Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects spoofed emails carrying a .patch attachment sent to a GitLab incoming-email merge-request address. Requires Microsoft's composite authentication verdict (CompAuth: fail) -- a lower-noise spoofing signal than raw SPF/DKIM/DMARC -- and excludes sender/recipient pairs already seen corresponding with that token address in the prior 30 days to suppress recurring legitimate contributors.
Detects spoofed emails carrying a .patch attachment sent to a GitLab incoming-email merge-request address. Requires Microsoft's composite authentication verdict (CompAuth: fail) -- a lower-noise spoofing signal than raw SPF/DKIM/DMARC -- and excludes sender/recipient pairs already seen corresponding with that token address in the prior 30 days to suppress recurring legitimate contributors.
This rule detects activity related to specific known fabricated news infrastructure domains and associated social media handles, which are indicative of influence operations. It monitors network connection events, email URL clicks, email communication patterns involving these domains, and process executions that reference these specific accounts or handles.
This rule monitors for network and email activity associated with known fraudulent AI reseller infrastructure. It aggregates data from device network connections, email URL inspections, and email header analysis to identify potential interactions with malicious domains known to facilitate AI-related fraud.
This rule identifies emails containing URLs associated with known suspicious or malicious domains (secboxes.com, msbenefit.com, attcdn.com, brianwilli.com). It filters for instances where the sender's domain is not one of the identified suspicious domains to reduce noise from potential email spoofing or miscategorized communications, flagging potential phishing attempts.
Detects HTML phishing lures associated with the GhostCode kit, which utilizes obfuscation techniques such as zero-font-size <ins> tags and injected HTML comments between characters to bypass static and NLP-based security analysis.
Detects phishing emails impersonating 'Veltrix Capital' that lure developers into running, debugging, or cloning repositories, often disguised as technical assessment or job-related tasks involving cryptocurrency or blockchain themes.
Detects network activity and HTTP request headers associated with the GhostCode phishing kit. The rule identifies specific URI patterns, custom site keys, malicious User-Agent strings, and session cookie artifacts indicative of interaction with a phishing server.
This rule detects potential OAuth token theft resulting from device code phishing (e.g., N0va phishkit). It monitors for a successful OAuth device-code authentication followed within 5 minutes by a secondary successful sign-in for the same user from a different IP address, different browser client, or different user agent, which is a common indicator of an adversary-in-the-middle (AiTM) session hijacking attempt.
Detects anomalous activity associated with OAuth 2.0 device code phishing campaigns. The rule identifies accounts showing frequent device code authentication attempts, including successful logins from potentially unmanaged or unrecognized devices, which is consistent with the behavior of phishing kits targeting OAuth device grant flows.
Detects downstream delivery of likely AI-paraphrased mass-produced lure content by identifying bursts of near-duplicate subject lines from newly-seen domains with auth failures.
Detects downstream delivery of likely AI-paraphrased mass-produced lure content by identifying bursts of near-duplicate subject lines from newly-seen domains with auth failures.
This rule monitors for user interactions with specific domains and URLs known to be associated with suspicious or malicious activity. It aggregates data from multiple sources, including email clicks (UrlClickEvents), device network activity (DeviceNetworkEvents), device browser events (DeviceEvents), and DNS queries (DnsEvents), to identify potential exposure to these indicators of compromise.
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.
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 email or web proxy traffic containing a lure themed around 'Confluence', combined with a redirect or link to Telegram, and specifically containing Cyrillic character sets. This combination is often indicative of targeted phishing campaigns using social engineering lures to redirect users to external messaging platforms for further interaction or credential harvesting.
This rule monitors email, SMS, and voice logs for potential phishing attempts targeting user credentials. It specifically looks for social engineering lures related to passkey, SSO, or MFA updates that express urgency or imply service expiration, often masquerading as IT support communications.
Detects a sequence of events indicative of an Adversary-in-the-Middle (AiTM) attack, specifically 'NovaCookies'. The rule identifies a phishing email lure (DocuSign/SharePoint-themed) received by a user, followed within a 6-hour window by an anomalous Microsoft 365 sign-in from that same user. The anomalous sign-in is defined by either risk flags or conditional access failure, suggesting potential replay of a captured session cookie.
Detects a suspicious web navigation pattern indicative of NovaCookies or similar AiTM (Adversary-in-the-Middle) phishing infrastructure. The rule correlates a legitimate website visit with an immediate subsequent request to a .vu domain, within a short time window (30 seconds), using the same process (e.g., browser process). This identifies the redirect chain from a legitimate host to a disposable phishing landing page commonly used for credential harvesting.
Detects a potential Adversary-in-the-Middle (AiTM) attack sequence by correlating OneDrive/SharePoint document sharing email lures with subsequent successful Microsoft 365 sign-ins from unusual locations or user agents within a short time window. This activity often indicates session cookie theft and MFA bypass.
Detects phishing emails purportedly from Docusign that contain malicious links which redirect users through legitimate identity provider domains (e.g., login.microsoftonline.com, accounts.google.com) before landing on non-trusted infrastructure. This redirect-chain pattern is indicative of NovaCookies Adversary-in-the-Middle (AiTM) delivery, used to facilitate credential or session cookie theft.
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