Security Bulletin: Numerous CVE entires for TensorFlow in Watson Machine Learning Community Edition

Summary

An collection of CVE’s have been published for TensorFlow. Details of each are listed.

Vulnerability Details

CVEID:CVE-2020-15206
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by a flaw when changing the SavedModel protocol buffer and altering the name of required keys. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause segmentation fault and data corruption.
CVSS Base score: 9
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188945 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H)

CVEID:CVE-2020-15202
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by an integer truncation in Shard API. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a segmentation fault, read or write outside of heap allocated arrays, stack overflows, or data corruption.
CVSS Base score: 9
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188941 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H)

CVEID:CVE-2020-15199
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by improper input validation in the RaggedCountSparseOutput function. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 5.9
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188938 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:CVE-2020-15214
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by an out-of-bounds write flaw in the TFLite implementation of segment sum. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition and memory corruption.
CVSS Base score: 8.1
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188973 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:H)

CVEID:CVE-2020-15194
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by improper input validation by the SparseFillEmptyRowsGrad implementation. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 5.3
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188923 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:CVE-2020-15210
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by a segmentation fault and data corruption flaw when using an invalid TFLite model. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 6.5
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188969 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H)

CVEID:CVE-2020-15197
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by improper input validation by the SparseCountSparseOutput implementation. By sending a specially-crafted request, a remote authenticated attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 6.3
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188926 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H)

CVEID:CVE-2020-15213
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by an out of memory allocation in the TFLite implementation of segment sum. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 4
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188972 for the current score.
CVSS Vector: (CVSS:3.0/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:CVE-2020-15193
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by a memory corruption in the implementation of dlpack.to_dlpack. By sending a specially-crafted request, a remote authenticated attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 7.1
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188922 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:L)

CVEID:CVE-2020-15209
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by a NULL pointer dereference flaw in TFLite. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 5.9
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188960 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:CVE-2020-15205
**DESCRIPTION:**TensorFlow could allow a remote attacker to obtain sensitive information, caused by a heap-based buffer overflow in the data_splits argument of tf.raw_ops.StringNGrams. By sending a specially-crafted request, an attacker could exploit this vulnerability to obtain contents of the memory, and use this information to launch further attacks against the affected system.
CVSS Base score: 9
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188944 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H)

CVEID:CVE-2020-15201
**DESCRIPTION:**TensorFlow is vulnerable to a heap-based buffer overflow, caused by improper bounds checking by the RaggedCountSparseOutput implementation . By sending a specially-crafted request, a remote attacker could overflow a buffer and execute arbitrary code on the system.
CVSS Base score: 4.8
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188940 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N)

CVEID:CVE-2020-15204
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by a NULL pointer dereference flaw when calling tf.raw_ops.GetSessionHandle or tf.raw_ops.GetSessionHandleV2 functions in eager mode. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 5.3
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188943 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:CVE-2020-15200
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by a improper input validation by the RaggedCountSparseOutput implementation. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 5.9
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188939 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H)

CVEID:CVE-2020-15196
**DESCRIPTION:**TensorFlow is vulnerable to a heap-based buffer overflow, caused by improper bounds checking by the SparseCountSparseOutput and RaggedCountSparseOutput implementations implementations. By sending a specially-crafted request, a remote authenticated attacker could overflow a buffer and execute arbitrary code on the system.
CVSS Base score: 8.5
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188925 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H)

CVEID:CVE-2020-15212
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by an out-of-bounds access flaw in the TFLite implementation of segment sum. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a segmentation fault and memory corruption.
CVSS Base score: 8.1
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188971 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:H)

CVEID:CVE-2020-15192
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by a memory leak when passing a list of strings to dlpack.to_dlpack. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 5.3
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188921 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:CVE-2020-15208
**DESCRIPTION:**TensorFlow could allow a remote attacker to bypass security restrictions, caused by a data corruption flaw when a dimension mismatch occurs in TFLite. By sending a specially-crafted request, an attacker could exploit this vulnerability to read and write outside of bounds of memory.
CVSS Base score: 7.4
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188959 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N)

CVEID:CVE-2020-15195
**DESCRIPTION:**TensorFlow is vulnerable to a heap-based buffer overflow, caused by improper bounds checking by the SparseFillEmptyRowsGrad implementation. By sending a specially-crafted request, a remote authenticated attacker could overflow a buffer and execute arbitrary code on the system.
CVSS Base score: 8.5
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188924 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H)

CVEID:CVE-2020-15211
**DESCRIPTION:**TensorFlow could allow a remote attacker to bypass security restrictions, caused by an out-of-bounds access flaw in the TFLite operators. By sending a specially-crafted request, an attacker could exploit this vulnerability to read and write from outside the bounds of heap allocated arrays.
CVSS Base score: 4.8
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188970 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N)

CVEID:CVE-2020-15191
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by improper input validation by the dlpack.to_dlpack function. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 5.3
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188920 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L)

CVEID:CVE-2020-15207
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by a segmentation fault data corruption flaw when using negative indexing in TFLite. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 8.7
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188958 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:H/A:H)

CVEID:CVE-2020-15203
**DESCRIPTION:**TensorFlow is vulnerable to a denial of service, caused by improper input validation by the fill argument in tf.strings.as_string. By sending a specially-crafted request, a remote attacker could exploit this vulnerability to cause a denial of service condition.
CVSS Base score: 7.5
CVSS Temporal Score: See: https://exchange.xforce.ibmcloud.com/vulnerabilities/188942 for the current score.
CVSS Vector: (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

Affected Products and Versions

Remediation/Fixes

An ifix has been delivered for WML CE 1.6.2 and 1.7.0 that includes an updated package set. Obtaining the latest packages from the WML CE channel will ensure that you have the ifix installed.

Installing Tensorflow from WML CE 1.6.2 with ifix from scratch:

As noted, the latest package versions available contain the fixes, so new installations or new conda environments will automatically install the patched versions. Conda strict channel priority is recommended when using WML CE. This example is for Python 3.6, for other versions adjust the version listed.

$ cat .condarc
channels:
  - <https://public.dhe.ibm.com/ibmdl/export/pub/software/server/ibm-ai/conda>
  - defaults
channel_priority: strict



conda create -n my_env python=3.6
conda activate my_env
conda install powerai=1.6.2

or

conda create -n my_env python=3.6
conda activate my_env
conda install tensorflow-gpu=1.15.4

Installing Tensorflow from WML CE 1.7.0 with ifix from scratch:

As noted, the latest package versions available contain the fixes, so new installations or new conda environments will automatically install the patched versions. Conda strict channel priority is recommended when using WML CE. This example is for Python 3.6. For other python versions, adjust the version listed.

$ cat .condarc
channels:
  - <https://public.dhe.ibm.com/ibmdl/export/pub/software/server/ibm-ai/conda>
  - defaults
channel_priority: strict



conda create -n my_env python=3.6
conda activate my_env
conda install powerai=1.7.0

or

conda create -n my_env python=3.6
conda activate my_env
conda install tensorflow-gpu=2.1.2

Updating an existing WML CE installation:

It is recommended that you keep packages up to date. To update all packages to the latest versions, run:

conda update --all --prune

To update individual packages, use the package name:

conda update tensorflow-gpu  
or  
conda install tensorflow-gpu=1.15.4

For WML CE 1.7.0:

conda update tensorflow-gpu  
or  
conda install tensorflow-gpu=2.1.2

Workarounds and Mitigations

None