CVE-2020-15205criticalCWE-119CWE-122

CVE-2020-15205: critical vulnerability in tensorflow

Data leak in Tensorflow

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28Vexday Risk Score

No sign of exploitation. No public exploitation artifact known so far.

ssvc Trackcvss 9epss 1.0%
In short

TensorFlow's StringNGrams function doesn't validate user input properly, allowing attackers to read sensitive data from the computer's memory. This can leak information needed to bypass security protections.

Technical detail

The `data_splits` argument in tf.raw_ops.StringNGrams lacks input validation, enabling heap buffer overflow that leaks adjacent memory contents including stack addresses. An attacker can exploit this to extract data for ASLR bypass without requiring elevated privileges.

Summary generated and translated by AI from the 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.
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
Affected products
tensorflow · tensorflow
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