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AWS Discovery API Calls via CLI from a Single Resource
Dec 8, 2025 · Domain: Cloud Data Source: AWS Data Source: AWS EC2 Data Source: AWS IAM Data Source: AWS S3 Data Source: AWS Cloudtrail Data Source: AWS RDS Data Source: AWS Lambda Data Source: AWS STS Data Source: AWS KMS Data Source: AWS SES Data Source: AWS Cloudfront Data Source: AWS DynamoDB Data Source: AWS Elastic Load Balancing Use Case: Threat Detection Tactic: Discovery Resources: Investigation Guide ·Detects when a single AWS resource is running multiple read-only, discovery API calls in a 10-second window. This behavior could indicate an actor attempting to discover the AWS infrastructure using compromised credentials or a compromised instance. Adversaries may use this information to identify potential targets for further exploitation or to gain a better understanding of the target's infrastructure.
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AWS EC2 LOLBin Execution via SSM SendCommand
Dec 5, 2025 · Domain: Cloud Domain: Endpoint OS: Linux Use Case: Threat Detection Tactic: Execution Tactic: Command and Control Data Source: AWS Data Source: Amazon Web Services Data Source: AWS CloudTrail Data Source: AWS EC2 Data Source: AWS SSM Data Source: AWS Systems Manager Data Source: Elastic Defend Resources: Investigation Guide ·Identifies the execution of Living Off the Land Binaries (LOLBins) or GTFOBins on EC2 instances via AWS Systems Manager (SSM)
SendCommandAPI. This detection correlates AWS CloudTrailSendCommandevents with endpoint process execution by matching SSM command IDs. While AWS redacts command parameters in CloudTrail logs, this correlation technique reveals the actual commands executed on EC2 instances. Adversaries may abuse SSM to execute malicious commands remotely without requiring SSH or RDP access, using legitimate system utilities for data exfiltration, establishing reverse shells, or lateral movement.
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This rule identifies potentially suspicious activity by detecting instances where a single IAM user's temporary session token is accessed from multiple IP addresses within a short time frame. Such behavior may suggest that an adversary has compromised temporary credentials and is utilizing them from various locations. To enhance detection accuracy and minimize false positives, the rule incorporates criteria that evaluate unique IP addresses, user agents, cities, and networks. These additional checks help distinguish between legitimate distributed access patterns and potential credential misuse. Detected activities are classified into different types based on the combination of unique indicators, with each classification assigned a fidelity score reflecting the likelihood of malicious behavior. High fidelity scores are given to patterns most indicative of threats, such as multiple unique IPs, networks, cities, and user agents. Medium and low fidelity scores correspond to less severe patterns, enabling security teams to effectively prioritize alerts.
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Detects sensitive AWS IAM API operations executed using temporary session credentials (access key IDs beginning with "ASIA"). Temporary credentials are commonly issued through sts:GetSessionToken, sts:AssumeRole, or AWS SSO logins and are meant for short-term use. It is unusual for legitimate users or automated processes to perform privileged IAM actions (e.g., creating users, updating policies, or enabling/disabling MFA) with session tokens. This behavior may indicate credential theft, session hijacking, or the abuse of a privileged role’s temporary credentials.
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Detects the deactivation of a Multi-Factor Authentication (MFA) device in AWS Identity and Access Management (IAM). MFA provides critical protection against unauthorized access by requiring a second factor for authentication. Adversaries or compromised administrators may deactivate MFA devices to weaken account protections, disable strong authentication, or prepare for privilege escalation or persistence. This rule monitors successful DeactivateMFADevice API calls, which represent the point at which MFA protection is actually removed.
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Detects attempts to create or enable a Virtual MFA device (CreateVirtualMFADevice, EnableMFADevice) using temporary AWS credentials (access keys beginning with ASIA). Session credentials are short-lived and tied to existing authenticated sessions, so using them to register or enable MFA devices is unusual. Adversaries who compromise temporary credentials may abuse this behavior to establish persistence by attaching new MFA devices to maintain access to high-privilege accounts despite key rotation or password resets.
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Detects creation of a new AWS CloudTrail trail via CreateTrail API. While legitimate during onboarding or auditing improvements, adversaries can create trails that write to attacker-controlled destinations, limit regions, or otherwise subvert monitoring objectives. New trails should be validated for destination ownership, encryption, multi-region coverage, and organizational scope.
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Detects deletion of an AWS CloudTrail trail via DeleteTrail API. Removing trails is a high-risk action that destroys an audit control plane and is frequently paired with other destructive or stealthy operations. Validate immediately and restore compliant logging.
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Detects Cloudtrail logging suspension via StopLogging API. Stopping CloudTrail eliminates forward audit visibility and is a classic defense evasion step before sensitive changes or data theft. Investigate immediately and determine what occurred during the logging gap.
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Detects updates to an existing CloudTrail trail via UpdateTrail API which may reduce visibility, change destinations, or weaken integrity (e.g., removing global events, moving the S3 destination, or disabling validation). Adversaries can modify trails to evade detection while maintaining a semblance of logging. Validate any configuration change against approved baselines.
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Identifies the usage of the AWS CLI with a user agent string containing
distrib#kali, which suggests the request was made from a Kali Linux distribution. This may indicate offensive security tooling or unauthorized use of the AWS CLI from a potentially adversarial environment.
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