Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
361 detections
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Detects anomalous, high-volume file download or sync activity by a single user within a 10-minute window in M365 (SharePoint/OneDrive). This behavior is indicative of bulk data exfiltration, potentially occurring after a session hijacking or account takeover, where the attacker leverages legitimate user credentials to access and export sensitive data.
Detects rapid mass-cloning or downloading of private GitHub repositories shortly after an OAuth token authorization, originating from IP addresses or countries not previously associated with the user account. This behavior is indicative of unauthorized bulk data extraction using compromised credentials, consistent with threat actor activity (e.g., TeamPCP/UNC6780).
Detects anomalous access to SharePoint or OneDrive by identities identified as bots, agents, or service principals. The rule specifically monitors for multiple file accesses where the file names suggest the presence of secrets, passwords, or API keys, which may indicate a compromised or malicious AI agent attempting to harvest credentials.
Detects an AI agent identity accessing an unusually high number of distinct internal repositories, such as wikis, ticketing systems, code repositories, or customer data stores within a 15-minute window. This behavior is consistent with automated discovery or collection (T1213) by an AI agent.
Detects instances where an AI agent tool invocation contains potential credential data (API keys, tokens) followed by a suspicious sign-in or Key Vault access event from an atypical location for that specific identity within a short timeframe. This rule monitors for potential exfiltration or abuse of credentials handled or exposed by AI agents.
This rule detects the unauthorized download of complete ML model checkpoint or weight files from a model registry or object storage. It monitors for common model file extensions in download events that are not associated with a legitimate deployment justification or a pre-approved change management window, helping to identify potential intellectual property theft or model exfiltration attempts.
Detects anomalous, high-volume activity in cloud-based services such as SharePoint, OneDrive, and Exchange, specifically tracking file access, downloads, and mailbox exports. This behavior may indicate bulk data collection, unauthorized exfiltration, or malicious data staging by a compromised account.
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.
This rule detects when a user or service account accesses or downloads a high volume of files from SharePoint or OneDrive that match sensitive keywords such as 'password', 'secret', 'credential', or specific file extensions like '.pem', '.pfx', and '.env'. This behavior is indicative of an attempt to harvest credentials, API keys, or configuration secrets from cloud storage repositories.
Detects high-volume file download, access, or preview activity originating from known anonymous proxy services. This behavior is indicative of potential data exfiltration or unauthorized mass data collection from cloud storage applications.
Detects high-volume file download, access, or preview activity originating from known anonymous proxy services. This behavior is indicative of potential data exfiltration or unauthorized mass data collection from cloud storage applications.
Detects behavior associated with the TeamFiltration backdoor, where a user account downloads a file from OneDrive, modifies or replaces that file, and re-uploads it within a short timeframe (30 minutes). This pattern is consistent with the 'taint shared content' technique used to distribute malicious files through legitimate cloud storage.
Detects potential abuse of the Microsoft Graph API by correlating device-code authentication events with subsequent high-volume activity, such as mail or file enumeration, from the same account within a short window. This pattern is indicative of ARToken-style token proxying, where an attacker intercepts an OAuth device-code token to gain unauthorized access to an user's resources.
Detects a suspicious spike in MailItemsAccessed operations occurring across multiple distinct tenant organization IDs within a 60-second window, using the same ClientAppId. This behavior is indicative of automated, centralized credential abuse or mailbox collection tools (often associated with campaigns like Storm-2755) rather than legitimate, isolated user or service-level activity.
Detects automated post-compromise mailbox reconnaissance following an anomalous OAuth device code sign-in that exhibits high-risk indicators. The rule identifies programmatic access to a high volume of mail items within a short window following suspicious token issuance, which is characteristic of automated scanning or data exfiltration tooling.
Detects anomalous, high-frequency enumeration of AI/ML assets such as model registries, container image repositories, and training data buckets. This activity is indicative of reconnaissance for AI supply chain attacks, specifically tracking with MITRE ATLAS AML.T0007 (Discover AI Artifacts), where an actor probes infrastructure to identify targets for model theft, data poisoning, or unauthorized access.
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.
Detects newly consented OAuth applications that immediately perform mass access or exfiltration of mail and file data across multiple mailboxes or drives within a short period, potentially indicating an attacker utilizing a malicious OAuth application.
Detects high-volume file access or download operations in SharePoint or OneDrive performed by common scripting libraries and client user agents, which may indicate automated data exfiltration.
Detects bulk read operations on AWS Secrets Manager or similar cloud secret stores where the accessed resources contain keywords related to cryptocurrency custody, private keys, or wallet material. This pattern is indicative of unauthorized exfiltration attempts by threat actors such as Slim Spider targeting digital asset infrastructure.
Detects a suspicious spike in MailItemsAccessed operations occurring across multiple distinct tenant organization IDs within a 60-second window, using the same ClientAppId. This behavior is indicative of automated, centralized credential abuse or mailbox collection tools (often associated with campaigns like Storm-2755) rather than legitimate, isolated user or service-level activity.
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