EXPLORE DETECTIONS
AWS Bedrock Unauthorized Foundation Model Access Attempt
Identifies failed, access-denied attempts to enable account-level access to an Amazon Bedrock foundation model, either by granting a foundation-model entitlement, submitting a use case for model access, or creating a foundation-model agreement (accepting the EULA). These account-level "model access" actions unlock a foundation model so that it can subsequently be invoked. A principal that is repeatedly denied when attempting these actions may be a compromised or under-privileged identity probing for the ability to unlock expensive models (LLMjacking) or to establish a durable ability to invoke models. Unlike the companion rule that detects successful model-access grants, this rule surfaces the attempt itself, which is a high-signal indicator of credential boundary-testing even though access was not granted.
AWS Bedrock Unauthorized Resource-Based Policy Modification Attempt
Detects failed, access-denied attempts to modify or delete resource-based access policies on AWS Bedrock resources via the PutResourcePolicy and DeleteResourcePolicy API calls. Resource-based policies govern which principals (including external accounts) may access Bedrock resources such as agents, knowledge bases, and custom models. A principal that is repeatedly denied when attempting to attach or remove these policies may be a compromised or under-privileged identity probing for the ability to grant external or cross-account access, or to weaken existing access controls. Unlike the companion rule that detects successful changes, this rule surfaces the attempt itself, which is a high-signal indicator of credential boundary-testing even though no change occurred.
AWS Bedrock Untrusted Model Imported or Marketplace Endpoint Registered
Detects when an AWS Bedrock custom model is imported or deployed, or when a marketplace model endpoint is created or registered, via the CreateModelImportJob, CreateCustomModelDeployment, CreateMarketplaceModelEndpoint, or RegisterMarketplaceModelEndpoint API calls. These actions introduce a model artifact from outside the organization's trusted training and approval pipeline. A backdoored, poisoned, or attacker-supplied model that downstream applications subsequently invoke represents a software supply-chain compromise. New model imports and marketplace endpoint registrations should be validated for artifact provenance (S3 source ownership), the registering identity, and whether the model originates from an approved internal pipeline.
AWS CLI Command with Custom Endpoint URL
Detects the use of the AWS CLI with the "--endpoint-url" argument, which allows users to specify a custom endpoint URL for AWS services. This can be leveraged by adversaries to redirect API requests to non-standard or malicious endpoints, potentially bypassing typical security controls and logging mechanisms. This behavior may indicate an attempt to interact with unauthorized or compromised infrastructure, exfiltrate data, or perform other malicious activities under the guise of legitimate AWS operations.
AWS CloudShell Environment Created
Identifies the creation of a new AWS CloudShell environment. CloudShell is a browser-based shell that provides command-line access to AWS resources directly from the AWS Management Console. The CreateEnvironment API is called when a user launches CloudShell for the first time or when accessing CloudShell in a new AWS region. Adversaries with console access may use CloudShell to execute commands, install tools, or interact with AWS services without needing local CLI credentials. Monitoring environment creation helps detect unauthorized CloudShell usage from compromised console sessions.
AWS CloudTrail Log Created
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.
AWS CloudTrail Log Deleted
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.
AWS CloudTrail Log Evasion
Identifies the evasion of cloudtrail logging for IAM actions involving policy creation, modification or attachment. When making certain policy-related API calls, an adversary may pad the associated policy document with whitespaces to trigger CloudTrail’s logging size constraints, resulting in incomplete logging where critical details about the policy are omitted. By exploiting this gap, threat actors can bypass monitoring performed through CloudTrail and can effectively obscure unauthorized changes. This rule looks for IAM API calls with the requestParameters property containing reason:”requestParameters too large” and omitted:true.
AWS CloudTrail Log Suspended
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.
AWS CloudTrail Log Updated
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.
AWS CloudWatch Alarm Deletion
Detects the deletion of one or more Amazon CloudWatch alarms using the "DeleteAlarms" API. CloudWatch alarms are critical for monitoring metrics and triggering alerts when thresholds are exceeded. An adversary may delete alarms to impair visibility, silence alerts, and evade detection following malicious activity. This behavior may occur during post-exploitation or cleanup phases to remove traces of compromise or disable automated responses.
AWS CloudWatch Log Group Deletion
Detects the deletion of an Amazon CloudWatch Log Group using the "DeleteLogGroup" API. CloudWatch log groups store operational and security logs for AWS services and custom applications. Deleting a log group permanently removes all associated log streams and historical log data, which can eliminate forensic evidence and disrupt security monitoring pipelines. Adversaries may delete log groups to conceal malicious activity, disable log forwarding, or impede incident response.
