Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects GitHub OAuth authorization, repository cloning, or ZIP downloads from source IP addresses that have not been observed for the specific actor within the past 30 days. This rule helps identify potential account compromise or token theft where an attacker attempts to access repository data from a new location, while specifically excluding bot/service accounts known for rotating CI infrastructure IPs.
Detects an attempt to exploit a directive injection vulnerability in the SharePoint 'WebPartPages.asmx' SOAP web service, specifically targeting the 'GetWebPartPageConnectionInfo' method. The rule looks for suspicious 'Register' directives in the request body, which could lead to unauthorized code execution or configuration manipulation.
These rules detect various exploitation attempts targeting SharePoint to bypass SafeControls, an security mechanism used to restrict the types of controls allowed in web parts. The patterns match suspicious Register directives and markup injection techniques often associated with remote code execution or privilege escalation, as identified in CVE-2026-65660.
Monitors for the publication of specific NPM packages ('@dforge-core/dforge-mcp' or 'dforge-mcp') with a specific version ('0.2.21'). This rule is designed to track software supply chain activity related to this specific package and version.
Detects high-frequency actions including code pushes, branch policy overrides, or workflow completions on the 'main' branch of the 'dforge-core/dforge-mcp' repository within a short time window (under 120 minutes). This may indicate automated interaction, potential rapid CI/CD activity, or unauthorized mass modification of the core repository.
This rule detects modifications to GitHub Actions workflow configuration files (.yml or .yaml) located in the .github/workflows/ directory. Such modifications may indicate unauthorized tampering with CI/CD pipelines to facilitate persistent execution, credential theft, or supply chain attacks.
Detects the use of anomalous session tokens in Azure Active Directory (Azure AD) sign-in events where the token is being used in a non-interactive manner without a corresponding interactive authentication event. This behavior is indicative of token theft or infostealer activity, where an adversary replays a stolen session cookie from a new, untrusted, or non-compliant device to bypass authentication protections.
This rule detects a potential vishing attack by correlating suspicious IT helpdesk requests (e.g., password or MFA reset without manager approval or verified callback) with subsequent sensitive Entra ID identity changes (e.g., self-service password resets, MFA device registration, or new device registration) occurring for the same user within a short time window. This activity is indicative of an attacker attempting to social-engineer helpdesk staff to bypass authentication controls and compromise a user account.
Detects a single developer identity performing a high volume of git push or clone operations across a large number of distinct repositories within a short timeframe. This behavior is indicative of a compromised developer account being used to programmatically inject code into multiple repositories, potentially for a supply chain attack or mass payload propagation.
This rule detects the creation or modification of Exchange mailbox rules (Forward, Redirect, Delete, or Mark as Read) involving sensitive keywords (invoice, wire, payment, finance, remittance) shortly after an anomalous sign-in event or a password reset on the same account. This combination is a strong indicator of account takeover and mailbox persistence.
Detects instances where a user grants OAuth application permissions for high-risk scopes (e.g., mail access, offline access). The rule flags these grants, with higher risk scores assigned if the application publisher is unverified or unknown, helping identify potential illicit consent grant attacks often used to maintain long-term persistence in cloud environments.
Detects user-granted OAuth consent in Microsoft Entra ID (formerly Azure AD) involving high-risk scopes such as Mail.Read, Files.ReadWrite.All, or offline_access. This pattern is characteristic of illicit consent-grant phishing, where attackers entice users to authorize malicious applications to bypass multi-factor authentication (MFA) and establish persistent, programmatic access to sensitive mailbox and file resources.
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 the creation and immediate deletion of a GitHub OAuth token that is used to clone or fetch a large volume of private repositories within a short lifespan. This behavior is indicative of an adversary using a temporary, ephemeral token to perform rapid data exfiltration or mass reconnaissance on source code repositories.
This rule detects unauthorized GitHub repository access or OAuth activity performed by a user account identified as terminated in the organization's HR system. It uses a watchlist to cross-reference GitHub audit logs against terminated employee records, applying a 2-hour grace period to account for potential log synchronization delays or final offboarding tasks.
Detects Microsoft 365 Exchange MailItemsAccessed operations performed by a specific ClientAppId and AppId known to be associated with an exfiltration toolkit. This activity indicates unauthorized access to mail items, consistent with data harvesting efforts.
Detects anomalous SharePoint search activity that uses 'indexdocid' queries targeting specific site or web content classes. This pattern is often indicative of automated reconnaissance or enumeration of documents within a SharePoint environment, potentially attempting to bypass standard UI navigation to identify or access sensitive content.
This rule identifies potential automated activity by monitoring for specific HTTP User-Agents (e.g., Python requests, Microsoft Graph client) associated with file and mail access events. It groups by UserId and UserAgent to detect anomalous patterns that may indicate unauthorized data access or interaction by automated tools or scripts.
This rule correlates the receipt of a potential extortion-themed email (containing keywords related to ransom, bitcoin, or data leaks and mentioning cloud platforms like SharePoint, OneDrive, or Box) with a subsequent bulk access event of mail items by the same recipient using a specific client application identifier. This pattern is indicative of an attacker attempting to extort a user or organization following the unauthorized exfiltration or access of sensitive email data stored in cloud services.
Detects high-frequency access to mail items via specific client applications, or high-frequency file downloads/access within SharePoint and OneDrive. These patterns may indicate suspicious data collection or exfiltration attempts by a compromised account.
Detects high-volume, diverse administrative and discovery activities in cloud environments, including SharePoint site enumeration, Azure AD user/identity discovery, and suspicious access to mail items via specific client applications, potentially indicating post-compromise reconnaissance or data harvesting.
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