Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects emails where the subject line contains a 13-16 digit number, potentially indicating sensitive numerical patterns like a Credit Card. The rule looks for contiguous digits or common dashed/spaced credit card formats and filters out common automated email keywords to reduce false positives.
Detects emails where the subject line contains a 13-16 digit number, potentially indicating sensitive numerical patterns like a Credit Card. The rule looks for contiguous digits or common dashed/spaced credit card formats and filters out common automated email keywords to reduce false positives.
This rule detects emails that contain keywords related to 'civil id' in English or Arabic and subsequently extract potential Civil ID numbers from the email body. It then validates the extracted numbers based on birth month and day, and categorizes the risk level based on sender's domain and attachment count. This could indicate data exfiltration or sensitive information exposure.
Detects PowerShell script block logging events (Event Code 4104) that indicate the instantiation of the Outlook COM object via the MAPI namespace. This behavior is associated with malware like Horabot for email harvesting and spreading.
Detects potential spam campaigns originating from disposable or trial Jira Cloud instances with randomized subdomain names. The rule identifies emails from '.atlassian.net' domains where the subdomain is longer than 12 characters and contains a mix of letters and numbers, indicating a potentially randomized or disposable instance. It then alerts if more than 5 emails with the same subject are sent from such a suspicious subdomain.
This query parses the complex JSON parameters of the New-TransportRule and Set-TransportRule commands to find instances where email is being secretly copied externally or security is being lowered.
This rule detects instances where a SharePoint or OneDrive file/folder is shared with a guest user whose email address is identified as a threat intelligence indicator. This could indicate an attempt to exfiltrate data to a known malicious entity or an account compromise being used for data staging.
This rule detects suspicious activity related to mailbox access within Office 365. It has two main parts: 1) Identifies users accessing a high number of unique mailboxes belonging to other users. 2) Identifies users accessing a high number of unique folders within another user's mailbox. Both scenarios can indicate unauthorized access, data exfiltration attempts, or compromised accounts.
This rule detects when a user from a specified watchlist sends an email with a large attachment (over 5MB).
This rule detects suspicious activity related to mailbox access within Office 365. It has two main parts: 1) Identifies users accessing a high number of distinct mailboxes belonging to other users. 2) Identifies users accessing a high number of distinct folders within another user's mailbox. Both parts are designed to flag potential unauthorized access, data exfiltration, or reconnaissance activities within an Exchange Online environment.
Detects suspicious email inbox rule creation indicative of account compromise. Focuses on rules with randomly-generated names or rules that move emails to low-visibility folders combined with hiding actions (mark as read, delete, stop processing).
Detects a high volume of Microsoft Teams invitation emails sent to multiple users within the organization. This could indicate a reconnaissance attempt or a widespread phishing campaign where an attacker is trying to lure users into a malicious external tenant, bypassing some internal security controls.
This rule identifies emails sent from an internal employee email address to external personal email domains where the recipient's local part of the email address contains tokens from the sender's display name for more than 0 words matching. It also analyses attachments for sensitive keywords (e.g., 'confidential', 'secret') and assigns a risk score based on factors like email volume, attachment count, and presence of sensitive attachments. This could indicate an attempt to exfiltrate sensitive company data to a personal account.
It matches first name and last name keywords within the Recipient's email address, including prefixes, suffixes, or in-between parts. Therefore, the false positive rate for this query is lower.
It matches first name and last name keywords within the Recipient's email address, including prefixes, suffixes, or in-between parts. Therefore, the false positive rate for this query is lower.
To detect sensitive or confidential information sent by email from our users, I discovered that DefenderXDR is registering events when some user or services is reading files tagged or marked as sensitive. Basically, it has a "SensitiveFileRead" ActionType in the DeviceFileEvents table which indicates that a process on the monitored device has accessed a file classified as sensitive. This could include files with personally identifiable information (PII), intellectual property, or other data deemed sensitive based on the organization’s data protection policies or Microsoft’s predefined rules. This event type is essential for tracking access to sensitive data, helping to identify potential data leakage or unauthorized access attempts.
Detects a single Gmail sender address using multiple distinct display names within a short timeframe (1 hour). This behavior can indicate an attempt at impersonation, phishing, or spam campaigns where an attacker tries to appear as different entities from the same compromised or controlled email account.
Detects a high volume of emails being moved to the 'Deleted Items' folder from the 'Inbox' or 'Sent Items' folders by a single user in a short timeframe. This behavior is a known tactic used by threat actors, such as the 'Jingle Thief' group (CL-CRI-1032/Atlas Lion), to hide malicious activities like internal phishing by deleting the sent messages and any replies.
Detects internal phishing emails with subject lines mimicking IT service notifications, such as from ServiceNow. This is a tactic used by the Jingle Thief group (also tracked as Atlas Lion and STORM-0539) for lateral movement within a compromised organization.
KQL Query
This rule detects outbound email activity, specifically focusing on emails sent outside the organization's domain that include attachments. It identifies the sender, recipient, file type, file name, and file size of these attachments.
This rule detects outbound automatic reply emails sent from an organization's users to external recipients. It specifically looks for emails with subjects starting with "Automatic reply:" that have been delivered and are outbound.
This rule detects suspicious inbox forwarding rules, specifically those that forward a copy of all emails to an external address. This behavior is often indicative of an attacker attempting to exfiltrate sensitive information from a compromised mailbox.
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