GCP - ロギングのポストエクスプロイテーション

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基本情報

詳細については、以下を確認してください：

GCP - Logging Enum

監視を妨害する他の方法については、以下を確認してください：

GCP - Monitoring Post Exploitation

デフォルトのロギング

デフォルトでは、読み取りアクションを実行するだけでは捕まることはありません。詳細については、ロギング列挙セクションを確認してください。

除外されたプリンシパルの追加

https://console.cloud.google.com/iam-admin/audit/allservices および https://console.cloud.google.com/iam-admin/audit では、ログを生成しないプリンシパルを追加することが可能です。攻撃者はこれを悪用して捕まるのを防ぐことができます。

ログの読み取り - logging.logEntries.list

bash
# Read logs
gcloud logging read "logName=projects/your-project-id/logs/log-id" --limit=10 --format=json

# Everything from a timestamp
gcloud logging read "timestamp >= \"2023-01-01T00:00:00Z\"" --limit=10 --format=json

# Use these options to indicate a different bucket or view to use: --bucket=_Required  --view=_Default

logging.logs.delete

bash
# Delete all entries from a log in the _Default log bucket - logging.logs.delete
gcloud logging logs delete <log-name>

ログを書く - logging.logEntries.create

bash
# Write a log entry to try to disrupt some system
gcloud logging write LOG_NAME "A deceptive log entry" --severity=ERROR

logging.buckets.update

bash
# Set retention period to 1 day (_Required has a fixed one of 400days)

gcloud logging buckets update bucketlog --location=<location> --description="New description" --retention-days=1

logging.buckets.delete

bash
# Delete log bucket
gcloud logging buckets delete BUCKET_NAME --location=<location>

logging.links.delete

bash
# Delete link
gcloud logging links delete <link-id> --bucket <bucket> --location <location>

logging.views.delete

bash
# Delete a logging view to remove access to anyone using it
gcloud logging views delete <view-id> --bucket=<bucket> --location=global

logging.views.update

bash
# Update a logging view to hide data
gcloud logging views update <view-id> --log-filter="resource.type=gce_instance" --bucket=<bucket> --location=global --description="New description for the log view"

logging.logMetrics.update

bash
# Update log based metrics - logging.logMetrics.update
gcloud logging metrics update <metric-name> --description="Changed metric description" --log-filter="severity>CRITICAL" --project=PROJECT_ID

logging.logMetrics.delete

bash
# Delete log based metrics - logging.logMetrics.delete
gcloud logging metrics delete <metric-name>

logging.sinks.delete

bash
# Delete sink - logging.sinks.delete
gcloud logging sinks delete <sink-name>

logging.sinks.update

bash
# Disable sink - logging.sinks.update
gcloud logging sinks update <sink-name> --disabled

# Createa filter to exclude attackers logs - logging.sinks.update
gcloud logging sinks update SINK_NAME --add-exclusion="name=exclude-info-logs,filter=severity<INFO"

# Change where the sink is storing the data - logging.sinks.update
gcloud logging sinks update <sink-name> new-destination

# Change the service account to one withuot permissions to write in the destination - logging.sinks.update
gcloud logging sinks update SINK_NAME --custom-writer-identity=attacker-service-account-email --project=PROJECT_ID

# Remove explusions to try to overload with logs - logging.sinks.update
gcloud logging sinks update SINK_NAME --clear-exclusions

# If the sink exports to BigQuery, an attacker might enable or disable the use of partitioned tables, potentially leading to inefficient querying and higher costs. - logging.sinks.update
gcloud logging sinks update SINK_NAME --use-partitioned-tables
gcloud logging sinks update SINK_NAME --no-use-partitioned-tables

tip

AWSハッキングを学び、実践する：HackTricks Training AWS Red Team Expert (ARTE)
GCPハッキングを学び、実践する：HackTricks Training GCP Red Team Expert (GRTE) Azureハッキングを学び、実践する：HackTricks Training Azure Red Team Expert (AzRTE)

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