GitHub_MCVE-2021-37679CVE-2021-37679
CVSS2
Attack Vector
LOCAL
Attack Complexity
LOW
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:P/I:P/A:P
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
HIGH
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
AI Score
Confidence
High
EPSS
Percentile
12.6%
TensorFlow is an end-to-end open source platform for machine learning. In affected versions it is possible to nest a tf.map_fn within another tf.map_fn call. However, if the input tensor is a RaggedTensor and there is no function signature provided, code assumes the output is a fully specified tensor and fills output buffer with uninitialized contents from the heap. The t and z outputs should be identical, however this is not the case. The last row of t contains data from the heap which can be used to leak other memory information. The bug lies in the conversion from a Variant tensor to a RaggedTensor. The implementation does not check that all inner shapes match and this results in the additional dimensions. The same implementation can result in data loss, if input tensor is tweaked. We have patched the issue in GitHub commit 4e2565483d0ffcadc719bd44893fb7f609bb5f12. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Affected configurations
| Vendor | Product | Version | CPE |
|---|---|---|---|
| tensorflow | * | cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* | |
| tensorflow | 2.5.0 | cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:* | |
| tensorflow | 2.6.0 | cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:* | |
| tensorflow | 2.6.0 | cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:* | |
| tensorflow | 2.6.0 | cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:* |
CNA Affected
[
{
"product": "tensorflow",
"vendor": "tensorflow",
"versions": [
{
"status": "affected",
"version": ">= 2.5.0, < 2.5.1"
},
{
"status": "affected",
"version": ">= 2.4.0, < 2.4.3"
},
{
"status": "affected",
"version": "< 2.3.4"
}
]
}
]Related
CVSS2
Attack Vector
LOCAL
Attack Complexity
LOW
Authentication
NONE
Confidentiality Impact
PARTIAL
Integrity Impact
PARTIAL
Availability Impact
PARTIAL
AV:L/AC:L/Au:N/C:P/I:P/A:P
CVSS3
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
HIGH
Integrity Impact
HIGH
Availability Impact
HIGH
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
AI Score
Confidence
High
EPSS
Percentile
12.6%