Vulnerability-Lookup

FKIE_CVE-2021-30046

Vulnerability from fkie_nvd - Published: 2021-04-06 13:15 - Updated: 2026-06-17 03:49

Severity

6.5 (Medium) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H

Summary

VIGRA Computer Vision Library Version-1-11-1 contains a segmentation fault vulnerability in the impex.hxx read_image_band() function, in which a crafted file can cause a denial of service.

References

	URL	Tags
	cve@mitre.org	https://github.com/ukoethe/vigra/issues/494	Exploit, Third Party Advisory
	af854a3a-2127-422b-91ae-364da2661108	https://github.com/ukoethe/vigra/issues/494	Exploit, Third Party Advisory

Impacted products

	Vendor	Product	Version
	vigra_computer_vision_library_project	vigra_computer_vision_library	1.11.1

JSON

To clipboard

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    },
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  "id": "CVE-2021-30046",
  "lastModified": "2026-06-17T03:49:37.907",
  "metrics": {
    "cvssMetricV2": [
      {
        "acInsufInfo": false,
        "baseSeverity": "MEDIUM",
        "cvssData": {
          "accessComplexity": "MEDIUM",
          "accessVector": "NETWORK",
          "authentication": "NONE",
          "availabilityImpact": "PARTIAL",
          "baseScore": 4.3,
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "vectorString": "AV:N/AC:M/Au:N/C:N/I:N/A:P",
          "version": "2.0"
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        "exploitabilityScore": 8.6,
        "impactScore": 2.9,
        "obtainAllPrivilege": false,
        "obtainOtherPrivilege": false,
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          "availabilityImpact": "HIGH",
          "baseScore": 6.5,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
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          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H",
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        "impactScore": 3.6,
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  "published": "2021-04-06T13:15:14.607",
  "references": [
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      "source": "cve@mitre.org",
      "tags": [
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  "vulnStatus": "Modified",
  "weaknesses": [
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      "description": [
        {
          "lang": "en",
          "value": "CWE-755"
        }
      ],
      "source": "nvd@nist.gov",
      "type": "Primary"
    }
  ]
}

CVE-2021-30046 (GCVE-0-2021-30046)

Vulnerability from cvelistv5 – Published: 2021-04-06 12:09 – Updated: 2024-08-03 22:24

Summary

VIGRA Computer Vision Library Version-1-11-1 contains a segmentation fault vulnerability in the impex.hxx read_image_band() function, in which a crafted file can cause a denial of service.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

1 reference

URL	Tags
https://github.com/ukoethe/vigra/issues/494	x_refsource_MISC

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.