Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects when a known malicious file, identified by its SHA256 hash through VirusTotal relationships, attempts to contact a domain that VirusTotal also associates with that file. It correlates DNS query events with VirusTotal intelligence to identify suspicious network communications originating from potentially compromised systems.
Detects the execution of the "pbpaste" utility on macOS. This utility retrieves the contents of the clipboard and writes them to standard output. Attackers can abuse this utility to collect sensitive data, such as passwords or other confidential information, from the user's clipboard. The rule is designed to hunt for potential malicious use of pbpaste by examining the parent process and command-line arguments for suspicious activity.
Detect DNS events that communicate with gaming sites in MISP. These violate policy.
IOC Domain C2
YARA-L
Detect DNS events that indicate communication to a C2 domain in MISP
Hash Prevalence
YARA-L
Correlate process events with hashes that have a low rolling max over the past 10 days
Identify process creations that are tagged exploit in VT
Alert on known Hash querying a known hostname with VT Relationships
Alert on downloading a known file hash from a known IP with VT Relationships.
GCTI Remote Access Tools
YARA-L
Alert process and file create events that are associated with hashes from the GCTI Remote Access Tool list
GCTI Tor Exit Nodes
YARA-L
Alert traffic destined for known Tor exit nodes
Alert on Benign Binary contacting a TOR IP
A malicious file contacting a known Tor Exit Node.
The following analytic identifies processes referencing plist files that determine which applications are re-opened when a user reboots their MacOS machine. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and parent processes related to "com.apple.loginwindow." This activity is significant because it can indicate attempts to persist across reboots, a common tactic used by attackers to maintain access. If confirmed malicious, this could allow an attacker to execute code or maintain persistence on the affected system, potentially leading to further compromise.
The following analytic detects the usage of the `plutil` command to modify plist files on macOS systems. It leverages osquery to monitor process events, specifically looking for executions of `/usr/bin/plutil`. This activity is significant because adversaries can use `plutil` to alter plist files, potentially adding malicious binaries or command-line arguments that execute upon user logon or system startup. If confirmed malicious, this could allow attackers to achieve persistence, execute arbitrary code, or escalate privileges, posing a significant threat to the system's security.
The following analytic detects the use of curl on Linux or MacOS systems to download a file from a remote source and pipe it directly to bash for execution. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, command-line arguments, and parent processes. This activity is significant as it is commonly associated with malicious actions such as coinminers and exploitation of vulnerabilities like CVE-2021-44228 in Log4j. If confirmed malicious, this behavior could lead to unauthorized code execution, system compromise, and further exploitation within the environment.
This analytic detects the use of `wget` to download a file from a remote source and pipe its content directly to `bash` for execution. This behavior is commonly associated with malicious activities such as deploying coinminers or exploiting vulnerabilities like CVE-2021-44228 (Log4j). Successful execution of such commands could lead to arbitrary code execution, system compromise, and unauthorized data access.
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 analytic detects multiple CrowdStrike LOW severity alerts originating from the same endpoint, indicating a series of minor suspicious activities or policy violations. Specifically, it triggers when an endpoint generates three or more distinct types of LOW severity alerts. These alerts are not immediately critical but should be reviewed to prevent potential threats. They often highlight unusual behavior or low-level risks that, if left unchecked, could escalate into more significant security issues. Regular monitoring and analysis of these alerts are essential for maintaining robust security, as a cluster of different low-severity events can be an early indicator of a more significant compromise or an adversary's reconnaissance activities.
This analytic detects CrowdStrike alerts specifically categorized with a 'MEDIUM' severity. These alerts indicate suspicious activity that warrants prompt attention but is not immediately critical. Such activities might include unusual behavior or attempted policy violations. The rule processes CrowdStrike stream data, renames relevant fields for consistency, and then filters for events where the 'severity' field contains 'MEDIUM'. The primary goal is to identify and flag these medium-severity incidents for further investigation and mitigation to prevent potential escalation of attacks.
The following analytic detects CrowdStrike alerts for Medium Identity Risk Severity with a risk score of 55% or higher. These alerts indicate significant vulnerabilities in user identities, such as suspicious behavior or compromised credentials. Promptly investigating and addressing these alerts is crucial to prevent potential security breaches and ensure the integrity and protection of sensitive information and systems.
The analytic identifies the use of `sqlite3` querying the MacOS preferences to determine the original URL from which a package was downloaded. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line executions involving `LSQuarantine`. This activity is significant as it is commonly associated with MacOS adware and other malicious software. If confirmed malicious, this behavior could indicate an attempt to track or manipulate downloaded packages, potentially leading to further system compromise or persistent adware infections.
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