Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects phishing emails that impersonate Adobe Acrobat Sign or DocuSign using invoice or RFP-themed lures. The rule identifies suspicious emails by checking for brand-related keywords in the subject and display name, identifying links that do not lead to legitimate signing domains, and identifying senders that are impersonating a brand or are newly seen in the environment.
Detects phishing emails that impersonate Adobe Acrobat Sign or DocuSign using invoice or RFP-themed lures. The rule identifies suspicious emails by checking for brand-related keywords in the subject and display name, identifying links that do not lead to legitimate signing domains, and identifying senders that are impersonating a brand or are newly seen in the environment.
Detects phishing emails that impersonate Adobe Acrobat Sign or DocuSign using invoice or RFP-themed lures. The rule identifies suspicious emails by checking for brand-related keywords in the subject and display name, identifying links that do not lead to legitimate signing domains, and identifying senders that are impersonating a brand or are newly seen in the environment.
Detects phishing emails that impersonate Adobe Acrobat Sign or DocuSign using invoice or RFP-themed lures. The rule identifies suspicious emails by checking for brand-related keywords in the subject and display name, identifying links that do not lead to legitimate signing domains, and identifying senders that are impersonating a brand or are newly seen in the environment.
This rule detects high-confidence phishing emails that were delivered to either the Inbox or Junk folder. It explicitly filters out messages that have been explicitly allowed by organization-level policies, user-level actions, or specific safe-sender bypass mechanisms, ensuring the alert focuses on malicious emails that bypassed standard security filters without an authorized exception.
Detects a suspected EvilTokens attack sequence where a user clicks a phishing URL and subsequently initiates a browser session to the Microsoft device-code authorization page (devicelogin) within 15 minutes, with the phishing lure domain appearing in the browser context.
Detects a multi-stage phishing redirect chain used in 'EvilTokens' attacks. The rule identifies communication with common serverless hosting platforms (Vercel, Cloudflare Workers, AWS Lambda/Execute-API) followed by interaction with anti-bot/CAPTCHA gates (Cloudflare Turnstile, hCaptcha, Google reCAPTCHA) and finally reaching known Microsoft device code phishing endpoints (/devicelogin or /common/oauth2/deviceauth).
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
This rule detects potentially malicious messages within Microsoft Teams that use common social engineering keywords related to security configuration changes (e.g., passkey, MFA, SSO). The detection specifically filters for users who have successfully logged in within the last 30 days to identify potential compromised accounts acting as internal senders.
This rule detects a multi-stage attack chain targeting a single user within a 2-hour window. It identifies the combination of email bombing (a distraction technique), an incoming external or anonymous Teams call (social engineering channel), and the installation of common remote access tools (e.g., AnyDesk, TeamViewer) on the same host.
This rule detects a multi-stage attack chain targeting a single user within a 2-hour window. It identifies the combination of email bombing (a distraction technique), an incoming external or anonymous Teams call (social engineering channel), and the installation of common remote access tools (e.g., AnyDesk, TeamViewer) on the same host.
This rule detects potential Adversary-in-the-Middle (AiTM) phishing activity by correlating network requests to known malicious lure domains with help-desk or vishing-themed events (such as password resets or unsolicited IT support) for the same user within a one-hour window. This behavior is indicative of a help-desk impersonation campaign where attackers direct users to credential harvesting sites.
Hunts network, HTTP, and email-URL telemetry for known ARToken infrastructure (operator backend IPs and phishing/panel domains). Bounded to a 30-day lookback and tiers matches by confidence: domain hits are high-confidence (attacker-registered infrastructure), while IP hits are medium-confidence since the IPs sit on shared DigitalOcean hosting that can be reassigned to unrelated tenants once ARToken's infrastructure is taken down. Empty/unparsed indicator fields are excluded to avoid spurious matches in the HTTP event parsing branch. No known file hashes are associated with this intel.
This rule detects a multi-stage phishing attack, often referred to as 'quishing'. It identifies incoming emails containing image (JPG, PNG) or PDF attachments that embed previously unseen URLs, correlated with a subsequent sign-in event from a mobile device by the same recipient, which is a common indicator of Adversary-in-the-Middle (AiTM) credential harvesting.
Detects phishing emails containing suspicious URLs pointing to PaaS platforms (Azure Static Web Apps, Cloudflare, Firebase) that exhibit credential harvesting characteristics (branded keywords or base64 patterns). The rule correlates these emails with subsequent clicks and a successful M365 sign-in by the same user within 30 minutes of the click, indicating a probable successful credential compromise.
This rule detects mass phishing campaigns by identifying HTML/HTM email attachments that contain embedded URLs. It monitors for a pattern where the same sender distributes these attachments to multiple recipients, a common behavior for HTML smuggling delivery vectors where malicious payloads are constructed client-side to bypass static email gateway inspection.
Detects proxy requests to typosquatted domains masquerading as major job platforms (LinkedIn, Indeed) that are serving suspicious file extensions (.hta, .ps1) often associated with the 'ClickFix' social engineering technique. This rule monitors for URLs mimicking these brands while attempting to deliver potentially malicious scripts to the user.
Detects incoming EXTERNAL emails containing subject lines indicative of meeting invitations or call records, which include external URLs pointing to non-standard or unverified cloud storage providers, combined with explicit remote-access/support solicitation language. Requiring the remote-access/support signal and excluding internal-to-internal mail narrows this to callback-phishing style lures rather than routine meeting correspondence.
Detects high-volume, individually-tailored spear-phishing campaigns likely assisted by Generative AI. The rule monitors for a single sender targeting a high number of unique recipients with distinct, non-identical email subjects within a short timeframe. It specifically flags activity involving newly registered look-alike domains and interactions with credential-harvesting patterns in URLs.
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