Vulnerability-Lookup

VAR-202112-0645

Vulnerability from variot - Updated: 2024-02-13 22:54

There is a memory leak vulnerability in CloudEngine 12800 V200R019C00SPC800, CloudEngine 5800 V200R019C00SPC800, CloudEngine 6800 V200R019C00SPC800 and CloudEngine 7800 V200R019C00SPC800. The software does not sufficiently track and release allocated memory while parse a series of crafted binary messages, which could consume remaining memory. Successful exploit could cause memory exhaust. plural Huawei The product contains a vulnerability related to lack of freeing of resources after valid lifetime.Service operation interruption (DoS) It may be in a state. Huawei CloudEngine is a data center switch of China's Huawei (Huawei) company

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CVE-2021-40008 (GCVE-0-2021-40008)

Vulnerability from cvelistv5 – Published: 2021-12-13 15:48 – Updated: 2024-08-04 02:27

Summary

Severity

No CVSS data available.

CWE

Memory Leak

Assigner

huawei mitre root

References

1 reference

URL	Tags
https://www.huawei.com/en/psirt/security-advisori…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
n/a	CloudEngine 12800;CloudEngine 5800;CloudEngine 6800;CloudEngine 7800	Affected: V200R019C00SPC800

Show details on NVD website

JSON

To clipboard

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Sightings

Author	Source	Type	Date	Other

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.