Vulnerability-Lookup

GHSA-JWRV-R6RM-VQH2

Vulnerability from github – Published: 2022-01-14 00:01 – Updated: 2022-01-15 00:02

Details

This vulnerability allows remote attackers to execute arbitrary code on affected installations of Bentley View 10.15.0.75. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of JT files. Crafted data in a JT file can trigger a write past the end of an allocated buffer. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-14829.

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{
  "affected": [],
  "aliases": [
    "CVE-2021-34877"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2022-01-13T22:15:00Z",
    "severity": "HIGH"
  },
  "details": "This vulnerability allows remote attackers to execute arbitrary code on affected installations of Bentley View 10.15.0.75. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of JT files. Crafted data in a JT file can trigger a write past the end of an allocated buffer. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-14829.",
  "id": "GHSA-jwrv-r6rm-vqh2",
  "modified": "2022-01-15T00:02:39Z",
  "published": "2022-01-14T00:01:47Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-34877"
    },
    {
      "type": "WEB",
      "url": "https://www.bentley.com/en/common-vulnerability-exposure/BE-2021-0005"
    },
    {
      "type": "WEB",
      "url": "https://www.zerodayinitiative.com/advisories/ZDI-21-1465"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

CVE-2021-34877 (GCVE-0-2021-34877)

Vulnerability from cvelistv5 – Published: 2022-01-13 21:43 – Updated: 2024-08-04 00:26

Summary

Severity

7.8 (High)


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

CWE

CWE-787 - Out-of-bounds Write

Assigner

zdi mitre root

References

2 references

URL	Tags
https://www.bentley.com/en/common-vulnerability-e…	x_refsource_MISC
https://www.zerodayinitiative.com/advisories/ZDI-…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
Bentley	View	Affected: 10.15.0.75

Credits

Mat Powell of Trend Micro Zero Day Initiative

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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.