Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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.
Detects web requests to Cloudflare workers.dev subdomains containing specific keywords commonly used in the EvilTokens device code phishing campaign. The rule specifically looks for a pattern like '[lure-type]-[3char-id].[username]-[domain]...workers.dev' to identify malicious URLs.
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.
Identifies web requests to commonly abused PaaS platforms (Cloudflare Workers, Vercel, AWS Amplify) or the Microsoft device login endpoint.
This rule acts as a base to identify specific events for downstream correlation. To properly detect a device code phishing sequence (such as EvilTokens), correlate a PaaS access event followed by a device login event from the same Source IP within a 5-minute window.
This rule acts as a base to identify specific events for downstream correlation. To properly detect a device code phishing sequence (such as EvilTokens), correlate a PaaS access event followed by a device login event from the same Source IP within a 5-minute window.
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.
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.
This detection identifies instances where a user has clicked on a URL within an email and has actively bypassed a security warning page. This behavior is a strong indicator of a successful phishing lure or high-risk user action, as the user has ignored a direct warning about the potential danger of the destination link.
This rule detects network connections or email URLs that contain domains associated with the 'ShinyHunters' threat group's infrastructure. The rule specifically looks for a predefined list of domains known to be used by ShinyHunters for phishing or other malicious activities. It correlates email URL information with device network events to identify potential compromise attempts.
Attackers take advantage of the emojis because they help the content stand out and gets more attention than plain text. It not apply just to Email Subject if not that it also applies to Attachment Files which based on my experience, legitime file not use to have icons in their file names.For example:
📄Invoice.pdf
🔐Reset_Password.html
📦Delivery_Document.zip
This can help find:
- Suspicious files dropped on emails
- Files downloaded from phishing emails
- User-downloaded /opening scam files
- Payloads with social engineering names
📄Invoice.pdf
🔐Reset_Password.html
📦Delivery_Document.zip
This can help find:
- Suspicious files dropped on emails
- Files downloaded from phishing emails
- User-downloaded /opening scam files
- Payloads with social engineering names
This rule detects when a user clicks on a URL that contains a domain identified as malicious. The rule specifically looks for `UrlClickEvents` where the extracted domain from the URL matches any of the domains listed in the `malicious_domains` array. This can indicate a successful phishing attempt or an accidental click on a known malicious link.
Correlates phishing email delivery with subsequent communication to attacker-controlled domains.
Detects incoming emails where a single URL contains indicators of two or more distinct security vendor rewriting services. This technique is used by adversaries to create multi-layered redirect chains to bypass automated scanners and deliver malicious content, as seen in Tycoon2FA and Sneaky2FA campaigns.
This rule detects network connections to specific deep link patterns associated with messaging applications like Telegram, WhatsApp, and Signal. Such deep links can be used in phishing attempts or to initiate actions on a user's device through these applications.
This rule detects network connections to a list of domains identified as associated with phishing activities associated with Crimson Kingsnake. Monitoring these connections can help identify compromised systems or users attempting to access malicious sites.
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