AWS Service Quotas Multi-Region GetServiceQuota Requests
Identifies when a single AWS principal makes GetServiceQuota API calls for the EC2 service quota L-1216C47A, across more than 10 AWS regions within a 30-second window. This quota represents the vCPU limit for on-demand EC2 instances. Adversaries commonly enumerate this quota across regions to assess capacity for large-scale instance deployment, including cryptocurrency mining, malware hosting, or command-and-control infrastructure. This behavior may indicate cloud infrastructure discovery using compromised credentials or a compromised workload.
Elastic rule (View on GitHub)
1[metadata]
2creation_date = "2024/08/26"
3maturity = "production"
4updated_date = "2025/12/15"
5
6[rule]
7author = ["Elastic"]
8description = """
9Identifies when a single AWS principal makes GetServiceQuota API calls for the EC2 service quota L-1216C47A, across more
10than 10 AWS regions within a 30-second window. This quota represents the vCPU limit for on-demand EC2 instances.
11Adversaries commonly enumerate this quota across regions to assess capacity for large-scale instance deployment,
12including cryptocurrency mining, malware hosting, or command-and-control infrastructure. This behavior may indicate
13cloud infrastructure discovery using compromised credentials or a compromised workload.
14"""
15false_positives = [
16 """
17 Organizations with mature multi-region operations may legitimately query EC2 service quotas across regions for
18 capacity planning, automation, or compliance validation. Infrastructure-as-code tooling, quota monitoring solutions,
19 or centralized cloud governance platforms may also generate similar activity. Validate the identity, purpose, and
20 historical behavior of the calling principal before treating this activity as malicious.
21 """,
22]
23from = "now-6m"
24language = "esql"
25license = "Elastic License v2"
26name = "AWS Service Quotas Multi-Region GetServiceQuota Requests"
27note = """## Triage and analysis
28
29> **Disclaimer**:
30> This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.
31
32### Investigating AWS Service Quotas Multi-Region GetServiceQuota Requests
33
34AWS Service Quotas define usage limits for AWS services and are commonly referenced during capacity planning or automation. However, adversaries frequently enumerate EC2 on-demand instance quotas across many regions to identify where they can rapidly deploy compute resources for malicious purposes such as cryptocurrency mining, botnet hosting, or malware staging. This rule detects unusually fast, multi-region enumeration of the EC2 on-demand vCPU quota (`L-1216C47A`), a pattern that is uncommon for normal administrative activity and strongly associated with cloud infrastructure discovery.
35
36### Possible investigation steps
37
38**Identify the actor**
39- Review `aws.cloudtrail.user_identity.arn` and `aws.cloudtrail.user_identity.access_key_id` to determine whether the requests originated from an IAM user, role, or assumed role. Validate whether this principal is expected to perform quota discovery or capacity analysis across many regions.
40
41**Evaluate the scope of discovery**
42- Review the `cloud.region` values to determine which regions were queried and whether they align with regions normally used by your organization. Rapid enumeration of rarely used or disabled regions increases suspicion.
43
44**Inspect request origin and tooling**
45- Review `source.ip`, `source.as.organization.name`, and `user_agent.original` to determine whether the activity originated from a trusted corporate network, known cloud automation environment, or an unexpected hosting provider or VPN.
46- Unexpected user agents or hosting providers may indicate compromised credentials or an attacker-controlled instance.
47
48**Correlate with follow-on activity**
49- Search for subsequent EC2-related actions such as `RunInstances`, `RequestSpotInstances`, `CreateLaunchTemplate`, or `ModifyInstanceAttribute` following the quota discovery.
50- Review recent IAM activity for the same principal, including access key creation, role assumptions, or policy changes.
51
52**Assess intent and risk**
53- Determine whether this activity aligns with a known operational task (capacity planning, onboarding, automation testing), or whether it represents unexplained reconnaissance behavior.
54- If the principal is newly created, rarely used, or exhibiting other anomalous behavior, treat this as high risk.
55
56### False positive analysis
57- Multi-region quota discovery may be legitimate in organizations with global deployments, centralized cloud governance, or automated capacity monitoring.
58- Infrastructure-as-code pipelines, quota management tools, or internal cloud platforms may periodically enumerate quotas.
59
60### Response and remediation
61- If the activity is unauthorized or suspicious, immediately rotate or disable access keys associated with the principal and revoke active sessions.
62- Review CloudTrail activity for evidence of follow-on abuse, particularly EC2 instance launches, network changes, or IAM modifications.
