Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

4,308 detections

This rule detects HTTP responses that contain content indicative of a survey lure page used for information gathering. It specifically looks for the presence of keywords such as 'survey', 'name', 'email', and 'company' within the HTTP response body, suggesting an attempt to collect personal or organizational information.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
001
This rule detects potential MFA OTP phishing pages by inspecting HTTP URIs for the presence of both 'verify' and 'otp' keywords, case-insensitively. This combination in a URI is indicative of a page designed to trick users into submitting their One-Time Passwords (OTPs) for multi-factor authentication.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
001
This rule detects a password spraying attack targeting LDAP services. It triggers an alert if there are 50 or more TCP connections to port 389 (LDAP) on the home network within a 60-second window, originating from the same destination IP address. This pattern is indicative of an attacker attempting to authenticate with a small set of passwords against many accounts.
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Darshan Thummar@Mighty
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Detections.ai Community
5 months ago
001
This rule detects potential GitHub token theft or abuse activity by identifying GitHub tokens that are used from an unusually high number of distinct IP addresses or for an unusually high number of uses within a one-hour window. Specifically, it looks for tokens with more than 5 uses and more than 2 distinct IP addresses in an hour. This behavior could indicate that a compromised token is being used by an attacker from multiple locations or in an automated fashion.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
006
This rule detects suspicious NTLM network or remote interactive logon activity. It specifically looks for multiple distinct accounts logging in from the same device and remote IP address within a one-hour window, using NTLM authentication via NtLmSsp or Seclogon processes. This pattern can indicate credential stuffing, NTLM relay attacks, or other forms of credential misuse.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
006
This rule detects the execution of known credential dumping tools, Mimikatz and ProcDump, when specific command-line arguments associated with credential extraction from LSASS are used. It specifically looks for `mimikatz.exe` or `procdump.exe` combined with arguments like `sekurlsa`, `logonpasswords`, or `-ma` which are commonly used to dump credentials from memory.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
306
Detects inbound emails containing Mailchimp click-tracking links that redirect to ActiveCampaign landing pages, a known ESP chaining technique used to obscure credential harvesters. This technique is often used in phishing campaigns to bypass email security controls.
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Ethan Andrews@eandrews
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Federal Signal Detections
5 months ago
407
Identifies suspicious token authorizations for the Google Chrome OAuth client. Tycoon 2FA operators frequently use this specific client and scope to proxy authentications and capture session cookies. In a complete attack sequence, this event occurs within a 1-second window alongside a login_success and a device registration event.
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Duo Tech@duotech
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Detections.ai Community
5 months ago
7012
Detects Node.js or Bun processes accessing sensitive developer configuration directories such as .ssh and .npmrc, indicating potential credential harvesting. This rule specifically looks for file access or open events initiated by 'node.exe', 'node', 'bun.exe', or 'bun' processes targeting paths containing '.ssh' or '.npmrc', or files named '.npmrc'.
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Brandon Rodriguez@BMRodriguez
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Detections.ai Community
5 months ago
1011
This rule detects suspicious activity related to OpenSSL or certificate manipulation by identifying processes that execute commands containing 'openssl' or 'certificate' keywords. It aggregates these activities by computer and account within one-hour bins and flags if three or more such activities occur, which could indicate credential access attempts or system misconfiguration.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
000
Identifies node.js or npm processes attempting to access known credential stores or execute credential dumping utilities, which may indicate the presence of the Miasma credential-stealing worm.
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Brandon Rodriguez@BMRodriguez
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Detections.ai Community
5 months ago
3011
Detects attempts to read common HashiCorp Vault token paths from the filesystem, indicating potential credential harvesting by malware like Miasma stealer.
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Tim Peck@timpeck
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Detections.ai Community
5 months ago
409
Detects suspicious activity involving multiple password resets for different users initiated by a single user within a one-hour timeframe in Azure AD. This could indicate an attacker attempting to gain control over multiple accounts.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
000
This rule detects when a user account assigns a 'Global Administrator' or 'Owner' role from multiple distinct IP addresses within a one-hour window. This behavior can indicate a compromised account being used to escalate privileges or establish persistence from different locations.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
205
Detects ServiceAccount-based enumeration of sensitive Kubernetes resources. This rule identifies when a Kubernetes ServiceAccount performs a high volume of 'get', 'list', or 'watch' operations on sensitive resources such as secrets, pods, nodes, namespaces, or other role-related resources. It specifically flags activity with 'secrets' as high severity.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
5 months ago
4010
Detects modified PAM modules or ELF files implementing PAM backdoors for credential interception, as seen in Ebury and QLNX, whihc uses Rootkit techniques.
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Danny Y@zendannyy
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Detections.ai Community
5 months ago
006
Detects sign-in or Microsoft Graph API activity using user-agent strings characteristic of ROADtools and similar Python-based identity-attack tooling. The rule generalizes beyond ROADtools to catch AzureHound, MicroBurst, MFASweep, GraphRunner, and similar identity attack frameworks by looking for scripting user-agents (python, requests, urllib, curl) which signal non-browser, non-app authentication that is inherently suspicious for Entra ID admin operations.
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Tim Peck@timpeck
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Detections.ai Community
5 months ago
291289
Detects suspicious Kubernetes Role-Based Access Control (RBAC) changes that grant elevated privileges, such as 'cluster-admin' roles, wildcard permissions for verbs, resources, or API groups, or direct access to secrets or service accounts. This rule monitors 'create', 'update', and 'patch' operations on roles, clusterroles, rolebindings, and clusterrolebindings within Kubernetes audit logs.
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Daniel Jeremiah@daniyyell
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Detections.ai Community
5 months ago
408
Detects PowerShell script block telemetry (Event ID 4104) containing P/Invoke declarations targeting advapi32.dll's CredEnumerate function or related Credential Manager APIs (CredRead, CredWrite). This technique bypasses standard cmdlets that may be monitored or restricted, providing direct API access to stored Windows credentials including RDP sessions, web service credentials, and enterprise application tokens. Generalizes well beyond specific campaigns to most PowerShell credential-theft families.
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Tim Peck@timpeck
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Detections.ai Community
5 months ago
60367
This rule detects a high volume (50 or more) of failed authenticated SMTP login attempts to Office 365 Exchange Online from a single IP address within a 24-hour period. The failures are specifically for error codes 50126 (invalid username or password) or 50053 (account locked). This pattern is indicative of a brute-force or password-guessing attack against Exchange Online accounts.
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Dulitha Wickramasinghe@dulitha99
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Detections.ai Community
5 months ago
220221
This rule detects a highly suspicious sequence of events in Microsoft Entra ID (formerly Azure AD) audit logs: a self-service password reset, followed by the registration of new security information, and then the deletion of existing security information, all performed by the same user within a short time window. This pattern is indicative of an attacker taking over an account, resetting the password, establishing their own MFA/security info, and then removing the legitimate user's security info to lock them out. This behavior has been observed in campaigns like Storm-2949.
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Bryant Smith@flowstate
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Detections.ai Community
5 months ago
352609
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