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ATT&CK Technique

Cloud Infrastructure Discovery

T1580 · discovery

An adversary may attempt to discover infrastructure and resources that are available within an infrastructure-as-a-service (IaaS) environment. This includes compute service resources such as instances, virtual machines, and snapshots as well as resources of other services including the storage and database services. Cloud providers offer methods such as APIs and commands issued through CLIs to serve information about infrastructure.

For example, AWS provides a DescribeInstances API within the Amazon EC2 API that can return information about one or more instances within an account, the ListBuckets API that returns a list of all buckets owned by the authenticated sender of the request, the HeadBucket API to determine a bucket’s existence along with access permissions of the request sender, or the GetPublicAccessBlock API to retrieve access block configuration for a bucket. Similarly, GCP's Cloud SDK CLI provides the gcloud compute instances list command to list all Google Compute Engine instances in a project, and Azure's CLI command az vm list lists details of virtual machines. In addition to API commands, adversaries can utilize open source tools to discover cloud storage infrastructure through Wordlist Scanning.

An adversary may enumerate resources using a compromised user's access keys to determine which are available to that user. The discovery of these available resources may help adversaries determine their next steps in the Cloud environment, such as establishing Persistence.An adversary may also use this information to change the configuration to make the bucket publicly accessible, allowing data to be accessed without authentication. Adversaries have also may use infrastructure discovery APIs such as DescribeDBInstances to determine size, owner, permissions, and network ACLs of database resources.

Adversaries can use this information to determine the potential value of databases and discover the requirements to access them. Unlike in Cloud Service Discovery, this technique focuses on the discovery of components of the provided services rather than the services themselves.

IaaS
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Actors Using This

3
north_koreaJade Sleet / TraderTraitor / UNC4899 / Pressure Chollima
predominantly_english_speaking_youth_organized_crimeLAPSUS$
chinaSilk Typhoon
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Likely Attack Path

Techniques the same actors pair with this one distinctively - those showing up among actors who use this technique noticeably more than across all actors (lift > 1.15), grouped by kill-chain phase. The × is that lift multiplier; the shared-actor count is in the tooltip. A near-universal technique pairs with everything at baseline, so its list is short by design.
resource-development earlier
T1583.003 · Virtual Private Server ×2.43T1585.001 · Social Media Accounts ×2.36
initial-access earlier
T1199 · Trusted Relationship ×2.74
execution earlier
T1204.001 · Malicious Link ×1.72
persistence earlier
T1078.004 · Cloud Accounts ×4.49
credential-access earlier
T1539 · Steal Web Session Cookie ×3.66T1555.003 · Credentials from Web Browsers ×1.86
discovery same
T1069 · Permission Groups Discovery ×1.82
lateral-movement later
T1550.004 · Web Session Cookie ×34.00T1021.004 · SSH ×4.86T1550 · Use Alternate Authentication Material ×4.58T1021.001 · Remote Desktop Protocol ×1.87T1021 · Remote Services ×1.56
collection later
T1213 · Data from Information Repositories ×1.70
exfiltration later
T1029 · Scheduled Transfer ×3.45
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Atomic Tests

2
Executable Atomic Red Team test cases for exercising this technique in a lab. Copy a command, run it on the listed platform, confirm your detections fire.
shlinux, macos, iaas:awsAWS - EC2 Enumeration from Cloud Instance
This atomic runs several API calls (sts:GetCallerIdentity, s3:ListBuckets, iam:GetAccountSummary, iam:ListRoles, iam:ListUsers, iam:GetAccountAuthorizationDetails, ec2:DescribeSnapshots, cloudtrail:DescribeTrails, guardduty:ListDetectors) from the context of an EC2 instance role. This simulates an attacker compromising an EC2 instance and running initial discovery commands on it. This atomic test leverages a tool called stratus-red-team built by DataDog (https://github.com/DataDog/stratus-red-team). Stratus Red Team is a self-contained binary. You can use it to easily detonate offensive attack techniques against a live cloud environment. Ref: https://stratus-red-team.cloud/attack-techniques/AWS/aws.discovery.ec2-enumerate-from-instance/ 
export AWS_REGION=#{aws_region}
cd #{stratus_path}
echo "Stratus: Start Warmup."
./stratus warmup aws.discovery.ec2-enumerate-from-instance
echo "Stratus: Start Detonate."
./stratus detonate aws.discovery.ec2-enumerate-from-instance
command_promptiaas:awsAWS - EC2 Security Group Enumeration
Simulate an attacker's action to enumerate EC2 Security Groups in a compromised AWS environment.
aws ec2 describe-security-groups --profile #{aws_profile} --output #{output_format}
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Mitigations

