Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
101 detections
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This rule detects instances where the Ghidra reverse engineering suite (or associated Java processes running Ghidra components) initiates suspicious child processes. This behavior is considered anomalous as standard reverse engineering activities in Ghidra should not require the execution of system administrative tools, interpreters, or networking utilities, which may indicate an attacker using a compromised development environment to launch secondary payloads or tools.
Detects Server-Side Template Injection (SSTI) and subsequent Remote Code Execution (RCE) attempts within the Floci API Gateway environment. The rule monitors for suspicious child processes spawned by the Floci JVM (e.g., shell execution), the creation of specific RCE proof-of-concept marker files, and the execution of associated exploitation tooling or IAM-bypass command arguments.
Detects instances where the Ghidra reverse engineering tool (via java.exe or javaw.exe) spawns suspicious child processes. This behavior is considered anomalous as Ghidra typically does not require launching command shells, scripting interpreters, or other system binaries directly from its process tree. Such activity often indicates that an attacker is using the Ghidra environment to execute secondary payloads or perform post-exploitation tasks.
Detects OS command execution spawned by a Java process, potentially indicating successful exploitation of Velocity template injection (e.g., in Flowise or Floci) where java.lang.ProcessBuilder is leveraged to execute malicious commands.
Detects the staging and potential execution of Java deserialization payloads associated with the ysoserial CommonCollections5 (CC5) exploit, which leverages the BadAttributeValueExpException gadget chain.
Detects instances where a Java-based application (specifically associated with 'floci' or API Gateway components) spawns suspicious child processes such as shell interpreters (sh, bash, powershell, cmd.exe). This pattern is often indicative of post-exploitation activity following a remote code execution (RCE) attempt against a template engine or web-facing gateway. It also identifies specific file paths related to documented 'floci' POCs and RCE payloads.
Detects the deletion of .pkg_history or .pkg_logs, an anti-forensic attempt after the dropper completes, associated with the Mastra NPM compromise.
This rule set detects potential post-exploitation activity and exploitation attempts targeting Ivanti EPMM (formerly MobileIron Core). The first rule, `ivanti_epmm_java_spawns_shell`, identifies suspicious process creation where a Java or Tomcat process (parent process) spawns a shell process (cmd.exe, bash, sh, or powershell.exe). This behavior is indicative of an attacker gaining remote code execution and using the compromised Java/Tomcat process to execute system commands. The second rule, `ivanti_epmm_http_featureusage_exploit`, detects HTTP requests to the `/api/v2/featureusage` endpoint that contain parameters indicative of Expression Language (EL) injection or format string abuse, specifically looking for `format=` along with keywords like `${`, `Runtime`, `exec`, or `getRuntime` in the URL. This suggests an attempt to exploit a vulnerability in the Ivanti EPMM application to achieve remote code execution.
Detects the execution of a command shell by the Java Runtime to run a batch file from a typical malware staging directory. This behavior is a core TTP of the Stan Ghouls group, used to execute their malicious Java-based loaders which in turn drop and run the NetSupport RAT.
The following analytic detects the use of default or publicly known named pipes associated with Cobalt Strike. It leverages Sysmon EventID 17 and 18 to identify specific named pipes commonly used by Cobalt Strike's Artifact Kit and Malleable C2 Profiles. This activity is significant because Cobalt Strike is a popular tool for adversaries to conduct post-exploitation tasks, and identifying its named pipes can reveal potential malicious activity. If confirmed malicious, this could indicate an active Cobalt Strike beacon, leading to unauthorized access, data exfiltration, or further lateral movement within the network.
This analytic detects suspicious data transfer activities involving the use of the `split` syscall with the `-b` option, which specifies the size of each output file. This technique can be used by attackers to evade detection by breaking large files into smaller parts, bypassing size-based security controls, and facilitating covert exfiltration of sensitive data. By monitoring for unusual or unauthorized use of the `split` syscall with a specified block size, this analytic helps identify potential data exfiltration attempts.
This analytic identifies the bulk creation of ransomware notes (e.g., .txt, .html, .hta files) on an infected machine. It leverages Sysmon EventCode 11 to detect multiple instances of these file types being created within a short time frame (10 seconds). A detection is triggered if 15 or more unique readme paths are observed. This activity is a strong indicator of an active ransomware attack, where the attacker is notifying the victim of the encryption. If confirmed malicious, this behavior could lead to widespread data encryption, rendering critical files inaccessible and potentially causing significant operational disruption.
The following analytic detects suspicious attempts to find credentials stored in password stores, indicating a potential attacker's effort to access sensitive login information. Password stores are critical repositories that contain valuable credentials, and unauthorized access to them can lead to significant security breaches. By monitoring for unusual or unauthorized activities related to password store access, this analytic helps identify potential credential theft attempts, allowing security teams to respond promptly and prevent unauthorized access to critical systems and data.
This analytic detects instances where web or application server processes (such as Java, Tomcat, Apache, Nginx, Node, Caddy, IIS, PHP) spawn a Linux or Windows shell. This activity is highly indicative of successful exploitation, potentially related to vulnerabilities like Log4Shell (CVE-2021-44228) or Spring4Shell (CVE-2022-22965), leading to unauthorized command execution, privilege escalation, or persistent access. The detection leverages Endpoint Detection and Response (EDR) telemetry, focusing on parent-child process relationships and process names.
The following analytic identifies the execution of RAR utilities to archive files on a system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, GUIDs, and command-line arguments. This activity is significant as threat actors, including red-teamers and malware like DarkGate, use RAR archiving to compress and exfiltrate collected data from compromised hosts. If confirmed malicious, this behavior could lead to the unauthorized transfer of sensitive information to command and control servers, posing a severe risk to data confidentiality and integrity.
This analytic detects the configuration of TFTP services on Cisco IOS devices that could be used to exfiltrate sensitive configuration files. Threat actors like Static Tundra have been observed configuring TFTP servers to make device configuration files accessible for exfiltration after gaining initial access. The detection specifically looks for commands that expose critical configuration files such as startup-config, running-config, and other sensitive system information through TFTP. This activity is particularly concerning as it may represent an attempt to steal credentials, network topology information, and other sensitive data stored in device configurations.
The analytic detects when a Windows RDP client attempts to execute an RDP file from a temporary directory, downloads directory, or Outlook directories. This detection is significant as it can indicate an attempt for an adversary to deliver a .rdp file, which may be leveraged by attackers to control or exfiltrate data. If confirmed malicious, this activity could lead to unauthorized access, data theft, or further lateral movement within the network.
The analytic identifies the execution of the native mimikatz.exe binary on Windows systems, including instances where the binary is renamed. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and original file names. This activity is significant because Mimikatz is a widely used tool for extracting authentication credentials, posing a severe security risk. If confirmed malicious, this activity could allow attackers to obtain sensitive credentials, escalate privileges, and move laterally within the network, leading to potential data breaches and system compromise.
Detects suspicious script download attempts initiated by a Java process, indicative of potential JDWP exploitation leading to Remote Code Execution (RCE). Attackers often leverage exposed JDWP interfaces to execute commands like downloading and running malicious scripts.
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.
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