CVE-2026-14538 (GCVE-0-2026-14538)

Vulnerability from cvelistv5 – Published: 2026-07-31 01:42 – Updated: 2026-07-31 16:09
VLAI
Title
BigQuery Dataset Allowlist Bypass via Metadata Dry-Run in MCP Toolbox
Summary
An improper authorization and security-boundary bypass vulnerability in the bigquery-execute-sql tool component of Google mcp-toolbox versions 0.16.1 through 1.4.0 allows an authenticated attacker to bypass allowedDatasets validation checks. The toolbox relies on the BigQuery dry-run API to enforce dataset restrictions, but due to a fail-open logic flaw, it bypasses validation when the API returns an empty array for specialized constructs. This allows the attacker to extract structural DDL schemas for explicitly excluded datasets via INFORMATION_SCHEMA, and access downstream federated row data via EXTERNAL_QUERY connections.
SSVC
Exploitation: none Automatable: no Technical Impact: partial
CISA Coordinator (v2.0.3)
CWE
  • CWE-285 - (Improper Authorization)
  • CWE-863 - (Incorrect Authorization)
Assigner
References
Impacted products
Vendor Product Version
Google mcp-toolbox Affected: 0.16.1 , ≤ 1.4.0 (semver)
Create a notification for this product.
Credits
HE WEI (ギカク)
Show details on NVD website

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-14538",
                "options": [
                  {
                    "Exploitation": "none"
                  },
                  {
                    "Automatable": "no"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-07-31T16:09:10.915078Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-07-31T16:09:31.250Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "defaultStatus": "unaffected",
          "product": "mcp-toolbox",
          "vendor": "Google",
          "versions": [
            {
              "lessThanOrEqual": "1.4.0",
              "status": "affected",
              "version": "0.16.1",
              "versionType": "semver"
            }
          ]
        }
      ],
      "credits": [
        {
          "lang": "en",
          "type": "finder",
          "value": "HE WEI (\u30ae\u30ab\u30af)"
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "supportingMedia": [
            {
              "base64": false,
              "type": "text/html",
              "value": "An improper authorization and security-boundary bypass vulnerability in the bigquery-execute-sql tool component of Google mcp-toolbox versions 0.16.1 through 1.4.0 allows an authenticated attacker to bypass allowedDatasets validation checks. The toolbox relies on the BigQuery dry-run API to enforce dataset restrictions, but due to a fail-open logic flaw, it bypasses validation when the API returns an empty array for specialized constructs. This allows the attacker to extract structural DDL schemas for explicitly excluded datasets via INFORMATION_SCHEMA, and access downstream federated row data via EXTERNAL_QUERY connections."
            }
          ],
          "value": "An improper authorization and security-boundary bypass vulnerability in the bigquery-execute-sql tool component of Google mcp-toolbox versions 0.16.1 through 1.4.0 allows an authenticated attacker to bypass allowedDatasets validation checks. The toolbox relies on the BigQuery dry-run API to enforce dataset restrictions, but due to a fail-open logic flaw, it bypasses validation when the API returns an empty array for specialized constructs. This allows the attacker to extract structural DDL schemas for explicitly excluded datasets via INFORMATION_SCHEMA, and access downstream federated row data via EXTERNAL_QUERY connections."
