Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
539 detections
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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 detects SSL certificates with Punycode domains in the SSL issuer email domain, identified by the prefix "xn--". It leverages the Certificates Datamodel to flag these domains and uses CyberChef for decoding. This activity is significant as Punycode can be used for domain spoofing and phishing attacks. If confirmed malicious, attackers could deceive users and systems, potentially leading to unauthorized access and data breaches.
The analytic identifies potential exploitation of Log4Shell CVE-2021-44228 by correlating multiple MITRE ATT&CK tactics detected in risk events. It leverages Splunk's risk data model to calculate the distinct count of MITRE ATT&CK tactics from Log4Shell-related detections. This activity is significant because it indicates a high probability of exploitation if two or more distinct tactics are observed. If confirmed malicious, this activity could lead to initial payload delivery, callback to a malicious server, and post-exploitation activities, potentially resulting in unauthorized access, lateral movement, and further compromise of the affected systems.
The following analytic detects cloud provisioning activities originating from previously unseen cities. It leverages cloud infrastructure logs and compares the geographic location of the source IP address against a baseline of known locations. This activity is significant as it may indicate unauthorized access or misuse of cloud resources from an unexpected location. If confirmed malicious, this could lead to unauthorized resource creation, potential data exfiltration, or further compromise of cloud infrastructure.
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 DNS requests with unusually large query lengths for the record type being requested. It leverages the Network_Resolution data model and applies a machine learning model to detect outliers in DNS query lengths. This activity is significant because unusually large DNS queries can indicate data exfiltration or command-and-control communication attempts. If confirmed malicious, this activity could allow attackers to exfiltrate sensitive data or maintain persistent communication channels with compromised systems.
This rule detects the execution of the 'sysctl' command on macOS with specific arguments ('hw.', 'kern.', or 'machdep.'). Threat actors and malware commonly use 'sysctl' with these arguments to gather system hardware information, often as part of virtualization or sandbox evasion techniques. By querying system properties, adversaries can determine if they are operating in an analysis environment and adjust their behavior accordingly.
Detects when the Time Machine backup utility is disabled on macOS using the `tmutil` command-line tool. This action can be performed by an attacker to prevent system backups, hindering recovery efforts after an attack.
Detects disabling of Time Machine (Apple's automated backup utility software) via the native macOS backup utility "tmutil".
An attacker can use this to prevent backups from occurring.
An attacker can use this to prevent backups from occurring.
Detects deletion attempts of MacOS Time Machine backups via the native backup utility "tmutil".
An adversary may perform this action before launching a ransonware attack to prevent the victim from restoring their files.
An adversary may perform this action before launching a ransonware attack to prevent the victim from restoring their files.
Detects the addition of a new file or path exclusion to MacOS Time Machine via the "tmutil" utility.
An adversary could exclude a path from Time Machine backups to prevent certain files from being backed up.
An adversary could exclude a path from Time Machine backups to prevent certain files from being backed up.
Detects the creation of Python path configuration files (.pth) within Python library folders on macOS. These files can be maliciously used for code execution and persistence, as modules referenced by them are executed at every Python startup (v3.5+), regardless of whether they are explicitly imported by a script. The rule specifically looks for files ending with '.pth' in the '/lib/python3.([5-9]|[0-9]{2})/site-packages/' directory structure.
Detects when the `csrutil` command is used with the `disable` argument to turn off System Integrity Protection (SIP) on macOS. This action is often performed in post-exploitation scenarios by adversaries to gain greater control over the system or to bypass security mechanisms.
This rule detects the execution of the 'sw_vers' command-line utility on macOS systems when specific arguments are used to query system information. The arguments monitored include '-buildVersion', '-productName', and '-productVersion', which are commonly used for system information discovery.
Detects the use of csrutil to disable the Configure System Integrity Protection (SIP). This technique is used in post-exploit scenarios.
Detects the use of csrutil to view the Configure System Integrity Protection (SIP) status. This technique is used in post-exploit scenarios.
Detects the use of "ioreg" which will show I/O Kit registry information.
This process is used for system information discovery.
It has been observed in-the-wild by calling this process directly or using bash and grep to look for specific strings.
This process is used for system information discovery.
It has been observed in-the-wild by calling this process directly or using bash and grep to look for specific strings.
Detects the use of "sw_vers" for system information discovery
Detects the execution of common macOS command-line utilities used for enumerating local network configuration and firewall settings. This includes tools like 'arp', 'ifconfig', 'netstat', 'networksetup', and 'socketfilterfw', as well as 'defaults' when querying specific firewall preferences.
Detects enumeration of local network configuration
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