Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
289 detections
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Detects GCP audit log write operations involving settings, IAM, or metadata modifications (such as setMetadata, setIamPolicy, setServiceAccount) that either originate from a known attacker IP or are performed by a default GCP service account from a public caller IP.
Detects a suspicious sequence of activities in GCP Compute Engine where a principal creates a new VM instance, attaches a disk, and creates a disk snapshot or new disk within a short window, potentially indicating data staging or exfiltration preparation.
Detects high-volume retrieval of secrets by a single principal within a one-hour window across AWS Secrets Manager, Azure Key Vault, and Google Cloud Secret Manager. This behavior is indicative of bulk credential harvesting or automated sensitive data exfiltration following unauthorized access or privilege escalation in cloud environments.
This rule detects potential privilege escalation in cloud environments (AWS, Azure, GCP) by identifying the attachment or update of overly permissive policies (e.g., wildcard permissions or administrative roles) followed by rapid execution of high-privilege actions (like creating new users, keys, or profiles) by the same actor within 15 minutes.
Detects anomalous GCP IAM Service Account Credential API calls where a principal impersonates multiple distinct service accounts within a short time window. This behavior often indicates a credential delegation chain or a multi-stage privilege escalation attempt within a GCP environment.
Detects unauthorized attempts to disable, suspend, or downgrade critical native cloud security and monitoring services (e.g., AWS GuardDuty, AWS Security Hub, Azure Defender for Cloud, and GCP Security Command Center). Attackers often perform these actions to evade detection of subsequent malicious activity within the cloud environment.
Detects anomalous authentication patterns associated with AI agent or service account credentials. The rule monitors for logins originating from multiple disparate network locations, ASNs, or countries within a 15-minute window, and detects unexpected MFA challenges directed at accounts that typically function as automated, headless identities.
Detects malicious attempts to delete or modify the access control settings of centralized cloud audit log storage, such as S3 buckets, Azure Log Analytics workspaces, or GCP log buckets. These actions aim to impair visibility into an adversary's activities, a common step in anti-forensics and data destruction workflows.
This rule detects anomalous activity involving cloud-based shell services (AWS CloudShell, Azure Cloud Shell, GCP Cloud Shell). It triggers on two main conditions: (1) First-time usage of these shell environments by a principal within the detection window, and (2) The execution of commands associated with data staging, ingress tool transfer, or exfiltration (e.g., curl, wget, storage copy commands).
Detects modifications to security groups, network security groups (NSG), or firewall rules across AWS, Azure, and GCP that expose sensitive management or database ports (22, 3389, 3306, 5432, 6379, 9200, 27017) to the entire internet (0.0.0.0/0). Such configurations significantly increase the attack surface and potential for unauthorized access, brute-force attacks, or data exposure.
Detects the creation of a new application secret or credential in a cloud environment followed by an immediate authentication attempt using that credential from an IP address that has not been observed performing successful authentication within the specified lookback window. This behavior is indicative of potential unauthorized persistence or the use of compromised credentials by an adversary.
Detects unauthorized sharing, copying, or exporting of EBS, disk, or database snapshots to external cloud accounts, subscriptions, or projects that are not present in the defined trusted allow-list for AWS, Azure, or GCP environments.
Detects modifications to cloud storage access control configurations in Azure (containers/blobs) and GCP (storage buckets) that result in public or unauthenticated access. The rule uses lookups to filter out approved public assets before alerting.
Detects high-volume or multi-type destructive operations against cloud backup, snapshot, and recovery infrastructure, including the disabling of immutability policies or soft-delete protections. This activity is consistent with ransomware actors attempting to eliminate recovery options before encrypting data.
Detects the creation of GCP compute instances that are attached to service accounts with broad 'cloud-platform' scope permissions. This activity is monitored to ensure that only authorized automation service accounts (e.g., IaC pipelines) are performing these actions, as creating instances with highly privileged service accounts can be a technique used to escalate privileges or establish persistence.
Detects anomalous large-scale data export operations in Google BigQuery (via jobs.insert or jobs.query) performed by identities (service accounts, API keys) not previously observed in the environment. This activity is indicative of credential abuse where stolen third-party analytics or monitoring service tokens are utilized for illicit data exfiltration, a behavior consistent with tactics employed by threat actors such as ShinyHunters.
This rule detects administrative changes to cloud storage configurations (AWS S3, Azure Blob, and GCP Storage) that result in public or anonymous read/write access to buckets or containers, which could lead to unauthorized data exposure.
Detects unauthorized or suspicious modifications to audit and logging configurations across AWS, Azure, and GCP. The rule identifies actions such as stopping, deleting, or updating logging trails, diagnostic settings, or logging sinks, which may indicate an adversary attempting to impair visibility into their activities (Anti-Forensics).
Detects the creation of high-cost, resource-intensive compute instances (such as GPU-enabled or large-scale VMs) within cloud regions that have not been previously utilized by the account, subscription, or project. This behavior is often indicative of unauthorized resource hijacking, such as crypto-mining or large-scale data processing by threat actors.
Detects the creation or modification of serverless functions (AWS Lambda, Azure Function Apps, GCP Cloud Functions) that exhibit high-risk configurations. These include functions assigned overly permissive IAM roles, configured for public or unauthenticated invocation, or tied to event triggers commonly abused for persistence in cloud environments.
This rule detects the creation or modification of identity federation trust configurations across multiple cloud platforms (AWS, Azure AD, GCP). Attackers often modify trust relationships to establish persistence, forge credentials, or escalate privileges by introducing malicious identity providers (SAML/OIDC) that grant unauthorized access to the environment.
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