CVE-2020-15213
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
- PublishedDisclosed publicly on CVE.org and NVD
- Last updatedMost recent change to the record
Why it ranks here
- Exploited in the wild: no, CISA does not list it.
- Exploit odds: 0.8% in the next 30 days (EPSS).
- Severity: 4.0 MEDIUM (CVSS).
- Fix: a patch or advisory is linked.
Details
- Published
- Last modified
- Exploit probability
- 0.8% · EPSS, next 30 days
- Weakness
- CWE-119 · Buffer errors
- Record status
- Modified
Affected
- Google Tensorflow < 2.2.1
- Google Tensorflow < 2.3.1
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.
Read https://cve-list.com/agent/cve/CVE-2020-15213.md and follow it. Check whether this project is affected by CVE-2020-15213. Read only. Don't change anything and don't upload my code. Tell me yes, no or not sure, with the file as proof.
Fix and advisories
- https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87
- https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87
References
- https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87
- https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a
- https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87