1
MITRE ATT&CK mitigations - vendor-agnostic guidance for reducing exposure to this technique.
M1018User Account Management

User Account Management involves implementing and enforcing policies for the lifecycle of user accounts, including creation, modification, and deactivation. Proper account management reduces the attack surface by limiting unauthorized access, managing account privileges, and ensuring accounts are used according to organizational policies.

Enforcing the Principle of Least Privilege
  • Implementation: Assign users only the minimum permissions required to perform their job functions. Regularly audit accounts to ensure no excess permissions are granted.
  • Use Case: Reduces the risk of privilege escalation by ensuring accounts cannot perform unauthorized actions. Implementing Strong Password Policies.
  • Implementation: Enforce password complexity requirements (e.g., length, character types). Require password expiration every 90 days and disallow password reuse.
  • Use Case: Prevents adversaries from gaining unauthorized access through password guessing or brute force attacks. Managing Dormant and Orphaned Accounts.
  • Implementation: Implement automated workflows to disable accounts after a set period of inactivity (e.g., 30 days). Remove orphaned accounts (e.g., accounts without an assigned owner) during regular account audits.
  • Use Case: Eliminates dormant accounts that could be exploited by attackers. Account Lockout Policies.
  • Implementation: Configure account lockout thresholds (e.g., lock accounts after five failed login attempts). Set lockout durations to a minimum of 15 minutes.
  • Use Case: Mitigates automated attack techniques that rely on repeated login attempts. Multi-Factor Authentication (MFA) for High-Risk Accounts.
  • Implementation: Require MFA for all administrative accounts and high-risk users. Use MFA mechanisms like hardware tokens, authenticator apps, or biometrics.
  • Use Case: Prevents unauthorized access, even if credentials are stolen. Restricting Interactive Logins.
  • Implementation: Restrict interactive logins for privileged accounts to specific secure systems or management consoles. Use group policies to enforce logon restrictions.
  • Use Case: Protects sensitive accounts from misuse or exploitation.
Tools for Implementation Built-in Tools
  • Microsoft Active Directory (AD): Centralized account management and RBAC enforcement.
  • Group Policy Object (GPO): Enforce password policies, logon restrictions, and account lockout policies.
Identity and Access Management (IAM) Tools
  • Okta: Centralized user provisioning, MFA, and SSO integration.
  • Microsoft Azure Active Directory: Provides advanced account lifecycle management, role-based access, and conditional access policies.
Privileged Account Management (PAM)
  • CyberArk, BeyondTrust, Thycotic: Manage and monitor privileged account usage, enforce session recording, and JIT access.
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Detection Coverage

1/6 layers
Coverage across standard detection surfaces. Rows marked none have no rule of that type mapped. Some are real blind spots worth closing; others are simply not applicable to this technique (e.g. YARA matches malware files, not network behaviour).
Behavioral / log (Sigma) 1
Analytics (MITRE CAR) none
Runtime / container (Falco) none
File / malware (YARA) none
Network (Suricata/Snort) none
Vuln scan (Nuclei) none
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Comply & Defend

NIST 800-53AC-02, AC-03, AC-05, AC-06, IA-02
Intelligence Graph · click any node to traverse
CVETechnique ActorTool Family
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External lookups - second-class, for what we don’t hold ourselves
MITRE ATT&CKAtomic Red Teamcar (MITRE)
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