Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
461 detections
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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 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.
Detects modifications to cloud storage configurations in Azure and GCP that grant public access to containers or blobs. Attackers may leverage this to expose sensitive data stored in cloud environments by changing permissions to be publicly readable.
Detects unauthorized or risky configuration changes in Google Cloud Storage or Azure Storage accounts that grant public access (e.g., allUsers/allAuthenticatedUsers or public blob access) specifically on storage resources identified as production or sensitive (PII/financial data).
Detects anomalous sign-in activity for service principals (non-interactive accounts) where the same application authenticates from multiple distinct countries within a 24-hour window. This behavior often indicates the unauthorized use of compromised service principal credentials, such as client secrets or certificates, from distributed attacker-controlled infrastructure.
Detects modifications to Google Cloud Storage bucket IAM policies that grant access to 'allUsers' or 'allAuthenticatedUsers'. This activity indicates a potential misconfiguration or an attempt by an attacker to stage or exfiltrate data by making bucket contents publicly accessible.
Detects the creation of scheduled tasks, recurring jobs, or webhook subscriptions by a user identity flagged as an AI_AGENT. This activity is monitored for persistence, especially when the event lacks a descriptive context or targets external networks, suggesting potential unauthorized agent behavioral drift or malicious persistence.
Detects anomalous, high-volume file deletion, modification, or resource deletion operations performed by an identified AI agent service account within a short timeframe. This behavior is indicative of a compromised AI agent being leveraged for mass data destruction, ransomware activity, or disruptive configuration changes.
Detects clicks on sponsored search engine ads that redirect users to Google Cloud Storage (GCS) buckets with names or paths designed to impersonate the 'Ledger' brand. These artifacts are indicative of a malvertising campaign using typosquatted storage paths to deliver malicious payloads or credential harvesting pages.
Detects anomalous, unauthorized access to machine learning model artifacts (e.g., .onnx, .pt, .h5) within object storage or model registries. The rule identifies suspicious patterns including high-volume file reads by non-ML team identities, lack of multi-factor authentication, or access from geolocations outside approved operating regions, indicative of potential model exfiltration or intellectual property theft.
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 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 the creation of new programmatic credentials (AWS access keys, Azure AD service principal credentials, or GCP service account keys) where the identity creating the credential differs from the identity for which the credential is being issued. This behavior is often indicative of persistence mechanisms or credential abuse where an attacker with sufficient permissions creates secondary credentials for other accounts.
This rule detects the creation or modification of recurring cloud automation tasks (AWS EventBridge rules, Azure Automation Runbooks/Logic Apps, and GCP Cloud Scheduler jobs). Adversaries leverage these features to establish persistent access to a cloud environment by ensuring malicious code or scripts execute automatically, even after initial compromised credentials have been revoked.
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