Common Weakness Enumeration

CWE-125

Allowed

Out-of-bounds Read

Abstraction: Base · Status: Draft

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

11505 vulnerabilities reference this CWE, most recent first.

CVE-2021-41533 (GCVE-0-2021-41533)

Vulnerability from cvelistv5 – Published: 2021-09-28 11:12 – Updated: 2024-08-04 03:15
VLAI
Summary
A vulnerability has been identified in NX 1980 Series (All versions < V1984), Solid Edge SE2021 (All versions < SE2021MP8). The affected application is vulnerable to an out of bounds read past the end of an allocated buffer when parsing JT files. An attacker could leverage this vulnerability to leak information in the context of the current process (ZDI-CAN-13565).
Severity
No CVSS data available.
CWE
Assigner
Impacted products
Vendor Product Version
Siemens NX 1980 Series Affected: All versions < V1984
Create a notification for this product.
Siemens Solid Edge SE2021 Affected: All versions < SE2021MP8
Create a notification for this product.
Show details on NVD website

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CVE-2021-41227 (GCVE-0-2021-41227)

Vulnerability from cvelistv5 – Published: 2021-11-05 22:30 – Updated: 2024-08-04 03:08
VLAI
Title
Arbitrary memory read in `ImmutableConst`
Summary
TensorFlow is an open source platform for machine learning. In affected versions the `ImmutableConst` operation in TensorFlow can be tricked into reading arbitrary memory contents. This is because the `tstring` TensorFlow string class has a special case for memory mapped strings but the operation itself does not offer any support for this datatype. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CWE
Assigner
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.6.0, < 2.6.1
Affected: >= 2.5.0, < 2.5.2
Affected: < 2.4.4
Create a notification for this product.
Show details on NVD website

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CVE-2021-41226 (GCVE-0-2021-41226)

Vulnerability from cvelistv5 – Published: 2021-11-05 20:20 – Updated: 2024-08-04 03:08
VLAI
Title
Heap OOB read in `SparseBinCount`
Summary
TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SparseBinCount` is vulnerable to a heap OOB access. This is because of missing validation between the elements of the `values` argument and the shape of the sparse output. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.6.0, < 2.6.1
Affected: >= 2.5.0, < 2.5.2
Affected: < 2.4.4
Create a notification for this product.
Show details on NVD website

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CVE-2021-41224 (GCVE-0-2021-41224)

Vulnerability from cvelistv5 – Published: 2021-11-05 20:20 – Updated: 2024-08-04 03:08
VLAI
Title
`SparseFillEmptyRows` heap OOB read
Summary
TensorFlow is an open source platform for machine learning. In affected versions the implementation of `SparseFillEmptyRows` can be made to trigger a heap OOB access. This occurs whenever the size of `indices` does not match the size of `values`. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.6.0, < 2.6.1
Affected: >= 2.5.0, < 2.5.2
Affected: < 2.4.4
Create a notification for this product.
Show details on NVD website

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CVE-2021-41223 (GCVE-0-2021-41223)

Vulnerability from cvelistv5 – Published: 2021-11-05 20:20 – Updated: 2024-08-04 03:08
VLAI
Title
Heap OOB read in `FusedBatchNorm` kernels
Summary
TensorFlow is an open source platform for machine learning. In affected versions the implementation of `FusedBatchNorm` kernels is vulnerable to a heap OOB access. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.6.0, < 2.6.1
Affected: >= 2.5.0, < 2.5.2
Affected: < 2.4.4
Create a notification for this product.
Show details on NVD website

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CVE-2021-41212 (GCVE-0-2021-41212)

Vulnerability from cvelistv5 – Published: 2021-11-05 20:15 – Updated: 2024-08-04 03:08
VLAI
Title
Heap OOB read in `tf.ragged.cross`
Summary
TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `tf.ragged.cross` can trigger a read outside of bounds of heap allocated array. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.6.0, < 2.6.1
Affected: >= 2.5.0, < 2.5.2
Affected: < 2.4.4
Create a notification for this product.
Show details on NVD website

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CVE-2021-41211 (GCVE-0-2021-41211)

Vulnerability from cvelistv5 – Published: 2021-11-05 20:15 – Updated: 2024-08-04 03:08
VLAI
Title
Heap OOB read in shape inference for `QuantizeV2`
Summary
TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.6.0, < 2.6.1
Create a notification for this product.
Show details on NVD website

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CVE-2021-41210 (GCVE-0-2021-41210)

Vulnerability from cvelistv5 – Published: 2021-11-05 20:10 – Updated: 2024-08-04 03:08
VLAI
Title
Heap OOB read in `tf.raw_ops.SparseCountSparseOutput`
Summary
TensorFlow is an open source platform for machine learning. In affected versions the shape inference functions for `SparseCountSparseOutput` can trigger a read outside of bounds of heap allocated array. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.6.0, < 2.6.1
Affected: >= 2.5.0, < 2.5.2
Affected: < 2.4.4
Create a notification for this product.
Show details on NVD website

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CVE-2021-41205 (GCVE-0-2021-41205)

Vulnerability from cvelistv5 – Published: 2021-11-05 20:10 – Updated: 2024-08-04 03:08
VLAI
Title
Heap OOB read in all `tf.raw_ops.QuantizeAndDequantizeV*` ops
Summary
TensorFlow is an open source platform for machine learning. In affected versions the shape inference functions for the `QuantizeAndDequantizeV*` operations can trigger a read outside of bounds of heap allocated array. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
CWE
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: >= 2.6.0, < 2.6.1
Affected: >= 2.5.0, < 2.5.2
Affected: < 2.4.4
Create a notification for this product.
Show details on NVD website

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CVE-2021-40795 (GCVE-0-2021-40795)

Vulnerability from cvelistv5 – Published: 2023-09-07 12:54 – Updated: 2025-02-27 21:00
VLAI
Title
Adobe Premiere Pro 3GP File Parsing Out-Of-Bounds Read Remote Code Execution Vulnerability
Summary
Adobe Premiere Pro versions 22.0 (and earlier) and 15.4.2 (and earlier) are affected by an out-of-bounds read vulnerability which could result in a read past the end of an allocated memory structure. An attacker could leverage this vulnerability to execute code in the context of the current user. Exploitation of this issue requires user interaction in that a victim must open a malicious file.
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator (v2.0.3)
CWE
  • CWE-125 - Out-of-bounds Read (CWE-125)
Assigner
References
Impacted products
Vendor Product Version
Adobe Premiere Pro Affected: 0 , ≤ 15.4.2 (semver)
Create a notification for this product.
Date Public
2021-12-14 17:00
Show details on NVD website

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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.