Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
289 detections
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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 the use of the .NET compiler csc.exe for on-the-fly compilation of potentially malicious .NET code. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on specific command-line patterns associated with csc.exe. This activity is significant because adversaries and malware often use this technique to evade detection by compiling malicious code at runtime. If confirmed malicious, this could allow attackers to execute arbitrary code, potentially leading to system compromise, data exfiltration, or further lateral movement within the network.
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 analytic detects instances of `regsvcs.exe` running without command line arguments. This behavior typically indicates process injection, where another process manipulates `regsvcs.exe`. The detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, IDs, and command-line executions. This activity is significant as it may signal an attempt to evade detection and execute malicious code. If confirmed malicious, the attacker could achieve code execution, potentially leading to privilege escalation, persistence, or access to sensitive information.
The following analytic detects the execution of "dsquery.exe" with arguments targeting `TrustedDomain` queries directly from the command line. This behavior is identified using Endpoint Detection and Response (EDR) telemetry, focusing on process names and command-line arguments. This activity is significant as it often indicates domain trust discovery, a common step in lateral movement or privilege escalation by adversaries. If confirmed malicious, this could allow attackers to map domain trusts, potentially leading to further exploitation and unauthorized access to trusted domains.
The following analytic identifies unauthorized devices attempting to connect to the organization's network by inspecting DHCP request packets. It detects this activity by comparing the MAC addresses in DHCP requests against a list of known authorized devices stored in the assets_by_str.csv file. This activity is significant for a SOC because unauthorized devices can pose security risks, including potential data breaches or network disruptions. If confirmed malicious, this activity could allow an attacker to gain unauthorized network access, potentially leading to further exploitation or data exfiltration.
The following analytic detects the execution of ngrok.exe on a Windows operating system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. This activity is significant because while ngrok is a legitimate tool for creating secure tunnels, it is increasingly used by adversaries to bypass network defenses and establish reverse proxies. If confirmed malicious, this could allow attackers to exfiltrate data, maintain persistence, or facilitate further attacks by tunneling traffic through the compromised system.
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 analytic identifies modifications to the registry path .wav\\OpenWithProgIds, associated with the Snake Malware campaign. This activity is significant because Snake's WerFault.exe uses this registry path to decrypt an encrypted blob containing critical components like the AES key, IV, and paths for its kernel driver and loader. If confirmed malicious, this could allow the attacker to load and execute Snake's kernel driver, leading to potential system compromise and persistent access.
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 analytic detects potential exploitation attempts against Adobe ColdFusion vulnerabilities CVE-2023-29298 and CVE-2023-26360. It monitors requests to specific ColdFusion Administrator endpoints, especially those with an unexpected additional forward slash, using the Web datamodel. This activity is significant for a SOC as it indicates attempts to bypass access controls, which can lead to unauthorized access to ColdFusion administration endpoints. If confirmed malicious, this could result in data theft, brute force attacks, or further exploitation of other vulnerabilities, posing a serious security risk to the environment.
This rule detects indicators of potential exploitation of CVE-2023-27997, a critical Fortigate SSL VPN vulnerability. It specifically looks for GET or POST requests to '/remote/hostcheck_validate' or '/remote/logincheck' URIs that also contain the 'enc=' parameter in the query string. These patterns are associated with attempts to exploit the vulnerability.
Detects exploitation indicators of CVE-2022-42475, a heap-based buffer overflow vulnerability in FortiOS SSL-VPN's sslvpnd daemon. The rule specifically looks for the creation of known malicious files or configuration backups in specific directories, which are artifacts of successful exploitation.
This rule detects the usage of cleartext protocols over a network by monitoring firewall logs for allowed connections to specific destination ports commonly associated with unencrypted services. These ports include HTTP (80, 8080), FTP (21), Telnet (23), and various database or application-specific ports (e.g., 1433, 3306, 1521, 27017, 50000, 11211, 15672, 5900-5904). The rule specifically looks for 'forward' or 'accept' actions, or connections not marked as 'blocked', indicating active cleartext communication. The primary goal is to identify potential credential exposure or sensitive data transmission over insecure channels.
Detects exploitation attempts against Fortinet SSL VPNs using the CVE-2018-13379 vulnerability. This vulnerability allows an unauthenticated attacker to read arbitrary files on the system via a specially crafted URI.
Ensure that all account usernames and authentication credentials are transmitted across networks using encrypted channels.
Ensure that an encryption is used for all sensitive information in transit. Ensure that an encrypted channels is used for all administrative account access.
Ensure that an encryption is used for all sensitive information in transit. Ensure that an encrypted channels is used for all administrative account access.
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