Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
123 detections
Filters
Last updated
All Time
Detection languages
42
41
26
7
4
Contributors
40
34
15
7
5
Categories
41
34
32
19
19
Platforms
74
31
9
8
4
Products / Services
10,680
9,761
6,694
4,418
3,744
MITRE Techniques
47
29
29
28
26
CVEs
2
2
1
1
1
IDS Classtypes
11
10
5
IDS Protocols
26
The analytic detects an Azure AD account with concurrent sessions originating from multiple unique IP addresses within a 5-minute window. It leverages Azure Active Directory NonInteractiveUserSignInLogs to identify this behavior by analyzing successful authentication events and counting distinct source IPs. This activity is significant as it may indicate session hijacking, where an attacker uses stolen session cookies to access corporate resources from a different location. If confirmed malicious, this could lead to unauthorized access to sensitive information and potential data breaches.
The following analytic detects suspicious database file and directory discovery activities, which may signal an attacker attempt to locate and assess critical database assets on a compromised system. This behavior is often a precursor to data theft, unauthorized access, or privilege escalation, as attackers seek to identify valuable information stored in databases. By monitoring for unusual or unauthorized attempts to locate database files and directories, this analytic aids in early detection of potential reconnaissance or data breach efforts, enabling security teams to respond swiftly and mitigate the risk of further compromise.
The analytic identifies potential lateral movement activities within an organization's Active Directory (AD) environment by correlating multiple analytics from the Active Directory Lateral Movement analytic story within a specified time frame. This is significant for a SOC as lateral movement is a common tactic used by attackers to expand their access within a network, posing a substantial risk. If confirmed malicious, this activity could allow attackers to escalate privileges, access sensitive information, and persist within the environment, leading to severe security breaches.
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 analytic identifies AWS console login attempts by users from a new region. It leverages AWS CloudTrail events and compares current login regions against a baseline of previously seen regions for each user. This activity is significant as it may indicate unauthorized access attempts or compromised credentials. If confirmed malicious, an attacker could gain unauthorized access to AWS resources, potentially leading to data breaches, resource manipulation, or further lateral movement within the cloud environment.
This analytic detects file transfers flagged as malware that occurred over non-standard ports (other than 80 and 443) from Cisco Secure Firewall Threat Defense logs. Adversaries may attempt to bypass protocol-based detection or use alternate ports to blend in with other traffic. This analytic identifies these non-conventional flows and surfaces potential evasion techniques. If confirmed malicious, this indicates potential malware delivery or other nefarious activity.
The analytic identifies a successful single-factor authentication event against Azure Active Directory. It leverages Azure SignInLogs data, specifically focusing on events where single-factor authentication succeeded. This activity is significant as it may indicate a misconfiguration, policy violation, or potential account takeover attempt. If confirmed malicious, an attacker could gain unauthorized access to the account, potentially leading to data breaches, privilege escalation, or further exploitation within the environment.
The following analytic detects `spoolsv.exe` writing a `.dll` file, which is unusual behavior and may indicate exploitation of vulnerabilities like CVE-2021-34527 (PrintNightmare). This detection leverages Sysmon EventID 11 to monitor file creation events in the `\spool\drivers\x64\` directory. This activity is significant because `spoolsv.exe` typically does not write DLL files, and such behavior could signify an ongoing attack. If confirmed malicious, this could allow an attacker to execute arbitrary code, escalate privileges, or maintain persistence on the compromised system.
The following analytic detects a suspicious registry modification aimed at disabling security audit logs by adding a specific registry entry. It leverages data from the Endpoint.Registry data model, focusing on changes to the "Control\\MiniNt" registry path. This activity is significant because it can prevent Windows from logging any events to the Security Log, effectively blinding security monitoring efforts. If confirmed malicious, this technique could allow an attacker to operate undetected, making it difficult to trace their actions and compromising the integrity of security audits.
This analytic identifies potential privilege escalation activities within an organization's Active Directory (AD) environment by correlating multiple analytics from the "Active Directory Privilege Escalation" analytic story within a specified time frame. This is significant for a SOC as it helps identify coordinated attempts to gain elevated privileges, which could indicate a serious security threat. If confirmed malicious, this activity could allow attackers to gain unauthorized access to sensitive systems and data, leading to potential data breaches and further compromise of the network.
This analytic identifies failed authentication attempts against an Azure AD tenant during the Multi-Factor Authentication (MFA) challenge, specifically flagged by error code 500121. It leverages Azure AD SignInLogs to detect these events. This activity is significant as it may indicate an adversary attempting to authenticate using compromised credentials on an account with MFA enabled. If confirmed malicious, this could suggest an ongoing effort to bypass MFA protections, potentially leading to unauthorized access and further compromise of the affected account.
The analytic detects an Azure AD account successfully authenticating from multiple unique IP addresses within a 30-minute window. It leverages Azure AD SignInLogs to identify instances where the same user logs in from different IPs in a short time frame. This behavior is significant as it may indicate compromised credentials being used by an adversary, potentially following a phishing attack. If confirmed malicious, this activity could allow unauthorized access to corporate resources, leading to data breaches or further exploitation within the network.
This analytic detects an unusual number of NTLM authentication attempts by a single user account against multiple distinct destinations. This behavior is indicative of an attacker performing brute-force attacks, password spraying, or other NTLM-based authentication attacks to gain access to numerous domain-joined Windows devices. Such activity may also generate a high volume of Event ID 4776 events.
This analytic detects the execution of the 'shred' command on a Linux machine, which is used to overwrite files to make them unrecoverable. It leverages data from Linux Auditd, focusing on process names and command-line arguments. This activity is significant because the 'shred' command can be used in destructive attacks, such as those seen in the Industroyer2 malware targeting energy facilities. If confirmed malicious, this activity could lead to the permanent destruction of critical files, severely impacting system integrity and data availability.
The following analytic identifies a source host failing to authenticate against a remote host with multiple users, potentially indicating a Password Spraying attack. It leverages Windows Event 4625 (failed logon attempts) and Logon Type 3 (remote authentication) to detect this behavior. This activity is significant as it may represent an adversary attempting to gain initial access or elevate privileges within an Active Directory environment. If confirmed malicious, this could lead to unauthorized access, privilege escalation, and further compromise of the network.
The following analytic identifies the creation and quick deletion of a Domain Controller (DC) object within 30 seconds in an Active Directory environment, indicative of a potential DCShadow attack. This detection leverages Windows Security Event Codes 5137 and 5141, analyzing the duration between these events. This activity is significant as DCShadow allows attackers with privileged access to register a rogue DC, enabling unauthorized changes to AD objects, including credentials. If confirmed malicious, this could lead to unauthorized AD modifications, compromising the integrity and security of the entire domain.
This analytic detects executables running from public or temporary locations that are communicating over Windows domain authentication ports/protocols such as LDAP (389), LDAPS (636), and Kerberos (88). It leverages network traffic data to identify processes originating from user-controlled directories. This activity is significant because legitimate applications rarely run from these locations and attempt domain authentication, making it a potential indicator of compromise. If confirmed malicious, attackers could leverage this to access domain resources, potentially leading to further exploitation and lateral movement within the network.
Detects the usage of specific LDAP attributes ('primaryInternationalISDNNumber', 'otherFacsimileTelephoneNumber', 'primaryTelexNumber') that are known to be used by the LDAPFragger tool for data exchange via LDAP. These attributes are generally not commonly used in enterprise environments, making their appearance suspicious and indicative of potential Command and Control activity.
Page 6 of 6