Process crash via negative FFT length
Published May 20, 2022 · Updated Apr 22, 2025
Improper input validation in Google TensorFlow signal FFT operations allows local users to crash the hosting process with crafted input. FFTBase copies each fft_length element into fft_shape without rejecting negative values, allowing downstream allocation checks to abort execution. A local user must cause an application to invoke rfft2d or rfft3d with a negative FFT length; the bounded consequence is termination of that process.
Summary
What happened
Improper input validation in Google TensorFlow signal FFT operations allows local users to crash the hosting process with crafted input. FFTBase copies each fft_length element into fft_shape without rejecting negative values, allowing downstream allocation checks to abort execution. A local user must cause an application to invoke rfft2d or rfft3d with a negative FFT length; the bounded consequence is termination of that process.
The record
- CVE
- CVE-2022-29213
- Published
- May 20, 2022
- Updated
- Apr 22, 2025
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-20, CWE-617, T1499.004
- Attack vector
- local
- Privileges
- authenticated
Timeline
How it unfolded
- May 20, 2022CVE publishedPublication date reported by the CVE source.
- Apr 22, 2025Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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Is a vulnerable build present?
Compare these published version ranges with your installed build and any vendor patches.
- Affected versionversion=< 2.6.4
- Affected versionversion=>= 2.7.0rc0, < 2.7.2
- Affected versionversion=>= 2.8.0rc0, < 2.8.1
- Affected versionversion=>= 2.9.0rc0, < 2.9.0
What conditions does exploitation require?
What is affected?
Attacks
What attackers are doing with it
Daily unique IPs observed by Shadowserver honeypots for known exploited vulnerabilities (KEVs). Missing observations do not establish an absence of attacks.
Weakness, pattern, technique
Public exploit references
- TensorFlow signal-operation crash reproducerproof of concept · demonstrated
Labels summarize the accepted research assessment. They do not indicate a test against your environment.
Technologies
Your stack
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Your stack
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