[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間:2025-09-05 (世界標準時間)。"],[],[],null,["| Premium and Enterprise [service tiers](/security-command-center/docs/service-tiers)\n\nThis document describes a threat finding type in Security Command Center. Threat findings are generated by\n[threat detectors](/security-command-center/docs/concepts-security-sources#threats) when they detect\na potential threat in your cloud resources. For a full list of available threat findings, see [Threat findings index](/security-command-center/docs/threat-findings-index).\n\nOverview\n\nData exfiltration from BigQuery is detected by examining audit\nlogs for the following scenario:\n\n- A resource is saved to a Google Drive folder.\n\nHow to respond\n\nTo respond to this finding, do the following:\n\nStep 1: Review finding details\n\n1. Open an `Exfiltration: BigQuery Data to Google Drive` finding, as directed in [Reviewing findings](/security-command-center/docs/how-to-investigate-threats#reviewing_findings).\n2. On the **Summary** tab of the finding details panel, review the\n information in the following sections:\n\n - **What was detected** , including:\n - **Principal email**: the account used to exfiltrate the data.\n - **Exfiltration sources**: details about the BigQuery table from which data was exfiltrated.\n - **Exfiltration targets**: details about the destination in Google Drive.\n - **Affected resource** , including:\n - **Resource full name**: the name of the BigQuery resource whose data was exfiltrated.\n - **Project full name**: the Google Cloud project that contains the source BigQuery dataset.\n - **Related links** , including:\n - **Cloud Logging URI**: link to Logging entries.\n - **MITRE ATT\\&CK method**: link to the MITRE ATT\\&CK documentation.\n - **Related findings**: links to any related findings.\n3. For additional information, click the **JSON** tab.\n\n4. In the JSON, note the following fields.\n\n - `sourceProperties`:\n - `evidence`:\n - `sourceLogId`:\n - `projectId`: the Google Cloud project that contains the source BigQuery dataset.\n - `properties`:\n - `extractionAttempt`:\n - `jobLink`: the link to the BigQuery job that exfiltrated data\n\nStep 2: Review permissions and settings\n\n1. In the Google Cloud console, go to the **IAM** page.\n\n \u003cbr /\u003e\n\n [Go to IAM](https://console.cloud.google.com/iam-admin/iam)\n\n \u003cbr /\u003e\n\n2. If necessary, select the project listed in the `projectId` field in the\n finding JSON (from [Step 1](#biqquery_drive_findings)).\n\n3. On the page that appears, in the **Filter** box, enter the email address\n listed in `access.principalEmail` (from [Step 1](#biqquery_drive_findings))\n and check what permissions are assigned to the account.\n\nStep 3: Check logs\n\n1. On the **Summary tab** of the finding details panel, click the **Cloud Logging URI** link to open the **Logs Explorer**.\n2. Find admin activity logs related to BigQuery jobs by using the following filters:\n - `protoPayload.methodName=\"Jobservice.insert\"`\n - `protoPayload.methodName=\"google.cloud.bigquery.v2.JobService.InsertJob\"`\n\nStep 4: Research attack and response methods\n\n1. Review the MITRE ATT\\&CK framework entry for this finding type: [Exfiltration Over Web Service: Exfiltration to Cloud Storage](https://attack.mitre.org/techniques/T1567/002/).\n2. Review related findings by clicking the link on the **Related findings** on the **Related findings** row in the **Summary** tab of the finding details. Related findings are the same finding type on the same instance and network.\n3. To develop a response plan, combine your investigation results with MITRE research.\n\nStep 5: Implement your response\n\n\nThe following response plan might be appropriate for this finding, but might also impact operations.\nCarefully evaluate the information you gather in your investigation to determine the best way to\nresolve findings.\n\n- Contact the owner of the project with exfiltrated data.\n- Consider [revoking permissions](/iam/docs/granting-changing-revoking-access#revoking-console) for the principal in the `access.principalEmail` field until the investigation is completed.\n- To stop further exfiltration, [add restrictive IAM policies](/bigquery/docs/dataset-access-controls) to the impacted BigQuery datasets (`exfiltration.sources`).\n- To scan impacted datasets for sensitive information, [use\n Sensitive Data Protection](/bigquery/docs/scan-with-dlp). You can also [send\n Sensitive Data Protection data to Security Command Center](/sensitive-data-protection/docs/sending-results-to-scc). Depending on the quantity of information, Sensitive Data Protection costs can be significant. Follow best practices for [keeping Sensitive Data Protection costs\n under control](/sensitive-data-protection/docs/best-practices-costs).\n- To limit access to the BigQuery API, [use\n VPC Service Controls](/vpc-service-controls/docs/overview).\n- To identify and fix overly permissive roles, use [IAM\n Recommender](/iam/docs/recommender-overview).\n\nWhat's next\n\n- Learn [how to work with threat\n findings in Security Command Center](/security-command-center/docs/how-to-investigate-threats).\n- Refer to the [Threat findings index](/security-command-center/docs/threat-findings-index).\n- Learn how to [review a\n finding](/security-command-center/docs/how-to-investigate-threats#reviewing_findings) through the Google Cloud console.\n- Learn about the [services that\n generate threat findings](/security-command-center/docs/concepts-security-sources#threats)."]]