AWS CloudWatch Log Stream Deletion
Detects the deletion of an Amazon CloudWatch log stream using the "DeleteLogStream" API. Deleting a log stream permanently removes its associated log events and may disrupt security visibility, break audit trails, or suppress forensic evidence. Adversaries may delete log streams to conceal malicious actions, impair monitoring pipelines, or remove artifacts generated during post-exploitation activity.
AWS Config Resource Deletion
Identifies attempts to delete AWS Config resources. AWS Config provides continuous visibility into resource configuration changes and compliance posture across an account. Deleting Config components can significantly reduce security visibility and auditability. Adversaries may delete or disable Config resources to evade detection, hide prior activity, or weaken governance controls before or after other malicious actions.
AWS Configuration Recorder Stopped
Identifies when an AWS Config configuration recorder is stopped. AWS Config recorders continuously track and record configuration changes across supported AWS resources. Stopping the recorder immediately reduces visibility into infrastructure changes and can be abused by adversaries to evade detection, obscure follow-on activity, or weaken compliance and security monitoring controls.
AWS Credentials Searched For Inside A Container
This rule detects the use of system search utilities like grep and find to search for AWS credentials inside a container. Unauthorized access to these sensitive files could lead to further compromise of the container environment or facilitate a container breakout to the underlying cloud environment.
AWS Credentials Used from GitHub Actions and Non-CI/CD Infrastructure
Detects AWS access keys that are used from both GitHub Actions CI/CD infrastructure and non-CI/CD infrastructure. This pattern indicates potential credential theft where an attacker who has stolen AWS credentials configured as GitHub Actions secrets and is using them from their own infrastructure.
AWS Discovery API Calls from VPN ASN for the First Time by Identity
Flags the first time a given IAM principal invokes a narrow set of high-signal discovery APIs (credential check, account and IAM enumeration, bucket and compute inventory, logging introspection) from a source IP whose autonomous system number (ASN) matches a curated set commonly associated with consumer VPN brands, VPN-heavy hosting, and provider networks referenced in public reporting on TeamPCP activity (for example 31173 Services AB AS39351 and Oy Crea Nova Hosting Solution Ltd). Broad `List*`/`Describe*` patterns are intentionally omitted to reduce noise. Hosting ASNs are heavily dual-use; validate `source.as.number` in your data and extend `event.action` only when your baseline allows it.
AWS Discovery API Calls via CLI from a Single Resource
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.
AWS DynamoDB Scan by Unusual User
Identifies when an AWS DynamoDB table is scanned by a user who does not typically perform this action. Adversaries may use the Scan operation to collect sensitive information or exfiltrate data from DynamoDB tables. This rule detects unusual user activity by monitoring for the Scan action in CloudTrail logs. This is a New Terms rule that only flags when this behavior is observed by a user or role for the first time.
AWS DynamoDB Table Exported to S3
Identifies when an AWS DynamoDB table is exported to S3. Adversaries may use the ExportTableToPointInTime operation to collect sensitive information or exfiltrate data from DynamoDB tables. This rule detects unusual user activity by monitoring for the ExportTableToPointInTime action in CloudTrail logs. This is a New Terms rule that only flags when this behavior is observed by a user or role for the first time.
AWS EC2 AMI Shared with Another Account
Identifies an AWS Amazon Machine Image (AMI) being shared with another AWS account. Adversaries with access may share an AMI with an external AWS account as a means of data exfiltration. AMIs can contain secrets, bash histories, code artifacts, and other sensitive data that adversaries may abuse if shared with unauthorized accounts. AMIs can be made publicly available accidentally as well.
AWS EC2 CreateKeyPair by New Principal from Non-Cloud AS Organization
Identifies the first time a given IAM principal successfully creates an EC2 key pair when the request is sourced from a network whose autonomous system organization is not attributed to common cloud or hyperscaler providers in your GeoIP data. Adversaries may call CreateKeyPair to stage SSH access material before launching or accessing instances. A new terms baseline on `user_identity.arn` suppresses repeated noise from the same principal while still surfacing the initial suspicious creation from an unusual egress label.
AWS EC2 Deprecated AMI Discovery
Identifies when a user has queried for deprecated Amazon Machine Images (AMIs) in AWS. This may indicate an adversary looking for outdated AMIs that may be vulnerable to exploitation. While deprecated AMIs are not inherently malicious or indicative of a breach, they may be more susceptible to vulnerabilities and should be investigated for potential security risks.