Detections

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

983 detections

This rule detects an unusual number of local or remote interactive logons (LogonType 2 or 10) by the 'SYSTEM' account within a one-hour window. While the SYSTEM account is legitimate, direct interactive logons are rare and multiple occurrences could indicate an attempt to escalate privileges or maintain persistence by an attacker.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
006
This rule detects potential Pass-the-Hash (PtH) attacks by looking for multiple successful network logons (LogonType 3) using NTLM authentication for the same user from the same IP address. A count of 5 or more such events is considered suspicious.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
308
This rule detects potential 'impossible travel' scenarios within Azure AD sign-in logs. It identifies users who successfully sign in to Office 365 from two geographically distant IP addresses within a one-hour window, suggesting a potential compromise or an attempt to bypass security controls.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
007
This rule detects an unusually high volume of logon events (both successful and failed) or a large number of unique users attempting to log on within a 5-minute window. This behavior is indicative of potential brute-force attacks or credential stuffing attempts against Windows systems.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
106
This rule detects an unusually high volume (5 or more within an hour) of successful logons by 'SYSTEM' or 'LOCAL SERVICE' accounts. While these are legitimate system accounts, a sudden surge in their logon activity could indicate unusual system behavior, potential compromise, or misconfiguration leading to excessive system account usage.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
004
This rule detects potential lateral movement activity by identifying a single user account attempting to log on to five or more distinct computers with at least ten logon attempts within a five-minute window. It specifically looks for successful logons (EventID 4624) with network, remote interactive, or remote desktop logon types (LogonType 3, 9, 10) and excludes machine accounts (TargetUserName not ending with '$'). This pattern can indicate an adversary attempting to spread across the network using compromised credentials.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
005
This rule detects an account performing multiple interactive logons (LogonType 2) from at least 3 unique IP addresses within a 5-minute window. This behavior can indicate credential compromise or an adversary attempting to move laterally or access multiple systems using stolen credentials.
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Ankit Mehta@Secvyn
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Detections.ai Community
4 months ago
001
This rule detects unusual logon activity for service accounts. It identifies service accounts by looking for a dollar sign ($) at the end of the username. The rule then counts logons, unique IP addresses, and unique computers for these service accounts within one-hour bins. An alert is triggered if a service account has 10 or more logons or logs in from 5 or more unique IP addresses within that hour, indicating potential abuse or compromise.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
004
This rule detects potential Pass-the-Hash (PtH) attacks by looking for multiple successful network logons (LogonType 3) using NTLM authentication for the same user from the same IP address. A count of 5 or more such events is considered suspicious.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
003
This rule detects an unusually high volume of logon events (both successful and failed) or a large number of unique users attempting to log on within a 5-minute window. This behavior is indicative of potential brute-force attacks or credential stuffing attempts against Windows systems.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
002
This rule detects potential lateral movement activity by identifying a single user account attempting to log on to five or more distinct computers with at least ten logon attempts within a five-minute window. It specifically looks for successful logons (EventID 4624) with network, remote interactive, or remote desktop logon types (LogonType 3, 9, 10) and excludes machine accounts (TargetUserName not ending with '$'). This pattern can indicate an adversary attempting to spread across the network using compromised credentials.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
102
This rule detects unusual logon activity for service accounts. It identifies service accounts by looking for a dollar sign ($) at the end of the username. The rule then counts logons, unique IP addresses, and unique computers for these service accounts within one-hour bins. An alert is triggered if a service account has 10 or more logons or logs in from 5 or more unique IP addresses within that hour, indicating potential abuse or compromise.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
5 months ago
002
This rule detects potential 'impossible travel' scenarios within Azure AD sign-in logs. It identifies users who successfully sign in to Office 365 from two geographically distant IP addresses within a one-hour window, suggesting a potential compromise or an attempt to bypass security controls.
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Ankit Mehta@Secvyn
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Detections.ai Community
5 months ago
002
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
Bharat Cyber Guardians
5 months ago
002
This rule detects suspicious device enrollment attempts via Microsoft Intune Company Portal from a country not previously observed in a user's 7-day sign-in history. It identifies two primary patterns: sustained successful sign-ins from a new country, indicating a potential active session and successful device enrollment (High Severity), or Conditional Access Policy (CAP) blocked attempts from a new country, suggesting an attacker probing with stolen credentials (Medium Severity). The detection aims to identify identity theft leading to unauthorized device enrollment.
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Rudra Verma@Rudraverma
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CyberHawk Consultancy
5 months ago
3022
This rule detects suspicious device enrollment attempts via Microsoft Intune Company Portal from a country not previously observed in a user's 7-day sign-in history. It identifies two primary patterns: sustained successful sign-ins from a new country, indicating a potential active session and successful device enrollment (High Severity), or Conditional Access Policy (CAP) blocked attempts from a new country, suggesting an attacker probing with stolen credentials (Medium Severity). The detection aims to identify identity theft leading to unauthorized device enrollment.
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Rudra Verma@Rudraverma
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Detections.ai Community
5 months ago
1012
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 suspicious device enrollment attempts via Microsoft Intune Company Portal from a country not previously observed in a user's 7-day sign-in history. It identifies two primary patterns: sustained successful sign-ins from a new country, indicating a potential active session and successful device enrollment (High Severity), or Conditional Access Policy (CAP) blocked attempts from a new country, suggesting an attacker probing with stolen credentials (Medium Severity). The detection aims to identify identity theft leading to unauthorized device enrollment.
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Rudra Verma@Rudraverma
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CyberHawk Consultancy
5 months ago
007
This rule analyzes historical logon, process, and network activity for a specified device over a configurable lookback period. It aims to validate whether a device, potentially flagged as decommissioned or stale, exhibits a pattern of sporadic, legitimate use (e.g., executive laptops, break-glass machines) rather than continuous or unauthorized activity. The output provides a daily timeline of activity, helping to differentiate between truly dormant assets and those with intermittent, legitimate usage.
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Nicholas Isakson@nisakson2000
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Detections.ai Community
7 months ago
160550
Detect remote login by Administrator user (depending on internal pattern).
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SigmaHQ Detections@sigmaHQ
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SigmaHQ
6 months ago
003
Detect failed attempts to sign in to disabled accounts.
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SigmaHQ Detections@sigmaHQ
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SigmaHQ
6 months ago
002
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