an open source platform for machine learning. If `MirrorPadGrad` is given outsize input `paddings`, TensorFlow will give a heap OOB error. We have patched the issue in GitHub commit 717ca98d8c3bba348ff62281fdf38dcb5ea1ec92. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Severity
4.8 (Medium)
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.10.0, < 2.10.1
Affected: >= 2.9.0, < 2.9.3
Affected: < 2.8.4
Create a notification for this product.
Show details on NVD website
To clipboard 

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CVE-2022-41883 (GCVE-0-2022-41883)

Vulnerability from cvelistv5 – Published: 2022-11-18 00:00 – Updated: 2025-04-22 16:07
VLAI
Title
Out of bounds segmentation fault due to unequal op inputs in Tensorflow
Summary
TensorFlow is an open source platform for machine learning. When ops that have specified input sizes receive a differing number of inputs, the executor will crash. We have patched the issue in GitHub commit f5381e0e10b5a61344109c1b7c174c68110f7629. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Severity
6.8 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.10.0, < 2.10.1
Create a notification for this product.
Show details on NVD website
To clipboard 

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CVE-2022-41880 (GCVE-0-2022-41880)

Vulnerability from cvelistv5 – Published: 2022-11-18 00:00 – Updated: 2025-04-22 16:07
VLAI
Title
ThreadUnsafeUnigramCandidateSampler Heap out of bounds in Tensorflow
Summary
TensorFlow is an open source platform for machine learning. When the `BaseCandidateSamplerOp` function receives a value in `true_classes` larger than `range_max`, a heap oob read occurs. We have patched the issue in GitHub commit b389f5c944cadfdfe599b3f1e4026e036f30d2d4. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Severity
6.8 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:L/I:L/A:H
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.10.0, < 2.10.1
Affected: >= 2.9.0, < 2.9.3
Affected: < 2.8.4
Create a notification for this product.
Show details on NVD website
To clipboard 

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CVE-2022-41873 (GCVE-0-2022-41873)

Vulnerability from cvelistv5 – Published: 2022-11-11 00:00 – Updated: 2025-04-23 16:38
VLAI
Title
Out-of-bounds read and write in BLE L2CAP module
Summary
Contiki-NG is an open-source, cross-platform operating system for Next-Generation IoT devices. Versions prior to 4.9 are vulnerable to an Out-of-bounds read. While processing the L2CAP protocol, the Bluetooth Low Energy stack of Contiki-NG needs to map an incoming channel ID to its metadata structure. While looking up the corresponding channel structure in get_channel_for_cid (in os/net/mac/ble/ble-l2cap.c), a bounds check is performed on the incoming channel ID, which is meant to ensure that the channel ID does not exceed the maximum number of supported channels.However, an integer truncation issue leads to only the lowest byte of the channel ID to be checked, which leads to an incomplete out-of-bounds check. A crafted channel ID leads to out-of-bounds memory to be read and written with attacker-controlled data. The vulnerability has been patched in the "develop" branch of Contiki-NG, and will be included in release 4.9. As a workaround, Users can apply the patch in Contiki-NG pull request 2081 on GitHub.
Severity
4.2 (Medium)
CVSS:3.1/AV:A/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
Assigner
References
Impacted products
Vendor Product Version
contiki-ng contiki-ng Affected: < 4.9
Create a notification for this product.
Show details on NVD website
To clipboard 

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Mitigation MIT-5
Implementation

Strategy: Input Validation

  • Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does.
  • When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue."
  • Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
  • To reduce the likelihood of introducing an out-of-bounds read, ensure that you validate and ensure correct calculations for any length argument, buffer size calculation, or offset. Be especially careful of relying on a sentinel (i.e. special character such as NUL) in untrusted inputs.
Mitigation
Architecture and Design

Strategy: Language Selection

Use a language that provides appropriate memory abstractions.

CAPEC-540: Overread Buffers

An adversary attacks a target by providing input that causes an application to read beyond the boundary of a defined buffer. This typically occurs when a value influencing where to start or stop reading is set to reflect positions outside of the valid memory location of the buffer. This type of attack may result in exposure of sensitive information, a system crash, or arbitrary code execution.

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