CVE-2020-15205 Data leak in Tensorflow
Attackers can leak memory contents via heap overflow in StringNGrams, potentially defeating ASLR in TensorFlow applications.
- Exploited in the wild
- Not known
- Login needed
- Not needed
- Attackable
- Over the internet
- Victim action needed
- Not needed
- Fix
- Available
What is CVE-2020-15205?
CVE-2020-15205 is a critical vulnerability in Google Tensorflow, published on 25 Sep 2020. An attacker can exploit it over the internet without logging in, with no action from the victim.
Official description
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `data_splits` argument of `tf.raw_ops.StringNGrams` lacks validation. This allows a user to pass values that can cause heap overflow errors and even leak contents of memory In the linked code snippet, all the binary strings after `ee ff` are contents from the memory stack. Since these can contain return addresses, this data leak can be used to defeat ASLR. The issue is patched in commit 0462de5b544ed4731aa2fb23946ac22c01856b80, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
Which versions are affected by CVE-2020-15205?
34 open source packages ship an affected version, including tensorflow, tensorflow-cpu and tensorflow-gpu. It affects 2 products.
| Package | Affected | Fixed in |
|---|---|---|
tensorflow Bitnami | All versions | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 |
tensorflow PyPI | All versions | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 |
tensorflow PyPI | All versions | 1.15.4 |
tensorflow PyPI | All versions | 1.15.4 |
tensorflow PyPI | From 2.0.0 | 2.0.3 |
tensorflow PyPI | From 2.0.0 | 2.0.3 |
28 more packages
tensorflow PyPI | From 2.1.0 | 2.1.2 |
tensorflow PyPI | From 2.1.0 | 2.1.2 |
tensorflow PyPI | From 2.2.0 | 2.2.1 |
tensorflow PyPI | From 2.2.0 | 2.2.1 |
tensorflow PyPI | From 2.3.0 | 2.3.1 |
tensorflow PyPI | From 2.3.0 | 2.3.1 |
tensorflow-cpu PyPI | All versions | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 |
tensorflow-cpu PyPI | All versions | 1.15.4 |
tensorflow-cpu PyPI | All versions | 1.15.4 |
tensorflow-cpu PyPI | From 2.0.0 | 2.0.3 |
tensorflow-cpu PyPI | From 2.0.0 | 2.0.3 |
tensorflow-cpu PyPI | From 2.1.0 | 2.1.2 |
tensorflow-cpu PyPI | From 2.1.0 | 2.1.2 |
tensorflow-cpu PyPI | From 2.2.0 | 2.2.1 |
tensorflow-cpu PyPI | From 2.2.0 | 2.2.1 |
tensorflow-cpu PyPI | From 2.3.0 | 2.3.1 |
tensorflow-cpu PyPI | From 2.3.0 | 2.3.1 |
tensorflow-gpu PyPI | All versions | 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 |
tensorflow-gpu PyPI | All versions | 1.15.4 |
tensorflow-gpu PyPI | All versions | 1.15.4 |
tensorflow-gpu PyPI | From 2.0.0 | 2.0.3 |
tensorflow-gpu PyPI | From 2.0.0 | 2.0.3 |
tensorflow-gpu PyPI | From 2.1.0 | 2.1.2 |
tensorflow-gpu PyPI | From 2.1.0 | 2.1.2 |
tensorflow-gpu PyPI | From 2.2.0 | 2.2.1 |
tensorflow-gpu PyPI | From 2.2.0 | 2.2.1 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.1 |
tensorflow-gpu PyPI | From 2.3.0 | 2.3.1 |
Products include Google Tensorflow, Opensuse Leap.
How do I fix CVE-2020-15205?
Upgrade tensorflow to a fixed version for your release line: 1.15.4, 2.0.3, 2.1.2 or 2.2.1.
Is CVE-2020-15205 being exploited?
There is no known exploitation of CVE-2020-15205 in the wild and no public exploit code.
Other vulnerabilities in Google Tensorflow
- CVE-2023-25668 TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation
- CVE-2018-7575 Integer Overflow or Wraparound in Google TensorFlow
- CVE-2021-37678 Arbitrary code execution due to YAML deserialization
- CVE-2021-35958 Path traversal in n/a
- CVE-2020-15202 Integer truncation in Shard API usage
Sources
Also known as BIT-tensorflow-2020-15205, GHSA-g7p5-5759-qv46, PYSEC-2020-128, PYSEC-2020-285, PYSEC-2020-320.