CVE-20XX-?
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CVE-2020-15213

4.0 MEDIUM 0.8% exploit odds Fix listed

What it is

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, if the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.

At a glance

Exploitability
Can be exploited over the network without logging in. Limited direct impact.
Exploit odds
0.8% chance of exploitation in the next 30 days (EPSS).
Fix
A patch, advisory or fixed version is referenced. Upgrade or apply it.

Timeline

  1. PublishedDisclosed publicly on CVE.org and NVD
  2. Last updatedMost recent change to the record

Why it ranks here

Details

Published
Last modified
Exploit probability
0.8% · EPSS, next 30 days
Weakness
CWE-119 · Buffer errors
Record status
Modified

Affected

Attack profile CVSS 3.1 · 4.0

Attack vector
Network
Complexity
High
Privileges needed
None
User interaction
None
Scope
Changed
Confidentiality
None
Integrity
None
Availability
Low
Raw vector

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L

Is it in your code?

Hand this to your coding agent. It searches your project for the affected products and checks versions. Nothing leaves your machine.

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Fix and advisories

References

NVD record · CVE.org record