Vulnerability-Lookup

VAR-202111-1730

Vulnerability from variot - Updated: 2023-12-18 12:16

A specially-crafted HTTP request can lead to SQL injection. An attacker can make authenticated HTTP requests to trigger this vulnerability at ‘health_alt_filter’ parameter. This can be done as any authenticated user or through cross-site request forgery. R-SeeNet for, SQL There is an injection vulnerability.Information is obtained, information is tampered with, and service operation is interrupted. (DoS) It may be in a state

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CVE-2021-21936 (GCVE-0-2021-21936)

Vulnerability from cvelistv5 – Published: 2021-12-22 18:07 – Updated: 2024-08-03 18:30

Summary

Severity

7.7 (High)


                        
                          CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N

CWE

CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

Assigner

talos mitre root

References

1 reference

URL	Tags
https://talosintelligence.com/vulnerability_repor…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
n/a	Advantech	Affected: Advantech R-SeeNet Advantech R-SeeNet 2.4.15 (30.07.2021)

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.