Vulnerability-Lookup

GHSA-PR63-CC36-Q84H

Vulnerability from github – Published: 2026-05-13 18:30 – Updated: 2026-05-13 18:30

Details

This issue impacts MongoDB Server v5.0 versions prior to 5.0.33, v6.0 versions prior to 6.0.28, v7.0 versions prior to 7.0.34, v8.0 versions prior to 8.0.23, v8.2 versions prior to 8.2.9 and v8.3 versions prior to 8.3.2.

Severity

8.8 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

8.7 (High)


                  
                    CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

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JSON

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{
  "affected": [],
  "aliases": [
    "CVE-2026-8053"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-05-13T04:17:41Z",
    "severity": "HIGH"
  },
  "details": "An issue in MongoDB Server\u0027s time-series collection implementation allows an authenticated user with database write privileges to trigger an out-of-bounds memory write in the mongod process. The issue results from an inconsistency in the internal field-name-to-index mapping within the time-series bucket catalog. Under certain conditions this can result in arbitrary code execution.\n\nThis issue impacts MongoDB Server v5.0 versions prior to 5.0.33, v6.0 versions prior to 6.0.28, v7.0 versions prior to 7.0.34, v8.0 versions prior to 8.0.23, v8.2 versions prior to 8.2.9 and v8.3 versions prior to 8.3.2.",
  "id": "GHSA-pr63-cc36-q84h",
  "modified": "2026-05-13T18:30:51Z",
  "published": "2026-05-13T18:30:51Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-8053"
    },
    {
      "type": "WEB",
      "url": "https://jira.mongodb.org/browse/SERVER-126021"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ]
}

CVE-2026-8053 (GCVE-0-2026-8053)

Vulnerability from cvelistv5 – Published: 2026-05-12 23:59 – Updated: 2026-05-14 03:56

Title

FlatBSON Duplicate Field Index Drift

Summary

An issue in MongoDB Server's time-series collection implementation allows an authenticated user with database write privileges to trigger an out-of-bounds memory write in the mongod process. The issue results from an inconsistency in the internal field-name-to-index mapping within the time-series bucket catalog. Under certain conditions this can result in arbitrary code execution. This issue impacts MongoDB Server v5.0 versions prior to 5.0.33, v6.0 versions prior to 6.0.28, v7.0 versions prior to 7.0.34, v8.0 versions prior to 8.0.23, v8.2 versions prior to 8.2.9 and v8.3 versions prior to 8.3.2.

Severity

8.7 (High)


                        
                          CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

8.8 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

SSVC

Exploitation: none Automatable: no Technical Impact: total

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2026-05-13 00:00 UTC

CWE

CWE-787 - Out-of-bounds Write

Assigner

mongodb mitre root

References

1 reference

URL	Tags
https://jira.mongodb.org/browse/SERVER-126021	issue-tracking

Impacted products

1 product

Vendor	Product	Version
MongoDB, Inc.	MongoDB Server	Affected: 5.0 , < 5.0.33 (custom) Affected: 6.0 , < 6.0.28 (custom) Affected: 7.0 , < 7.0.34 (custom) Affected: 8.0 , < 8.0.23 (custom) Affected: 8.2 , < 8.2.9 (custom) Affected: 8.3 , < 8.3.2 (custom)

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JSON

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      {
        "metrics": [
          {
            "other": {
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                "id": "CVE-2026-8053",
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                  },
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                  },
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                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-05-13T00:00:00+00:00",
                "version": "2.0.3"
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          "dateUpdated": "2026-05-14T03:56:09.398Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
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          "product": "MongoDB Server",
          "vendor": "MongoDB, Inc.",
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              "status": "affected",
              "version": "7.0",
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              "status": "affected",
              "version": "8.0",
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            },
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              "lessThan": "8.2.9",
              "status": "affected",
              "version": "8.2",
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            },
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              "lessThan": "8.3.2",
              "status": "affected",
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      "metrics": [
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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.