        }
      ],
      "impacts": [
        {
          "capecId": "CAPEC-180",
          "descriptions": [
            {
              "lang": "en",
              "value": "CAPEC-180 Exploiting Incorrectly Configured Access Control Security Levels"
            }
          ]
        }
      ],
      "metrics": [
        {
          "cvssV4_0": {
            "Automatable": "NOT_DEFINED",
            "Recovery": "NOT_DEFINED",
            "Safety": "NOT_DEFINED",
            "attackComplexity": "LOW",
            "attackRequirements": "NONE",
            "attackVector": "NETWORK",
            "baseScore": 5.7,
            "baseSeverity": "MEDIUM",
            "exploitMaturity": "UNREPORTED",
            "privilegesRequired": "LOW",
            "providerUrgency": "NOT_DEFINED",
            "subAvailabilityImpact": "NONE",
            "subConfidentialityImpact": "HIGH",
            "subIntegrityImpact": "NONE",
            "userInteraction": "NONE",
            "valueDensity": "NOT_DEFINED",
            "vectorString": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N/E:U",
            "version": "4.0",
            "vulnAvailabilityImpact": "NONE",
            "vulnConfidentialityImpact": "HIGH",
            "vulnIntegrityImpact": "NONE",
            "vulnerabilityResponseEffort": "NOT_DEFINED"
          },
          "format": "CVSS",
          "scenarios": [
            {
              "lang": "en",
              "value": "GENERAL"
            }
          ]
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-285",
              "description": "CWE-285 (Improper Authorization)",
              "lang": "en",
              "type": "CWE"
            },
            {
              "cweId": "CWE-863",
              "description": "CWE-863 (Incorrect Authorization)",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-07-31T01:42:29.707Z",
        "orgId": "14ed7db2-1595-443d-9d34-6215bf890778",
        "shortName": "Google"
      },
      "references": [
        {
          "url": "https://github.com/googleapis/mcp-toolbox/pull/3452"
        }
      ],
      "source": {
        "discovery": "UNKNOWN"
      },
      "title": "BigQuery Dataset Allowlist Bypass via Metadata Dry-Run in MCP Toolbox",
      "x_generator": {
        "engine": "Vulnogram 1.0.2"
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "14ed7db2-1595-443d-9d34-6215bf890778",
    "assignerShortName": "Google",
    "cveId": "CVE-2026-14538",
    "datePublished": "2026-07-31T01:42:29.707Z",
    "dateReserved": "2026-07-03T02:06:17.583Z",
    "dateUpdated": "2026-07-31T16:09:31.250Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2",
  "vulnerability-lookup:meta": {
    "epss": {
      "cve": "CVE-2026-14538",
      "date": "2026-07-31",
      "epss": "0.00202",
      "percentile": "0.1032"
    },
    "nvd": "{\"cve\":{\"id\":\"CVE-2026-14538\",\"sourceIdentifier\":\"cve-coordination@google.com\",\"published\":\"2026-07-31T02:16:28.757\",\"lastModified\":\"2026-07-31T16:16:58.073\",\"vulnStatus\":\"Received\",\"cveTags\":[],\"descriptions\":[{\"lang\":\"en\",\"value\":\"An improper authorization and security-boundary bypass vulnerability in the bigquery-execute-sql tool component of Google mcp-toolbox versions 0.16.1 through 1.4.0 allows an authenticated attacker to bypass allowedDatasets validation checks. The toolbox relies on the BigQuery dry-run API to enforce dataset restrictions, but due to a fail-open logic flaw, it bypasses validation when the API returns an empty array for specialized constructs. This allows the attacker to extract structural DDL schemas for explicitly excluded datasets via INFORMATION_SCHEMA, and access downstream federated row data via EXTERNAL_QUERY connections.