Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Test your applicationsUpgrade tensorflow
to version 2.12.0rc1 or higher.
tensorflow is a machine learning framework.
Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip) via a crafted archive when tf.keras.utils.get_file
is used with extract=True
.
NOTE: This CVE is disputed as the vendor's position is that tf.keras.utils.get_file
is not intended for untrusted archives. However, we feel this advisory is relevant as at the time of publication, there is no known security notice or documentation warning users of this behavior.
UPDATE: With the addition of a clear warning to the API documentation on Feb 23, 2023, this issue is considered fixed.
It is exploited using a specially crafted zip archive, that holds path traversal filenames. When exploited, a filename in a malicious archive is concatenated to the target extraction directory, which results in the final path ending up outside of the target folder. For instance, a zip may hold a file with a "../../file.exe" location and thus break out of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.
The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicous file will result in traversing out of the target folder, ending up in /root/.ssh/
overwriting the authorized_keys
file:
+2018-04-15 22:04:29 ..... 19 19 good.txt
+2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys