Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
3,124 detections
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The analytic detects `PutBucketLifecycle` events in AWS CloudTrail logs where a user sets a lifecycle rule for an S3 bucket with an expiration period of fewer than three days. This activity is significant because attackers may use it to delete CloudTrail logs quickly, thereby evading detection and impairing forensic investigations. If confirmed malicious, this could allow attackers to cover their tracks, making it difficult to trace their actions and respond to the breach effectively.
The analytic detects modifications to the Windows error recovery boot configurations using `bcdedit.exe` with flags such as "recoveryenabled" and "no". This activity is significant because ransomware often disables recovery options to prevent system restoration, making it crucial for SOC analysts to investigate. If confirmed malicious, this could hinder recovery efforts, allowing ransomware to cause extensive damage and complicate remediation.
The following analytic detects the use of the 'dd' command to overwrite files on a Linux system. It leverages data from Linux Auditd telemetry, focusing on process execution logs that include command-line details. This activity is significant because adversaries often use the 'dd' command to destroy or irreversibly overwrite files, disrupting system availability and services. If confirmed malicious, this behavior could lead to data destruction, making recovery difficult and potentially causing significant operational disruptions.
The analytic detects the deletion of service files on a Linux machine within system directories (e.g., /etc/systemd/, /lib/systemd/, /run/systemd/). This activity is significant because attackers may delete or modify services to disable security features, evade defenses, impair system functionality, or execute a destructive payload. Immediate investigation is required to determine the responsible process and user.
The analytic identifies modifications to the TranscodedWallpaper file in the wallpaper theme directory, excluding changes made by explorer.exe. This detection leverages the Endpoint.Processes and Endpoint.Filesystem data models to correlate process activity with file modifications. This activity is significant as it may indicate an adversary attempting to deface or change the desktop wallpaper of a targeted host, a tactic often used to signal compromise or deliver a message. If confirmed malicious, this could be a sign of unauthorized access and tampering, potentially leading to further system compromise or data exfiltration.
The following analytic detects excessive usage of `net.exe` within a one-minute interval. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, parent processes, and command-line executions. This behavior is significant as it may indicate an adversary attempting to create, delete, or disable multiple user accounts rapidly, a tactic observed in Monero mining incidents. If confirmed malicious, this activity could lead to unauthorized user account manipulation, potentially compromising system integrity and enabling further malicious actions.
The following analytic identifies a suspicious modification of the Windows registry setting for max connections per server. It detects changes to specific registry paths using data from the Endpoint.Registry datamodel. This activity is significant because altering this setting can be exploited by attackers to increase the number of concurrent connections to a remote server, potentially facilitating DDoS attacks or enabling more effective lateral movement within a compromised network. If confirmed malicious, this could lead to network disruption or further compromise of additional systems.
This analytic detects the termination of specific processes, namely "PServiceControl.exe" and "PService_PPD.exe", which are known targets of the Industroyer2 malware. The detection relies on Sysmon EventCode 5, indicating a process termination event. This activity is highly indicative of an attack on critical infrastructure, particularly energy facility networks, as these processes are related to industrial control systems. Such an attack could lead to severe disruption of essential services and operational control. Immediate investigation is crucial to determine the cause and mitigate potential threats.
The following analytic identifies attempts to download cryptomining software that are blocked by Zscaler. It leverages web proxy logs to detect blocked actions associated with cryptominer threats, analyzing key data points such as device owner, user, URL category, destination URL, and IP. This activity is significant for a SOC as it helps in early identification and mitigation of cryptomining activities, which can compromise network integrity and resource availability. If confirmed malicious, this activity could lead to unauthorized use of network resources for cryptomining, potentially degrading system performance and increasing operational costs.
The analytic identifies high resource utilization anomalies in Kubernetes processes. It leverages process metrics from an OTEL collector and hostmetrics receiver, fetched via the Splunk Infrastructure Monitoring Add-on. The detection uses a lookup table with average and standard deviation values to spot anomalies. This activity is significant as high resource utilization can indicate security threats like cryptojacking, unauthorized data exfiltration, or compromised containers. If confirmed malicious, such anomalies can disrupt services, exhaust resources, increase costs, and allow attackers to evade detection or maintain access.
This analytic detects IPv6 network infrastructure threats by identifying suspicious activities such as IP and MAC address theft or packet drops. It leverages logs from Cisco network devices configured with First Hop Security measures like RA Guard and DHCP Guard. This activity is significant as it can indicate attempts to compromise network integrity and security. If confirmed malicious, attackers could manipulate network traffic, leading to potential data interception, unauthorized access, or network disruption.
The following analytic detects the execution of a suspicious `bcdedit` command that reconfigures a host from safe mode back to normal boot. This detection leverages Endpoint Detection and Response (EDR) data, focusing on command-line executions involving `bcdedit.exe` with specific parameters. This activity is significant as it may indicate the presence of ransomware, such as BlackMatter, which manipulates boot configurations to facilitate encryption processes. If confirmed malicious, this behavior could allow attackers to maintain control over the boot process, potentially leading to further system compromise and data encryption.
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 detects the deletion of cron jobs on a Linux machine. It leverages filesystem event logs to identify when files within the "/etc/cron.*" directory are deleted. This activity is significant because attackers or malware may delete cron jobs to disable scheduled security tasks or evade detection mechanisms. If confirmed malicious, this action could allow an attacker to disrupt system operations, evade security measures, or facilitate further malicious activities such as data wiping, as seen with the acidrain malware.
The following analytic detects the execution of DiskCryptor, identified by the process names "dcrypt.exe" or "dcinst.exe". This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and original file names. DiskCryptor is significant because adversaries use it to manually encrypt disks during an operation, potentially leading to data inaccessibility. If confirmed malicious, this activity could result in complete disk encryption, causing data loss and operational disruption. Immediate investigation is required to mitigate potential ransomware attacks.
The following analytic detects when a repository is archived in GitHub Enterprise. The detection monitors GitHub Enterprise audit logs for repository archival events by tracking actor details, repository information, and associated metadata. For a SOC, identifying repository archival is important as it could indicate attempts to make critical code inaccessible or preparation for repository deletion. While archiving is a legitimate feature, unauthorized archival of active repositories could signal account compromise, insider threats, or attempts to disrupt development operations. The impact of unauthorized repository archival includes loss of active development access, disruption to workflows and CI/CD pipelines, and potential business delays if critical repositories are affected. Additionally, archived repositories may be targeted for subsequent deletion, potentially resulting in permanent loss of intellectual property if proper backups are not maintained.
The following analytic detects anomalous changes in resource utilization ratios for processes running on a Kubernetes node. It leverages process metrics collected via an OTEL collector and hostmetrics receiver, analyzed through Splunk Observability Cloud. The detection uses a lookup table containing average and standard deviation values for various resource ratios (e.g., CPU:memory, CPU:disk operations). Significant deviations from these baselines may indicate compromised processes, malicious activity, or misconfigurations. If confirmed malicious, this could signify a security breach, allowing attackers to manipulate workloads, potentially leading to data exfiltration or service disruption.
The following analytic identifies a suspicious series of command-line executions attempting to disable multiple services. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on processes where "sc.exe" is used with parameters like "config" or "Disabled" within a short time frame. This activity is significant as it may indicate an adversary's attempt to disable security or other critical services to further compromise the system. If confirmed malicious, this could lead to the attacker achieving persistence, evading detection, or disabling security mechanisms, thereby increasing the risk of further exploitation.
The following analytic detects a high frequency of file deletions in the /boot/ folder on Linux systems. It leverages filesystem event logs to identify when 200 or more files are deleted within an hour by the same process. This behavior is significant as it may indicate the presence of wiper malware, such as Industroyer2, which targets critical system directories. If confirmed malicious, this activity could lead to system instability or failure, hindering the boot process and potentially causing a complete system compromise.
The following analytic detects the execution of "bcdedit.exe" with parameters to set the boot status policy to ignore all failures. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names and command-line arguments. This activity is significant because it can indicate an attempt by ransomware to prevent a compromised machine from booting into automatic repair mode, thereby hindering recovery efforts. If confirmed malicious, this action could allow attackers to maintain control over the infected system, complicating remediation and potentially leading to further damage.
The following analytic detects the process of logging off a user through the use of the quser and logoff commands. By monitoring for these commands, the analytic identifies actions where a user session is forcibly terminated, which could be part of an administrative task or a potentially unauthorized access attempt. This detection helps identify potential misuse or malicious activity where a user’s access is revoked without proper authorization, providing insight into potential security incidents involving account management or session manipulation.
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