\"}],\"affected\":[{\"source\":\"cve-coordination@google.com\",\"affectedData\":[{\"vendor\":\"Google\",\"product\":\"mcp-toolbox\",\"defaultStatus\":\"unaffected\",\"versions\":[{\"version\":\"0.16.1\",\"lessThanOrEqual\":\"1.4.0\",\"versionType\":\"semver\",\"status\":\"affected\"}]}]}],\"metrics\":{\"cvssMetricV40\":[{\"source\":\"cve-coordination@google.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"4.0\",\"vectorString\":\"CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N/E:U/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\",\"baseScore\":5.7,\"baseSeverity\":\"MEDIUM\",\"attackVector\":\"NETWORK\",\"attackComplexity\":\"LOW\",\"attackRequirements\":\"NONE\",\"privilegesRequired\":\"LOW\",\"userInteraction\":\"NONE\",\"vulnConfidentialityImpact\":\"HIGH\",\"vulnIntegrityImpact\":\"NONE\",\"vulnAvailabilityImpact\":\"NONE\",\"subConfidentialityImpact\":\"HIGH\",\"subIntegrityImpact\":\"NONE\",\"subAvailabilityImpact\":\"NONE\",\"exploitMaturity\":\"UNREPORTED\",\"confidentialityRequirement\":\"NOT_DEFINED\",\"integrityRequirement\":\"NOT_DEFINED\",\"availabilityRequirement\":\"NOT_DEFINED\",\"modifiedAttackVector\":\"NOT_DEFINED\",\"modifiedAttackComplexity\":\"NOT_DEFINED\",\"modifiedAttackRequirements\":\"NOT_DEFINED\",\"modifiedPrivilegesRequired\":\"NOT_DEFINED\",\"modifiedUserInteraction\":\"NOT_DEFINED\",\"modifiedVulnConfidentialityImpact\":\"NOT_DEFINED\",\"modifiedVulnIntegrityImpact\":\"NOT_DEFINED\",\"modifiedVulnAvailabilityImpact\":\"NOT_DEFINED\",\"modifiedSubConfidentialityImpact\":\"NOT_DEFINED\",\"modifiedSubIntegrityImpact\":\"NOT_DEFINED\",\"modifiedSubAvailabilityImpact\":\"NOT_DEFINED\",\"Safety\":\"NOT_DEFINED\",\"Automatable\":\"NOT_DEFINED\",\"Recovery\":\"NOT_DEFINED\",\"valueDensity\":\"NOT_DEFINED\",\"vulnerabilityResponseEffort\":\"NOT_DEFINED\",\"providerUrgency\":\"NOT_DEFINED\"}}],\"ssvcV203\":[{\"source\":\"134c704f-9b21-4f2e-91b3-4a467353bcc0\",\"ssvcData\":{\"timestamp\":\"2026-07-31T16:09:10.915078Z\",\"id\":\"CVE-2026-14538\",\"options\":[{\"exploitation\":\"none\"},{\"automatable\":\"no\"},{\"technicalImpact\":\"partial\"}],\"role\":\"CISA Coordinator\",\"version\":\"2.0.3\"}}]},\"weaknesses\":[{\"source\":\"cve-coordination@google.com\",\"type\":\"Secondary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-285\"},{\"lang\":\"en\",\"value\":\"CWE-863\"}]}],\"references\":[{\"url\":\"https://github.com/googleapis/mcp-toolbox/pull/3452\",\"source\":\"cve-coordination@google.com\"}]}}",
    "vulnrichment": {
      "containers": "{\"adp\": [{\"title\": \"CISA ADP Vulnrichment\", \"metrics\": [{\"other\": {\"type\": \"ssvc\", \"content\": {\"id\": \"CVE-2026-14538\", \"role\": \"CISA Coordinator\", \"options\": [{\"Exploitation\": \"none\"}, {\"Automatable\": \"no\"}, {\"Technical Impact\": \"partial\"}], \"version\": \"2.0.3\", \"timestamp\": \"2026-07-31T16:09:10.915078Z\"}}}], \"providerMetadata\": {\"orgId\": \"134c704f-9b21-4f2e-91b3-4a467353bcc0\", \"shortName\": \"CISA-ADP\", \"dateUpdated\": \"2026-07-31T16:09:23.644Z\"}}], \"cna\": {\"title\": \"BigQuery Dataset Allowlist Bypass via Metadata Dry-Run in MCP Toolbox\", \"source\": {\"discovery\": \"UNKNOWN\"}, \"credits\": [{\"lang\": \"en\", \"type\": \"finder\", \"value\": \"HE WEI (\\u30ae\\u30ab\\u30af)\"}], \"impacts\": [{\"capecId\": \"CAPEC-180\", \"descriptions\": [{\"lang\": \"en\", \"value\": \"CAPEC-180 Exploiting Incorrectly Configured Access Control Security