Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,064 detections
Filters
Last updated
All Time
Detection languages
597
173
103
71
51
Contributors
184
155
139
90
73
Categories
20,443
11,831
5,875
5,151
4,864
1,064
Platforms
575
266
228
223
118
Products / Services
498
220
130
118
86
MITRE Techniques
488
451
363
349
341
CVEs
10
5
4
3
2
IDS Classtypes
34
3
2
2
1
IDS Protocols
29
9
1
Okta ThreatInsight detects access requests from known malicious IPs targeting a specific org.
Detects user logins for same user from different cities within 24 hours.
Okta Mismatch Between Source and Response for Verify Push Request
Detects multiple failed requests to access applications
Okta's ThreatInsight can identify Password Spray attacks.
Detects when an adversary attempts to reuse a stolen web session cookie in a different device that has a different OS, IP, Browser or User Agent.
Detects user logins for the same user from different cities within 24 hours.
Detects potential exploitation attempts of the Netlogon Elevation of Privilege Vulnerability (CVE-2020-1472), also known as Zerologon. This rule specifically looks for Event ID 4742 (A computer account was changed) where the SubjectUserName is 'ANONYMOUS LOGON' and the TargetUserName matches a Domain Controller's machine account name (ending with '$'), while filtering out legitimate password changes by checking if 'PasswordLastSet' is not '-'.
This rule detects the use of the OAuth 2.0 device code authentication flow within an environment. While legitimate for input-constrained devices, its presence in other scenarios warrants investigation as it could indicate a misconfigured application or malicious activity. The rule specifically looks for "Device Code" in Azure sign-in logs.
This rule identifies sign-in attempts from geographically distant locations within a short timeframe, which is indicative of an "impossible travel" scenario. It also considers if one of these locations is atypical for the user based on their past behavior. This pattern often suggests that an attacker has compromised user credentials and is attempting to access the account from a new, unusual location, potentially using a VPN or proxy service to mask their true origin.
This rule identifies 'impossible travel' events where a user's activities originate from geographically distant locations within a time period that is too short for physical travel between those locations. This often indicates a compromised account being accessed from multiple locations simultaneously or in rapid succession, potentially using different IP addresses or devices.
This rule detects attempts to coerce authentication using the PetitPotam technique. It specifically looks for Windows Security Event ID 5145, which indicates a network share access, where the ShareName starts with '\\' and ends with '\IPC$', the RelativeTargetName is 'lsarpc', and the SubjectUserName is 'ANONYMOUS LOGON'. This combination of events is indicative of a PetitPotam attack attempting to force a domain controller to authenticate to a malicious server.
Detects the use of NTLMv1 for authentication between a client and server. NTLMv1 is an insecure authentication protocol due to its susceptibility to brute-force attacks against its underlying encryption algorithms. This rule identifies events logged by the LsaSrv provider indicating NTLMv1 usage.
This rule detects the use of the Resource Owner Password Credentials (ROPC) authentication flow. ROPC is generally discouraged because it requires applications to directly handle user credentials, increasing the risk of credential compromise. While it can be used for automated testing or legacy applications, its presence in other contexts may indicate a security weakness or an attempt to bypass more secure authentication mechanisms.
This rule detects an anomaly in the SAML token issuer, indicating a potential compromise of the SAML token. The detection is triggered when the 'riskEventType' is 'tokenIssuerAnomaly', suggesting that the claims within the token are unusual or align with known attacker patterns. This could signify an adversary forging web credentials, specifically SAML tokens, to gain unauthorized access.
Detects sign-in attempts with properties (e.g., device, location, browser) that are unusual or unfamiliar compared to a user's past sign-in history. This rule leverages Azure AD Identity Protection's risk detection capabilities to identify anomalous sign-ins.
This rule detects anomalous token characteristics, such as an unusual token lifetime or a token being used from an unfamiliar location. This indicates potential compromise or misuse of identity tokens.
Detects logon events (Event ID 4672 and 4964) involving accounts with special privileges or belonging to special groups, such as administrators. The rule filters out the local system account (S-1-5-18) and allows for a configurable filter for valid internal accounts to reduce false positives.
This rule detects sign-in attempts originating from IP addresses that have been identified as infected with malware. These malware-infected IP addresses are known to actively communicate with bot servers, indicating a high risk of compromise or malicious activity associated with the sign-in.
This rule identifies user sign-ins originating from anonymous IP addresses, which may indicate the use of VPNs, Tor, or other anonymization services. Such activity can be a sign of an adversary attempting to mask their true location or identity during an access attempt.
This rule detects sign-in attempts originating from IP addresses that Microsoft Entra ID Protection has identified as malicious. These IP addresses are known to be associated with attackers or compromised systems at the time of the sign-in, indicating a high-risk authentication attempt.
Page 50 of 51