63- Apply tighter IAM permissions to restrict access to Service Quotas APIs where not explicitly required.
64- Enforce MFA on IAM users and consider conditional access controls (such as source IP or VPC restrictions) for sensitive roles.
65- Notify security operations and cloud platform teams to assess potential impact and determine whether containment actions (such as SCP enforcement or account isolation) are required.
66- Update detection coverage to monitor for EC2 provisioning attempts following quota discovery to catch resource abuse early.
67
68### Additional information
69- **[AWS IR Playbooks](https://github.com/aws-samples/aws-incident-response-playbooks/blob/c151b0dc091755fffd4d662a8f29e2f6794da52c/playbooks/)**
70- **[AWS Customer Playbook Framework](https://github.com/aws-samples/aws-customer-playbook-framework/tree/a8c7b313636b406a375952ac00b2d68e89a991f2/docs)**
71- **[AWS Knowledge Center – Security Best Practices](https://aws.amazon.com/premiumsupport/knowledge-center/security-best-practices/)**
72"""
73references = [
74 "https://www.sentinelone.com/labs/exploring-fbot-python-based-malware-targeting-cloud-and-payment-services/",
75 "https://docs.aws.amazon.com/servicequotas/2019-06-24/apireference/API_GetServiceQuota.html",
76]
77risk_score = 21
78rule_id = "19be0164-63d2-11ef-8e38-f661ea17fbce"
79severity = "low"
80tags = [
81 "Domain: Cloud",
82 "Data Source: AWS",
83 "Data Source: Amazon Web Services",
84 "Data Source: AWS Service Quotas",
85 "Use Case: Threat Detection",
86 "Tactic: Discovery",
87 "Resources: Investigation Guide",
88]
89timestamp_override = "event.ingested"
90type = "esql"
91
92query = '''
93from logs-aws.cloudtrail-* METADATA _id, _version, _index
94
95// filter for GetServiceQuota API calls
96| where
97 event.dataset == "aws.cloudtrail"
98 and event.provider == "servicequotas.amazonaws.com"
99 and event.action == "GetServiceQuota"
100
101// truncate the timestamp to a 30-second window
102| eval Esql.time_window_date_trunc = date_trunc(30 seconds, @timestamp)
103
104// dissect request parameters to extract service and quota code
105| dissect aws.cloudtrail.request_parameters "{%{?Esql.aws_cloudtrail_request_parameters_service_code_key}=%{Esql.aws_cloudtrail_request_parameters_service_code}, %{?quota_code_key}=%{Esql.aws_cloudtrail_request_parameters_quota_code}}"
106
107// filter for EC2 service quota L-1216C47A (vCPU on-demand instances)
108| where Esql.aws_cloudtrail_request_parameters_service_code == "ec2" and Esql.aws_cloudtrail_request_parameters_quota_code == "L-1216C47A"
109
110// keep only the relevant fields
111| keep
112 Esql.time_window_date_trunc,
113 aws.cloudtrail.user_identity.arn,
114 cloud.region,
115 Esql.aws_cloudtrail_request_parameters_service_code,
116 Esql.aws_cloudtrail_request_parameters_quota_code,
117 aws.cloudtrail.request_parameters,
118 @timestamp,
119 aws.cloudtrail.user_identity.type,
120 aws.cloudtrail.user_identity.access_key_id,
121 source.ip,
122 cloud.account.id,
123 user_agent.original,
124 source.as.organization.name,
125 data_stream.namespace
126
127// count the number of unique regions and total API calls within the time window
128| stats
129 Esql.cloud_region_count_distinct = count_distinct(cloud.region),
130 Esql.event_count = count(*),
131 Esql.aws_cloudtrail_request_parameters_values = VALUES(aws.cloudtrail.request_parameters),
132 Esql.event_timestamp_values = VALUES(@timestamp),
133 Esql.aws_cloudtrail_user_identity_type_values = VALUES(aws.cloudtrail.user_identity.type),
134 Esql.aws_cloudtrail_user_identity_access_key_id_values = VALUES(aws.cloudtrail.user_identity.access_key_id),
135 Esql.source_ip_values = VALUES(source.ip),
136 Esql.cloud_account_id_values = VALUES(cloud.account.id),
137 Esql.user_agent_original_values = VALUES(user_agent.original),
138 Esql.source_as_organization_name_values = VALUES(source.as.organization.name),
139 Esql.cloud_region_values = VALUES(cloud.region),
140 Esql.data_stream_namespace_values = VALUES(data_stream.namespace)
141 by Esql.time_window_date_trunc, aws.cloudtrail.user_identity.arn
142
143// filter for API calls in more than 10 regions within the 30-second window
144| where
145 Esql.cloud_region_count_distinct >= 10
146 and Esql.event_count >= 10
147'''
148
149
150[[rule.threat]]
151framework = "MITRE ATT&CK"
152[[rule.threat.technique]]
153id = "T1580"