Levels\"}]}], \"metrics\": [{\"format\": \"CVSS\", \"cvssV4_0\": {\"Safety\": \"NOT_DEFINED\", \"version\": \"4.0\", \"Recovery\": \"NOT_DEFINED\", \"baseScore\": 5.7, \"Automatable\": \"NOT_DEFINED\", \"attackVector\": \"NETWORK\", \"baseSeverity\": \"MEDIUM\", \"valueDensity\": \"NOT_DEFINED\", \"vectorString\": \"CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N/E:U\", \"exploitMaturity\": \"UNREPORTED\", \"providerUrgency\": \"NOT_DEFINED\", \"userInteraction\": \"NONE\", \"attackComplexity\": \"LOW\", \"attackRequirements\": \"NONE\", \"privilegesRequired\": \"LOW\", \"subIntegrityImpact\": \"NONE\", \"vulnIntegrityImpact\": \"NONE\", \"subAvailabilityImpact\": \"NONE\", \"vulnAvailabilityImpact\": \"NONE\", \"subConfidentialityImpact\": \"HIGH\", \"vulnConfidentialityImpact\": \"HIGH\", \"vulnerabilityResponseEffort\": \"NOT_DEFINED\"}, \"scenarios\": [{\"lang\": \"en\", \"value\": \"GENERAL\"}]}], \"affected\": [{\"vendor\": \"Google\", \"product\": \"mcp-toolbox\", \"versions\": [{\"status\": \"affected\", \"version\": \"0.16.1\", \"versionType\": \"semver\", \"lessThanOrEqual\": \"1.4.0\"}], \"defaultStatus\": \"unaffected\"}], \"references\": [{\"url\": \"https://github.com/googleapis/mcp-toolbox/pull/3452\"}], \"x_generator\": {\"engine\": \"Vulnogram 1.0.2\"}, \"descriptions\": [{\"lang\": \"en\", \"value\": \"An improper authorization and security-boundary bypass vulnerability in the bigquery-execute-sql tool component of Google mcp-toolbox versions 0.16.1 through 1.4.0 allows an authenticated attacker to bypass allowedDatasets validation checks. The toolbox relies on the BigQuery dry-run API to enforce dataset restrictions, but due to a fail-open logic flaw, it bypasses validation when the API returns an empty array for specialized constructs. This allows the attacker to extract structural DDL schemas for explicitly excluded datasets via INFORMATION_SCHEMA, and access downstream federated row data via EXTERNAL_QUERY connections.\", \"supportingMedia\": [{\"type\": \"text/html\", \"value\": \"An improper authorization and security-boundary bypass vulnerability in the bigquery-execute-sql tool component of Google mcp-toolbox versions 0.16.1 through 1.4.0 allows an authenticated attacker to bypass allowedDatasets validation checks. The toolbox relies on the BigQuery dry-run API to enforce dataset restrictions, but due to a fail-open logic flaw, it bypasses validation when the API returns an empty array for specialized constructs. This allows the attacker to extract structural DDL schemas for explicitly excluded datasets via INFORMATION_SCHEMA, and access downstream federated row data via EXTERNAL_QUERY connections.\", \"base64\": false}]}], \"problemTypes\": [{\"descriptions\": [{\"lang\": \"en\", \"type\": \"CWE\", \"cweId\": \"CWE-285\", \"description\": \"CWE-285 (Improper Authorization)\"}, {\"lang\": \"en\", \"type\": \"CWE\", \"cweId\": \"CWE-863\", \"description\": \"CWE-863 (Incorrect Authorization)\"}]}], \"providerMetadata\": {\"orgId\": \"14ed7db2-1595-443d-9d34-6215bf890778\", \"shortName\": \"Google\", \"dateUpdated\": \"2026-07-31T01:42:29.707Z\"}}}",
      "cveMetadata": "{\"cveId\": \"CVE-2026-14538\", \"state\": \"PUBLISHED\", \"dateUpdated\": \"2026-07-31T16:09:31.250Z\", \"dateReserved\": \"2026-07-03T02:06:17.583Z\", \"assignerOrgId\": \"14ed7db2-1595-443d-9d34-6215bf890778\", \"datePublished\": \"2026-07-31T01:42:29.707Z\", \"assignerShortName\": \"Google\"}",
      "dataType": "CVE_RECORD",
      "dataVersion": "5.2"
    }
  }
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

Loading…