Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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https://blog.checkpoint.com/research/iran-nexus-password-spray-campaign-targeting-cloud-environments-with-a-focus-on-the-middle-east/
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 multiple failed sign-in attempts using the 'Device Code' authentication flow from various IP addresses or locations for a single user. This behavior can indicate an adversary attempting to bypass multi-factor authentication (MFA) or gain unauthorized access through device code phishing or brute-force attacks against the device code flow. The rule specifically looks for more than 3 attempts from more than 2 distinct IP addresses or locations, targeting common Microsoft applications like Office, Teams, Azure Portal, or Graph.
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 Azure AD application registrations with redirect URIs pointing to known tunneling, reverse proxy, or attacker interaction/callback infrastructure. This can indicate an adversary attempting to establish persistence or exfiltrate data.
This rule detects inbound emails from 'azure-noreply@microsoft.com' that are delivered to the inbox, are the first contact from this sender, and contain specific keywords in the subject line such as 'severity', 'activated', 'deactivated', 'alert', 'invoice', 'payment', 'order', or 'fund'. This could indicate phishing attempts or social engineering using a spoofed Microsoft sender to deliver urgent or financially-themed messages.
This rule detects suspicious device registration activity in Microsoft 365. It correlates users who have recently visited Microsoft device login or OAuth2 device authentication URLs with subsequent device registration events in Azure AD. This could indicate an adversary attempting to register a new device to bypass MFA or gain persistent access, potentially through device code phishing.
Detects phishing emails abusing legitimate Trello invitation notifications. This rule specifically looks for emails sent from 'invitation-do-not-reply@trello.com' with a subject line matching the pattern '<name> @ <org> invited you to their board <board>'. This pattern is recently observed being abused in phishing campaigns to trick users into clicking malicious links embedded within Trello boards.
This rule detects potential social engineering attempts in external direct messages (DMs) by identifying messages that impersonate IT helpdesk or support personnel, or discuss 'working from home' scenarios. It specifically looks for keywords like 'helpdesk', 'help desk', 'IT support', and 'working from home' in the recipient details or sender display name of external messages within the last 5 days. The goal is to surface lures that aim to trick users into revealing sensitive information or performing actions under false pretenses.
This rule detects rare external domains shared in Microsoft Teams messages that users subsequently click on. It identifies messages from external senders, extracts URLs and their domains, and then filters for domains that appear infrequently (less than 3 times in the last day). The rule then correlates these rare external domains with user click events within Teams, surfacing potential phishing attempts or malicious link sharing where users interact with untrusted content.
This rule identifies external domains sending a high number of unique links in Microsoft Teams messages over the last 7 days, excluding common trusted Microsoft domains. It aims to detect potential phishing attempts or unusual external communication patterns that might indicate malicious activity or data exfiltration.
This rule detects messages within Microsoft Teams that have been identified by Microsoft Defender for Office 365 as containing phishing attempts, malware, or spam. It specifically looks for messages with 'Phish', 'Malware', or 'Spam' verdicts in the ThreatTypes field, allowing for quick identification and triage of malicious content.
Detects programmatic token refresh activity using the BAV2ROPC user agent originating from Railway IP space. This indicates automated persistent token cycling mechanisms used by the EvilTokens Phishing-as-a-Service (PhaaS) campaign to maintain access to compromised Microsoft 365 accounts.
This rule analyzes URL click events within Microsoft Teams to identify and summarize actions taken on URLs, specifically focusing on Safe Links outcomes. It helps in understanding user interaction with links, potentially identifying malicious link clicks that Safe Links has intercepted or allowed, and assessing the adoption of Safe Links protection within the Teams environment.
This rule identifies instances where users have clicked on URLs within Microsoft Teams. It specifically filters for 'UrlClickEvents' where the 'Workload' is 'Teams' and provides details such as the timestamp, user principal name, URL, URL domain, action type, and network message ID. This can be used to investigate potential phishing attempts or malicious link clicks within the Teams environment.
Detects inbound emails originating from 'azure-noreply@microsoft.com' with subjects that typically indicate financial transactions (e.g., 'Invoice Paid', 'Payment Reference') or system alerts (e.g., 'MemorySpike', 'DiskFull'). This pattern could be indicative of phishing attempts leveraging a seemingly legitimate sender to trick recipients.
This rule detects instances where a user clicks on a URL in an email, and the final redirected URL is hosted on 'workers.dev', which is often abused for phishing campaigns, particularly OAuth device code phishing. It correlates email delivery events with URL click events and analyzes the full redirect chain to identify the final destination.
This rule detects inbound emails with an SVG attachment that is disguised as an HTML file and contains a long, base64-like string in its filename. This pattern is often used in phishing campaigns to bypass traditional email filters and deliver malicious content, potentially leading to credential harvesting or malware delivery. The rule specifically looks for files with a '.svg' extension but a 'html' file type, combined with a filename containing a string of at least 20 alphanumeric characters, plus or minus, equal signs, which is characteristic of base64 encoding.
Detects mass device wipe, retire, or delete operations performed via Microsoft Intune, inspired by the Stryker/Handala attack. This rule combines five detection signals: static velocity threshold, bulk destructive actions from a single operator, first-time operator detection, UEBA anomaly correlation, and ML anomaly detection. Operations are categorized into Tier 1 (critical, zero baseline activity like wipe/retire) and Tier 2 (high, legitimate IT ops activity like device delete, subject to velocity and ML thresholds). Severity escalates based on the number of overlapping signals.
This rule detects emails containing a specific URL (https://openclaw.ai/install.ps1) which is known to host a PowerShell script. This indicates a potential attempt to deliver malicious code via email, likely as part of a phishing campaign to execute the script on the recipient's system.
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