Process crash via broadcast-dimension integer overflow
Published Nov 18, 2022 · Updated Apr 22, 2025
Denial of service in Google TensorFlow before 2.8.4, 2.9.0 through 2.9.2, and 2.10.0 allows attackers to crash a process via large shapes. BCastList stores the inferred output dimension in a 32-bit integer, so a dimension above that range overflows before BCast::ToShape encounters a fatal check. The caller must supply a broadcast dimension above 2,147,483,647; the resulting failure terminates the TensorFlow-hosting process without reading or changing data.
Summary
What happened
Denial of service in Google TensorFlow before 2.8.4, 2.9.0 through 2.9.2, and 2.10.0 allows attackers to crash a process via large shapes. BCastList stores the inferred output dimension in a 32-bit integer, so a dimension above that range overflows before BCast::ToShape encounters a fatal check. The caller must supply a broadcast dimension above 2,147,483,647; the resulting failure terminates the TensorFlow-hosting process without reading or changing data.
The record
- CVE
- CVE-2022-41890
- Published
- Nov 18, 2022
- Updated
- Apr 22, 2025
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-704, T1499.004
- Attack vector
- network
- Privileges
- authenticated
Timeline
How it unfolded
- Nov 18, 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=>= 2.10.0, < 2.10.1
- Affected versionversion=< 2.8.4
- Affected versionversion=>= 2.9.0, < 2.9.3
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
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 BCast::ToShape crash reproducerproof of concept · demonstrated
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Technologies
Your stack
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Your stack
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