Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
608 detections
Filters
Last updated
All Time
Detection languages
346
84
61
42
40
Contributors
155
87
50
48
42
Categories
348
215
150
124
82
Platforms
197
190
120
88
75
Products / Services
169
92
45
44
43
MITRE Techniques
18,123
15,639
12,581
8,394
6,215
CVEs
10
5
1
1
1
IDS Classtypes
35
4
4
3
IDS Protocols
35
6
1
1
'Identifies IPs with failed attempts to sign in to one or more disabled accounts signed in successfully to another account.
To use this analytics rule, make sure you have deployed the [ASIM normalization parsers](https://aka.ms/ASimAuthentication)'
To use this analytics rule, make sure you have deployed the [ASIM normalization parsers](https://aka.ms/ASimAuthentication)'
'User account failed to logon in current period. Excludes Windows Sign in attempts and limits to only more than 10 failed logons or 3 different IPs used. Results may indicate a potential malicious use of an account that is rarely used.'
'Identifies when 100 or more failed attempts by a given user in 10 minutes occur on the IIS Server.
This could be indicative of attempted brute force based on known account information.
This could also simply indicate a misconfigured service or device.
References:
IIS status code mapping - https://support.microsoft.com/help/943891/the-http-status-code-in-iis-7-0-iis-7-5-and-iis-8-0
Win32 Status code mapping - https://msdn.microsoft.com/library/cc231199.aspx'
This could be indicative of attempted brute force based on known account information.
This could also simply indicate a misconfigured service or device.
References:
IIS status code mapping - https://support.microsoft.com/help/943891/the-http-status-code-in-iis-7-0-iis-7-5-and-iis-8-0
Win32 Status code mapping - https://msdn.microsoft.com/library/cc231199.aspx'
'Identifies when failed logon attempts are 20 or higher during a 10 minute period (2 failed logons per minute minimum) from valid account.'
Sample query to detect If there are more then 3 failed logon authentications on high value assets.
Update DeviceName to reflect your high value assets.
For questions @MiladMSFT on Twitter or milad.aslaner@microsoft.com.
Update DeviceName to reflect your high value assets.
For questions @MiladMSFT on Twitter or milad.aslaner@microsoft.com.
Query #1: Look for public IP addresses that failed to logon to a computer multiple times, using multiple accounts, and eventually succeeded.
This rule detects a sequence of multiple failed login attempts (more than 4) followed by a successful login for the same user on the same hostname within a 15-minute window. It specifically targets Windows login events (event IDs 4625 for failure and 4624 for success) and correlates them with user and asset entity data, focusing on users in the 'Domain Admins' group and assets that are 'Domain Controllers'. This pattern is indicative of a brute-force attack or password guessing attempt that eventually succeeded.
This rule detects a pattern of multiple failed login attempts followed by a successful login for the same user on the same hostname within a 15-minute window. This behavior is indicative of a brute-force attack or password guessing attempt that eventually succeeded.
Detects failed logon attempts from clients with external network IP to an MSSQL server. This can be a sign of a bruteforce attack.
Detects failed logon attempts to MSSQL server instances, which can indicate brute-force attacks, password guessing, or credential stuffing attempts against database accounts. This rule specifically looks for Event ID 18456 from MSSQL providers in the Windows Application event log.
Detects failed logon attempts from clients with external network IP to an MSSQL server. This can be a sign of a bruteforce attack.
Detects failed logon attempts from clients to MSSQL server.
This correlation rule identifies when a user exceeds a predefined risk threshold based on multiple suspicious Okta activities within a 24-hour period. It aggregates risk events from "Suspicious Okta Activity," "Okta Account Takeover," and "Okta MFA Exhaustion" analytic stories. The detection is significant as it highlights potentially compromised user accounts exhibiting multiple tactics, techniques, and procedures (TTPs). If confirmed malicious, this activity could indicate a serious security breach, allowing attackers to gain unauthorized access, escalate privileges, or persist within the environment.
The analytic detects attempts to authenticate using the built-in local Administrator account across more than 30 endpoints within a 5-minute window. It leverages Windows Event Logs, specifically events 4625 (failed logon) and 4624 (successful logon), to identify this behavior. This activity is significant as it may indicate an adversary attempting to validate stolen local credentials across multiple hosts, potentially leading to privilege escalation. If confirmed malicious, this could allow the attacker to gain widespread access and control over numerous systems within the network, posing a severe security risk.
The following analytic detects a single source endpoint failing to authenticate with 30 unique invalid users using the NTLM protocol. It leverages EventCode 4776 from Domain Controller logs, focusing on error code 0xC0000064, which indicates non-existent usernames. This behavior is significant as it may indicate a Password Spraying attack, where an adversary attempts to gain initial access or elevate privileges. If confirmed malicious, this activity could lead to unauthorized access, privilege escalation, and potential compromise of sensitive information within the Active Directory environment.
The following analytic detects CrowdStrike alerts for admin weak password policy violations, identifying instances where administrative passwords do not meet security standards. These alerts highlight significant vulnerabilities that could be exploited by attackers to gain unauthorized access. Promptly addressing these alerts is crucial for maintaining robust security and protecting critical systems and data from potential threats.
The analytic identifies an Azure AD account experiencing more than 20 failed authentication attempts within a 10-minute window. This detection leverages Azure SignInLogs data, specifically monitoring for error code 50126 and unsuccessful authentication attempts. This behavior is significant as it may indicate a brute force attack targeting the account. If confirmed malicious, an attacker could potentially gain unauthorized access, leading to data breaches or further exploitation within the environment. Security teams should adjust the threshold based on their specific environment to reduce false positives.
The following analytic detects CrowdStrike alerts for weak password policy violations, identifying instances where passwords do not meet the required security standards. These alerts highlight potential vulnerabilities that could be exploited by attackers, emphasizing the need for stronger password practices. Addressing these alerts promptly helps to enhance overall security and protect sensitive information from unauthorized access.
The following analytic detects multiple Okta accounts being locked out within a short period. It uses the user.account.lock event from Okta logs, aggregated over a 5-minute window, to identify this behavior. This activity is significant as it may indicate a brute force or password spraying attack, where an adversary attempts to guess passwords, leading to account lockouts. If confirmed malicious, this could result in potential account takeovers or unauthorized access to sensitive Okta accounts, posing a significant security risk.
This analytic identifies user accounts experiencing an excessive number of lockouts within a short timeframe. It leverages the 'Change' data model, specifically focusing on events where the result indicates a lockout. This activity is significant as it may indicate a brute-force attack or misconfiguration, both of which require immediate attention. If confirmed malicious, this behavior could lead to account compromise, unauthorized access, and potential lateral movement within the network.
This analytic detects endpoints that generate a high number of account lockouts within a short timeframe. It analyzes Windows security event logs, specifically the `Change` datamodel's `Account_Management` node, to count lockout events. This activity can indicate a brute-force attack or a misconfigured system causing repeated authentication failures. If malicious, it could lead to denial of service through account lockouts or signal an ongoing attempt to compromise user credentials.
Page 26 of 29