Heap disclosure via unchecked Dequantize axis
Published Feb 3, 2022 · Updated May 5, 2025
Out-of-bounds read in TensorFlow allows attackers to read heap data or crash a process via a crafted Dequantize axis. DequantizeOp accepts an axis equal to or greater than the input tensor's dimension count, then uses it to index dimension arrays without an upper-bound check. Reachability requires an application to pass attacker-controlled operation parameters; the resulting heap overread exposes adjacent memory or terminates the process.
Summary
What happened
Out-of-bounds read in TensorFlow allows attackers to read heap data or crash a process via a crafted Dequantize axis. DequantizeOp accepts an axis equal to or greater than the input tensor's dimension count, then uses it to index dimension arrays without an upper-bound check. Reachability requires an application to pass attacker-controlled operation parameters; the resulting heap overread exposes adjacent memory or terminates the process.
The record
- CVE
- CVE-2022-21726
- Published
- Feb 3, 2022
- Updated
- May 5, 2025
- Vendor
- Unknown vendor
- Product
- Unknown product
- Classifications
- CWE-125, CAPEC-540
- Attack vector
- network
- Privileges
- authenticated
Timeline
How it unfolded
- Feb 3, 2022CVE publishedPublication date reported by the CVE source.
- May 5, 2025Record updatedLatest update available in the CVE record.
Exploitability
Present is not the same as exploitable
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What is affected?
Affected products and versions are unavailable in this record.
Published CVSS scores
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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.
Public exploit references
- TensorFlow Dequantize axis proof of conceptproof of concept · demonstrated
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Technologies
Your stack
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Your stack
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