Service interruption via unchecked Range size arithmetic
Published Feb 4, 2022 · Updated Apr 23, 2025
Integer overflow in Google TensorFlow Range before 2.5.3, 2.6.0 through 2.6.2, and 2.7.0 allows remote authenticated users to interrupt services. RangeOp and RangeSize compute the output length from start, limit, and delta, then cast it to int64_t without rejecting values above INT64_MAX. A caller must supply Range operands that overflow the size calculation; the resulting undefined behavior or extreme allocation interrupts the hosting process.
Summary
What happened
Integer overflow in Google TensorFlow Range before 2.5.3, 2.6.0 through 2.6.2, and 2.7.0 allows remote authenticated users to interrupt services. RangeOp and RangeSize compute the output length from start, limit, and delta, then cast it to int64_t without rejecting values above INT64_MAX. A caller must supply Range operands that overflow the size calculation; the resulting undefined behavior or extreme allocation interrupts the hosting process.
The record
- CVE
- CVE-2022-23562
- Published
- Feb 4, 2022
- Updated
- Apr 23, 2025
- Vendor
- Product
- TensorFlow
- Classifications
- CWE-190, T1499
- Attack vector
- network
- Privileges
- authenticated
Timeline
How it unfolded
- Feb 4, 2022CVE publishedPublication date reported by the CVE source.
- Apr 23, 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=< 2.5.3
- Affected versionversion=>= 2.6.0, < 2.6.3
- Affected versionversion=>= 2.7.0, < 2.7.1
What conditions does exploitation require?
What is affected?
Published CVSS scores
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Attacks
What attackers are doing with it
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Public exploit references
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Technologies
Your stack
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Your stack
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