Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 the modification of an Azure Storage account configuration to enable public access (allowBlobPublicAccess: true). This activity is often associated with attackers attempting to facilitate anonymous data exfiltration by enabling public access to blobs and subsequently reading them.
Detects the creation or modification of Exchange Online inbox rules that configure automatic email forwarding or redirection to an external domain. The rule specifically flags if the action also involves deleting or hiding the message, which is a common persistence and exfiltration technique used in Business Email Compromise (BEC) attacks. The detection also incorporates correlation with recent high-risk sign-in activity for the associated user account.
Detects network traffic associated with Adversary-in-the-Middle (AiTM) phishing kits that impersonate Microsoft and Google login pages. The rules identify the presence of specific HTML elements (like Cloudflare Turnstile anti-bot gates) and authentication session cookie headers served from non-authorized/non-official domains, indicating a reverse-proxy phishing attack.
Detects potential insider threats or departing employees by correlating abnormal bulk data downloads from cloud repositories (SharePoint/OneDrive/Box/etc.) with subsequent sensitive data access and exfiltration signals. It uses baseline behavioral profiling, requires a threshold of sensitive file interactions, and mandates high-confidence exfiltration indicators (removable media usage, suspicious external domains, or multiple combined destination events) to reduce noise. Archive/staging activity is used as an optional confidence booster.
Detects potential insider threats or departing employees by correlating abnormal bulk data downloads from cloud repositories (SharePoint/OneDrive/Box/etc.) with subsequent sensitive data access and exfiltration signals. It uses baseline behavioral profiling, requires a threshold of sensitive file interactions, and mandates high-confidence exfiltration indicators (removable media usage, suspicious external domains, or multiple combined destination events) to reduce noise. Archive/staging activity is used as an optional confidence booster.
Detects high-risk GitHub events indicating data or asset exposure, such as creating public repositories with specific naming conventions, changing private repositories to public, or creating new gists, which could indicate exfiltration of sensitive assets or information.
Detects anomalous, high-volume file download or export activity originating from a single identity across multiple downstream cloud applications or tenants within a one-hour window. This behavior is indicative of a compromised shared service provider, MSP, or clearinghouse account being leveraged to exfiltrate data from multiple client environments simultaneously. The detection excludes pre-approved service accounts and relies on a dynamic baseline comparison rather than a static threshold.
Detects the installation of a browser extension that requests excessive permissions, including proxy configuration ('proxy' and 'webRequestAuthProvider') and unrestricted host access ('<all_urls>'). This pattern is commonly exploited by malicious extensions, such as the 'VPN for X' family, to perform adversary-in-the-middle attacks or proxy browser traffic.
Detects the BotHelper RAT performing live screen surveillance by identifying repeated high-frequency JPEG frame uploads to the '/api/v1/screen_live.php' endpoint, initiated by the 'msedge_proxy.exe' process.
Detects the assignment of highly privileged OAuth scopes or application roles to service principals or users within Microsoft Entra ID (formerly Azure AD). This activity is often associated with consent phishing or token abuse, where an adversary attempts to gain long-term programmatic access to sensitive resources like email, files, or directory services using a malicious or compromised application.
Detects unauthorized processes attempting to read sensitive wallet extension storage files or desktop application wallet data folders, a behavior characteristic of the Psychedelic Stealer malware designed to harvest cryptocurrency credentials prior to exfiltration.
Detects a suspicious sequence of events where a host performs multiple reconnaissance-style probes (health checks, documentation, or OpenAPI definitions) followed within 10 minutes by access to sensitive artifact-related URLs on the same remote host. This pattern is indicative of an attacker profiling a target server for metadata and then proceeding to exfiltrate files or sensitive artifacts.
Detects the use of 'findstr' or PowerShell to query sensitive configuration files (such as web.config or applicationHost.config) for credential-related keywords like 'connectionString', 'AccountKey', or 'machineKey'. This behavior is indicative of an adversary attempting to harvest credentials or sensitive configuration data stored in cleartext on the filesystem.
Detects instances where a Microsoft IIS worker process (w3wp.exe) executes commands such as 'findstr', 'Get-Content', or 'Select-Xml' to scan configuration files (e.g., applicationHost.config, web.config) or source code files (e.g., App_Code/*.cs) for sensitive information like passwords, connection strings, or API keys. This behavior is indicative of credential harvesting by an attacker using a webshell or compromised IIS process.
Detects credential-phishing attempts originating from Proton Mail addresses that result in a user clicking on a link. The rule correlates email delivery from known Proton Mail domains with subsequent URL click events to identify potential Adversary-in-the-Middle (AiTM) activity, often associated with the Star Blizzard (COLDRIVER) threat group.
Detects the execution of known Python scripts (CES_Enroll.py, ntlm_ces_relay.py, ces_negotiate_ntlm.py) often associated with NTLM relay attacks or forced authentication techniques. These scripts leverage Python to interact with authentication protocols or relay requests.
Detects an suspicious progression of activities originating from identified AI assistant/agent processes. The rule monitors for a chain of behaviors occurring within a 15-minute window: execution of an AI agent/tool, followed by host discovery (network/system enumeration), access to sensitive local credential files, archival of data, and outbound network communication to common file-sharing/exfiltration platforms.
Detects potential Adversary-in-the-Middle (AiTM) session token theft by monitoring for an initial interactive sign-in followed shortly by a non-interactive token refresh from a different IP address and browser fingerprint without a multi-factor authentication (MFA) challenge. This behavior is indicative of an adversary replaying captured session cookies via reverse-proxy infrastructure.
Detects the granting of elevated mailbox permissions (FullAccess, SendAs, SendOnBehalf, or broad folder access) by an OAuth application or service principal. This behavior is indicative of a compromise where an actor uses an App-only context to establish persistence and stage internal spearphishing, bypassing standard administrative monitoring controls.
This rule detects when an OAuth application is granted sensitive Exchange Online permissions, such as 'full_access_as_app', 'Mail.Read', 'Mail.ReadWrite', or 'Mail.Send'. Granting these permissions allows an application to access mailboxes across the tenant without requiring a signed-in user context, which is a common persistence and data exfiltration technique used in Business Email Compromise (BEC) and espionage campaigns.
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