Service crash via zero dimension in UnravelIndex
Published Aug 12, 2021 · Updated Aug 4, 2024
Divide-by-zero in Google TensorFlow before 2.3.4, 2.4.0 through 2.4.2, and 2.5.0 allows local users to crash model-serving processes. The UnravelIndexOp kernel multiplies dims and divides indices by that product without rejecting a zero dimension, producing a floating-point exception. Reachability requires an application to pass attacker-controlled dimensions to the operation; the bounded impact is a crash of the serving process.
Summary
What happened
Divide-by-zero in Google TensorFlow before 2.3.4, 2.4.0 through 2.4.2, and 2.5.0 allows local users to crash model-serving processes. The UnravelIndexOp kernel multiplies dims and divides indices by that product without rejecting a zero dimension, producing a floating-point exception. Reachability requires an application to pass attacker-controlled dimensions to the operation; the bounded impact is a crash of the serving process.
The record
- CVE
- CVE-2021-37668
- Published
- Aug 12, 2021
- Updated
- Aug 4, 2024
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-369, T1499.004
- Attack vector
- local
- Privileges
- authenticated
Timeline
How it unfolded
- Aug 12, 2021CVE publishedPublication date reported by the CVE source.
- Aug 4, 2024Record 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=< 2.3.4
- Affected versionversion=>= 2.4.0, < 2.4.3
- Affected versionversion=>= 2.5.0, < 2.5.1
What conditions does exploitation require?
What is affected?
Published CVSS scores
CVSS describes severity. EPSS estimates exploitation probability.
Attacks
What attackers are doing with it
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Weakness, pattern, technique
Public exploit references
- Official UnravelIndex zero-dimension triggerproof of concept · demonstrated
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Technologies
Your stack
See the directory against your own environment.
Your stack
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