Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potential privilege escalation where an identity with iam:PassRole permissions deploys or updates compute resources (CloudFormation, EC2, or Lambda) to assume a more privileged IAM role than the user currently holds.
Detects the use of sts:AssumeRole or sts:GetFederationToken to request temporary security credentials in a different AWS account than the one initiating the request. This can indicate cross-account privilege escalation or lateral movement using identity federation or assumed roles.
Detects modifications to AWS S3 bucket Access Control Lists (ACLs) using the 'PutBucketAcl' API call that grant public read or write permissions. This could indicate an attempt to make sensitive data stored in S3 publicly accessible, potentially leading to data exfiltration.
Detects the use of AWS CloudShell to execute commands that download or install external files (e.g., using curl, wget, pip, or git), excluding those originating from known approved sources such as AWS-owned domains or standard package registries. This behavior may indicate an adversary attempting to download offensive tooling or backdoors into the cloud environment.
Detects 'PutBucketPolicy' API calls in AWS CloudTrail where the policy is modified to grant 'Allow' access to a wildcard ('*') or anonymous principal, without including restrictive conditional requirements such as VPC endpoints or organizational ID constraints. This behavior is a common precursor to data exfiltration from misconfigured S3 buckets.
Detects modifications to AWS EC2 snapshot or AMI attributes that grant cross-account permissions, including making them publicly accessible. This activity may indicate an attempt to exfiltrate volume data, such as credentials, configuration, or database contents, to an external AWS account.
Detects unauthorized attempts to disable, suppress, or modify security monitoring services in AWS, including GuardDuty, Security Hub, and AWS Config. This rule monitors for API calls that effectively reduce cloud visibility or detection capabilities, explicitly excluding actions performed by authorized security-engineering roles.
Detects the creation of recurring EventBridge rules or EventBridge Scheduler schedules configured with cron or rate expressions that trigger Lambda functions or SSM automation documents. This activity is a common method for cloud-native persistence, allowing for durable, recurring execution of malicious code that persists across credential rotations or resource deletions, provided the actor is not a recognized platform-engineering entity.
Detects a rapid burst of read-only IAM and STS API enumeration calls originating from a single source IP address within a one-minute window. This behavior is indicative of automated reconnaissance tools (e.g., enumerate-iam, Pacu) used in the early stages of a cloud attack to identify permissions and potential targets for privilege escalation.
Detects the execution of cloud CLI tools (aws, az, gcloud) using Unix shells (bash, sh) to perform sensitive operations such as listing secrets, keys, or metadata, which may indicate credential discovery or exfiltration.
Detects anomalous AWS activity combining bulk secret retrieval from AWS Secrets Manager using the BatchGetSecretValue API with subsequent authentication failures or validation errors in AWS STS. This behavior is indicative of automated credential harvesting pipelines or agentic frameworks rapidly enumerating and testing stolen credentials.
Detects AWS CloudTrail and Azure Active Directory (Entra ID) privilege-escalation actions (e.g., attaching policies, creating access keys, adding roles) performed by principals from rare source IPs or associated with low-frequency administrative actions, indicating potentially compromised or unauthorized account activity.
This rule detects high-risk AWS API calls that are commonly associated with privilege escalation and persistence. It monitors for the creation of overly permissive IAM policies (wildcard permissions), the creation of new access keys for existing users, and suspicious AssumeRole operations.
Detects potential AWS IAM privilege escalation attempts by identifying suspicious modifications to IAM policies, roles, or trust relationships, as well as unauthorized role assumption events. This rule monitors for activities such as attaching high-privilege policies (e.g., AdministratorAccess), creating new policy versions, and modifying trust policies to allow unexpected principals, which are common indicators of post-compromise activity designed to expand access within an AWS environment.
Detects the TeamFiltration/UNK_CondorFiltration spray signature: a large
number of distinct target UserPrincipalNames within a single tenant, each
receiving only a handful of sign-in attempts, spread across many distinct
AWS EC2-hosted source IPs/regions within a short time window. Individual
sign-ins from AWS-hosted IP ranges (VPN gateways, corporate cloud proxies,
remote contractors) are not flagged on their own; the rule requires both
the account-fanout and the IP-rotation dimensions to co-occur for the same
tenant in the same window.
number of distinct target UserPrincipalNames within a single tenant, each
receiving only a handful of sign-in attempts, spread across many distinct
AWS EC2-hosted source IPs/regions within a short time window. Individual
sign-ins from AWS-hosted IP ranges (VPN gateways, corporate cloud proxies,
remote contractors) are not flagged on their own; the rule requires both
the account-fanout and the IP-rotation dimensions to co-occur for the same
tenant in the same window.
Detects the TeamFiltration/UNK_CondorFiltration spray signature: a large
number of distinct target UserPrincipalNames within a single tenant, each
receiving only a handful of sign-in attempts, spread across many distinct
AWS EC2-hosted source IPs/regions within a short time window. Individual
sign-ins from AWS-hosted IP ranges (VPN gateways, corporate cloud proxies,
remote contractors) are not flagged on their own; the rule requires both
the account-fanout and the IP-rotation dimensions to co-occur for the same
tenant in the same window.
number of distinct target UserPrincipalNames within a single tenant, each
receiving only a handful of sign-in attempts, spread across many distinct
AWS EC2-hosted source IPs/regions within a short time window. Individual
sign-ins from AWS-hosted IP ranges (VPN gateways, corporate cloud proxies,
remote contractors) are not flagged on their own; the rule requires both
the account-fanout and the IP-rotation dimensions to co-occur for the same
tenant in the same window.
Detects a distributed password spraying campaign targeting cloud accounts, characterized by a large number of distinct accounts being targeted simultaneously from multiple AWS-hosted IP addresses, with a low volume of attempts per account per hour to evade standard threshold-based detection.
Detects cloud service principals identified as AI agents or assistants performing sensitive API operations such as IAM policy modifications or storage configuration changes. This pattern may indicate that an AI service account has been compromised or misused to perform reconnaissance, privilege escalation, or persistence, exceeding its intended scope of operation.
Detects potential poisoning of machine learning training data by identifying unauthorized file modifications to datasets, DVC repositories, or model registries that occur outside of authorized ETL or CI/CD windows.
Detects a suspicious sequence of events: an anomalous login (new device, new location, or high-risk sign-in) followed by the assumption of a highly privileged role (via AssumeRole, PIM, or role elevation) and subsequent sensitive administrative actions (e.g., creating access keys, modifying IAM policies, or disabling security auditing). This pattern is indicative of cloud identity compromise and privilege escalation, commonly seen in attacks involving groups like Scattered Spider.
Detects high-volume, unauthenticated or anonymous requests (GetObject, ListObjects, ListObjectsV2) against AWS S3 buckets. This behavior is consistent with mass enumeration or scanning activities often associated with data exfiltration attempts against misconfigured publicly-exposed storage buckets.
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