154name = "Cloud Infrastructure Discovery"
155reference = "https://attack.mitre.org/techniques/T1580/"
156
157
158[rule.threat.tactic]
159id = "TA0007"
160name = "Discovery"
161reference = "https://attack.mitre.org/tactics/TA0007/"
162
163[rule.investigation_fields]
164field_names = [
165 "Esql.cloud_region_count_distinct",
166 "Esql.event_count",
167 "Esql.time_window_date_trunc",
168 "Esql.event_timestamp_values",
169 "aws.cloudtrail.user_identity.arn",
170 "Esql.aws_cloudtrail_user_identity_type_values",
171 "Esql.aws_cloudtrail_user_identity_access_key_id_values",
172 "Esql.source_ip_values",
173 "Esql.source_as_organization_name_values",
174 "Esql.user_agent_original_values",
175 "Esql.cloud_account_id_values",
176 "Esql.cloud_region_values",
177 "Esql.data_stream_namespace_values",
178]
Triage and analysis
Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.
Investigating AWS Service Quotas Multi-Region GetServiceQuota Requests
AWS Service Quotas define usage limits for AWS services and are commonly referenced during capacity planning or automation. However, adversaries frequently enumerate EC2 on-demand instance quotas across many regions to identify where they can rapidly deploy compute resources for malicious purposes such as cryptocurrency mining, botnet hosting, or malware staging. This rule detects unusually fast, multi-region enumeration of the EC2 on-demand vCPU quota (L-1216C47A), a pattern that is uncommon for normal administrative activity and strongly associated with cloud infrastructure discovery.
Possible investigation steps
Identify the actor
- Review
aws.cloudtrail.user_identity.arnandaws.cloudtrail.user_identity.access_key_idto determine whether the requests originated from an IAM user, role, or assumed role. Validate whether this principal is expected to perform quota discovery or capacity analysis across many regions.
Evaluate the scope of discovery
- Review the
cloud.regionvalues to determine which regions were queried and whether they align with regions normally used by your organization. Rapid enumeration of rarely used or disabled regions increases suspicion.
Inspect request origin and tooling
- Review
source.ip,source.as.organization.name, anduser_agent.originalto determine whether the activity originated from a trusted corporate network, known cloud automation environment, or an unexpected hosting provider or VPN. - Unexpected user agents or hosting providers may indicate compromised credentials or an attacker-controlled instance.
Correlate with follow-on activity
- Search for subsequent EC2-related actions such as
RunInstances,RequestSpotInstances,CreateLaunchTemplate, orModifyInstanceAttributefollowing the quota discovery. - Review recent IAM activity for the same principal, including access key creation, role assumptions, or policy changes.
Assess intent and risk
- Determine whether this activity aligns with a known operational task (capacity planning, onboarding, automation testing), or whether it represents unexplained reconnaissance behavior.
- If the principal is newly created, rarely used, or exhibiting other anomalous behavior, treat this as high risk.
False positive analysis
- Multi-region quota discovery may be legitimate in organizations with global deployments, centralized cloud governance, or automated capacity monitoring.
- Infrastructure-as-code pipelines, quota management tools, or internal cloud platforms may periodically enumerate quotas.
Response and remediation
- If the activity is unauthorized or suspicious, immediately rotate or disable access keys associated with the principal and revoke active sessions.
- Review CloudTrail activity for evidence of follow-on abuse, particularly EC2 instance launches, network changes, or IAM modifications.
- Apply tighter IAM permissions to restrict access to Service Quotas APIs where not explicitly required.
- Enforce MFA on IAM users and consider conditional access controls (such as source IP or VPC restrictions) for sensitive roles.
- Notify security operations and cloud platform teams to assess potential impact and determine whether containment actions (such as SCP enforcement or account isolation) are required.
- Update detection coverage to monitor for EC2 provisioning attempts following quota discovery to catch resource abuse early.
Additional information
References
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