Vulnerability-Lookup

GHSA-32MW-C4PF-PRW5

Vulnerability from github – Published: 2022-05-24 17:34 – Updated: 2022-05-24 17:34

Details

A vulnerability in Cisco IoT Field Network Director (FND) could allow an unauthenticated, remote attacker to view sensitive database information on an affected device. The vulnerability is due to the absence of authentication for sensitive information. An attacker could exploit this vulnerability by sending crafted curl commands to an affected device. A successful exploit could allow the attacker to view sensitive database information on the affected device.

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{
  "affected": [],
  "aliases": [
    "CVE-2020-26076"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-200"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2020-11-18T18:15:00Z",
    "severity": "HIGH"
  },
  "details": "A vulnerability in Cisco IoT Field Network Director (FND) could allow an unauthenticated, remote attacker to view sensitive database information on an affected device. The vulnerability is due to the absence of authentication for sensitive information. An attacker could exploit this vulnerability by sending crafted curl commands to an affected device. A successful exploit could allow the attacker to view sensitive database information on the affected device.",
  "id": "GHSA-32mw-c4pf-prw5",
  "modified": "2022-05-24T17:34:27Z",
  "published": "2022-05-24T17:34:27Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-26076"
    },
    {
      "type": "WEB",
      "url": "https://tools.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-FND-SSI-V2myWX9y"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

CVE-2020-26076 (GCVE-0-2020-26076)

Vulnerability from cvelistv5 – Published: 2020-11-18 17:40 – Updated: 2024-11-13 17:39

Title

Cisco IoT Field Network Director Information Disclosure Vulnerability

Summary

Severity

5.3 (Medium)


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

SSVC

Exploitation: none Automatable: yes Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-11-13 17:12 UTC

CWE

CWE-497

Assigner

cisco mitre root

References

1 reference

URL	Tags
https://tools.cisco.com/security/center/content/C…	vendor-advisoryx_refsource_CISCO

Impacted products

1 product

Vendor	Product	Version
Cisco	Cisco IoT Field Network Director (IoT-FND)	Affected: n/a

Date Public

2020-11-18 00:00

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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.