CVE-2020-15213
published 2020-09-25CVE-2020-15213: In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the…
medium4CVSS 3.1
AVNACHPRNUINSCCNINAL
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.
Affected
8 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | >= 2.2.0 < 2.2.1 | 2.2.1 | |
| tensorflow | >= 2.3.0 < 2.3.1 | 2.3.1 | |
| intel | optimization_for_tensorflow | >= 0 < 204945b19e44b57906c9344c0d00120eeeae178a | 204945b19e44b57906c9344c0d00120eeeae178a |
| intel | optimization_for_tensorflow | >= 2.2.0 < 2.2.1 | 2.2.1 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.1 | 2.3.1 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
Debian
CVE-2020-15213: tensorflow - In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can...
vendor_debian·2020·CVSS 4.0
CVE-2020-15213 [MEDIUM] CVE-2020-15213: tensorflow - In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can...
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. Ho
GHSA
Denial of service in tensorflow-lite
ghsa·2020-09-25
CVE-2020-15213 [MEDIUM] CWE-119 Denial of service in tensorflow-lite
Denial of service in tensorflow-lite
### Impact
In TensorFlow Lite models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/segment_sum.cc#L39-L44
### Patches
We have patched the issue in 204945b and will release patch releases for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1, or 2.3.1.
### Workarounds
A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segme
OSV
Denial of service in tensorflow-lite
osv·2020-09-25
CVE-2020-15213 [MEDIUM] Denial of service in tensorflow-lite
Denial of service in tensorflow-lite
### Impact
In TensorFlow Lite models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/lite/kernels/segment_sum.cc#L39-L44
### Patches
We have patched the issue in 204945b and will release patch releases for all affected versions.
We recommend users to upgrade to TensorFlow 2.2.1, or 2.3.1.
### Workarounds
A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segme
OSV
CVE-2020-15213: In TensorFlow Lite before versions 2
osv·2020-09-25
CVE-2020-15213 CVE-2020-15213: In TensorFlow Lite before versions 2
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. Ho
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178ahttps://github.com/tensorflow/tensorflow/releases/tag/v2.3.1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178ahttps://github.com/tensorflow/tensorflow/releases/tag/v2.3.1https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87
2020-09-25
Published