Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,052 detections
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Detects the use of the "capsh" utility to invoke a shell.
'Identifies a list of IP addresses with a minimum number (default of 5) of failed logon attempts to Microsoft Entra ID.
Uses that list to identify any successful remote logons to hosts from these IPs within the same timeframe.'
Uses that list to identify any successful remote logons to hosts from these IPs within the same timeframe.'
Detects execution of inline Python code via the "-c" in order to call the "system" function from the "os" library, and spawn a shell.
Detects the execution of "awk" or it's sibling commands, to invoke a shell using the system() function.
This behavior is commonly associated with attempts to execute arbitrary commands or escalate privileges, potentially leading to unauthorized access or further exploitation.
This behavior is commonly associated with attempts to execute arbitrary commands or escalate privileges, potentially leading to unauthorized access or further exploitation.
Detects the use of the find command to execute a shell. Such behavior may be associated with privilege escalation, unauthorized command execution, or exploitation attempt.
Detects the use of the "flock" command to execute a shell. Such behavior may be associated with privilege escalation, unauthorized command execution, or to break out from restricted environments.
Detects the use of the "gcc" utility to execute a shell. Such behavior may be associated with privilege escalation, unauthorized command execution, or to break out from restricted environments.
Detects the use of the "git" utility to execute a shell. Such behavior may be associated with privilege escalation, unauthorized command execution, or to break out from restricted environments.
Detects the use of the "nice" utility to execute a shell. Such behavior may be associated with privilege escalation, unauthorized command execution, or to break out from restricted environments.
Detects the use of the "ssh" utility to execute a shell. Such behavior may be associated with privilege escalation, unauthorized command execution, or to break out from restricted environments.
This analytic detects suspicious modifications to Unix shell configuration files, such as `.bashrc` or `.profile`, which may indicate an attempt to alter system behavior or gain unauthorized access. Unauthorized changes to these files can be used to execute malicious commands, escalate privileges, or hide malicious activities. By monitoring for unusual or unauthorized modifications to shell configuration files, this analytic helps identify potential security threats, allowing security teams to respond quickly and mitigate risks.
The following analytic detects attempts to stop a service on Linux systems. It leverages data from Linux Auditd. This activity is significant as adversaries often stop or terminate security or critical services to disable defenses or disrupt operations, as seen in malware like Industroyer2. If confirmed malicious, this could lead to the disabling of security mechanisms, allowing attackers to persist, escalate privileges, or deploy destructive payloads, severely impacting system integrity and availability.
The following analytic detects the suspicious auditd service stop. This behavior is critical for a SOC to monitor because it may indicate attempts to gain unauthorized access or maintain control over a system. Such actions could be signs of malicious activity. If confirmed, this could lead to serious consequences, including a compromised system, unauthorized access to sensitive data, or even a wider breach affecting the entire network. Detecting and responding to these signs early is essential to prevent potential security incidents.
The analytic detects cloud API calls executed by user roles that have not previously run these commands. It leverages the Change data model in Splunk to identify commands executed by users with the user_type of AssumedRole and a status of success. This activity is significant because new commands from different user roles can indicate potential malicious activity or unauthorized actions. If confirmed malicious, this behavior could lead to unauthorized access, data breaches, or other damaging outcomes by exploiting new or unmonitored commands within the cloud environment.
The analytic detects the creation of cloud compute instances using previously unseen image IDs. It leverages cloud infrastructure logs to identify new image IDs that have not been observed before. This activity is significant because it may indicate unauthorized or suspicious activity, such as the deployment of malicious payloads or unauthorized access to sensitive information. If confirmed malicious, this could lead to data breaches, unauthorized access, or further compromise of the cloud environment. Immediate investigation is required to determine the legitimacy of the instance creation and to mitigate potential threats.
Detects suspicious use of command-line tools such as curl or wget to download remote
content - particularly scripts - into temporary directories (e.g., /dev/shm, /tmp), followed by
immediate execution, indicating potential malicious activity. This pattern is commonly used
by malicious scripts, stagers, or downloaders in fileless or multi-stage Linux attacks.
content - particularly scripts - into temporary directories (e.g., /dev/shm, /tmp), followed by
immediate execution, indicating potential malicious activity. This pattern is commonly used
by malicious scripts, stagers, or downloaders in fileless or multi-stage Linux attacks.
The following analytic detects command-line activities that redirect stdout or stderr to the /dev/null file. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process execution logs. This behavior is significant as it can indicate attempts to hide command outputs, a technique observed in the CyclopsBlink malware to conceal modifications to iptables firewall settings. If confirmed malicious, this activity could allow an attacker to stealthily alter system configurations, potentially leading to unauthorized access or persistent control over the compromised machine.
Detects the use of command-line tools such as 'scp', 'rsync', and 'sftp' that are commonly used to copy files to or from remote systems. This activity can be indicative of an adversary transferring tools into an environment (Ingress Tool Transfer) or moving files laterally within a compromised network (Lateral Tool Transfer). The rule specifically looks for the presence of these tool names followed by a space and then a colon or an '@' symbol, which are characteristic of remote file operations.
This rule detects buffer overflow attempts in Unix system log files by looking for specific keywords. These keywords include phrases indicating an attempt to execute code on the stack, known exploit strings like '0bin0sh1', a long string of 'A's (which can be indicative of buffer filling), and messages related to 'stack smashing detected'. The rule aims to identify malicious activity where an attacker tries to overflow a buffer to gain control of program execution, potentially leading to privilege escalation.
This rule detects attempts to create or rename files with a space at the end of their filename, which can be used to obfuscate malicious files or commands. Specifically, it looks for command-line executions involving 'echo "*" > * && chmod +x *' or 'mv * "* "'. The first pattern suggests creating an executable file with a trailing space, and the second suggests renaming a file to include a trailing space.
Detects potential Amazon SSM agent hijack attempts as outlined in the Mitiga research report.
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