Identifies an unusual process deleting the Zone.Identifier alternate data stream from an executable or Windows Installer package. Attackers can remove this stream to bypass Mark-of-the-Web protections.

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Indicates the creation and deletion of a scheduled task within a short time interval. Adversaries can use these to proxy malicious execution via the schedule service and perform clean up.

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This rule detects network events that may indicate the use of Telnet traffic. Telnet is commonly used by system administrators to remotely control older or embedded systems using the command line shell. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector. As a plain-text protocol, it may also expose usernames and passwords to anyone capable of observing the traffic.

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This rule detects network events that may indicate the use of RPC traffic from the Internet. RPC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector.

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This rule detects network events that may indicate the use of RPC traffic to the Internet. RPC is commonly used by system administrators to remotely control a system for maintenance or to use shared resources. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector.

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This rule detects network events that may indicate the use of Windows file sharing (also called SMB or CIFS) traffic to the Internet. SMB is commonly used within networks to share files, printers, and other system resources amongst trusted systems. It should almost never be directly exposed to the Internet, as it is frequently targeted and exploited by threat actors as an initial access or backdoor vector or for data exfiltration.

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Indicates the creation of a scheduled task using Windows event logs. Adversaries can use these to establish persistence, move laterally, and/or escalate privileges.

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Identifies the creation of a Process ID (PID), lock or reboot file created in temporary file storage paradigm (tmpfs) directory /var/run. On Linux, the PID files typically hold the process ID to track previous copies running and manage other tasks. Certain Linux malware use the /var/run directory for holding data, executables and other tasks, disguising itself or these files as legitimate PID files.

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Specially crafted DNS requests can manipulate a known overflow vulnerability in some Windows DNS servers, resulting in Remote Code Execution (RCE) or a Denial of Service (DoS) from crashing the service.

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This rule detects Linux Access Control List (ACL) modification via the setfacl command. Attackers may use the setfacl utility to modify file and directory permissions in order to evade detection and maintain persistence on a compromised system.

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Identify access to sensitive Active Directory object attributes that contains credentials and decryption keys such as unixUserPassword, ms-PKI-AccountCredentials and msPKI-CredentialRoamingTokens.

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Identifies when the SYSTEM account uses an account discovery utility. This could be a sign of discovery activity after an adversary has achieved privilege escalation.

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Identifies an attempt to reset a potentially privileged account password remotely. Adversaries may manipulate account passwords to maintain access or evade password duration policies and preserve compromised credentials.

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Detects when multiple hosts are using the same agent ID. This could occur in the event of an agent being taken over and used to inject illegitimate documents into an instance as an attempt to spoof events in order to masquerade actual activity to evade detection.

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Detects attempts to deactivate an Okta application. An adversary may attempt to modify, deactivate, or delete an Okta application in order to weaken an organization's security controls or disrupt their business operations.

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Detects attempts to delete an Okta application. An adversary may attempt to modify, deactivate, or delete an Okta application in order to weaken an organization's security controls or disrupt their business operations.

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Detects attempts to modify an Okta application. An adversary may attempt to modify, deactivate, or delete an Okta application in order to weaken an organization's security controls or disrupt their business operations.

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This rule identifies potentially suspicious activity by detecting instances where a single IAM user's temporary session token is accessed from multiple IP addresses within a short time frame. Such behavior may suggest that an adversary has compromised temporary credentials and is utilizing them from various locations. To enhance detection accuracy and minimize false positives, the rule incorporates criteria that evaluate unique IP addresses, user agents, cities, and networks. These additional checks help distinguish between legitimate distributed access patterns and potential credential misuse. Detected activities are classified into different types based on the combination of unique indicators, with each classification assigned a fidelity score reflecting the likelihood of malicious behavior. High fidelity scores are given to patterns most indicative of threats, such as multiple unique IPs, networks, cities, and user agents. Medium and low fidelity scores correspond to less severe patterns, enabling security teams to effectively prioritize alerts.

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Detects successful AssumeRoleWithWebIdentity where the caller identity is a Kubernetes service account and the source autonomous system organization is present but not Amazon.com, Inc. EKS workloads that obtain IAM credentials via IAM Roles for Service Accounts (IRSA) normally reach STS from AWS-managed or AWS-associated networks; the same identity from a clearly external ASN can indicate a stolen or misused projected service-account token being exchanged for IAM credentials off-cluster.

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Detects CloudTrail PutEventSelectors calls where the legacy event selectors explicitly set includeManagementEvents to false, disabling capture of all management API calls for that trail. Unlike StopLogging or DeleteTrail — which leave an obvious trace of the trail being stopped or removed entirely — this technique leaves the trail appearing active and healthy in the console while silently blinding defenders to subsequent IAM changes, credential operations, and resource abuse. This technique is documented in Stratus Red Team as aws.defense-evasion.cloudtrail-event-selectors and is a known pre-exfiltration step.

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Detects the deletion of one or more Amazon CloudWatch alarms using the "DeleteAlarms" API. CloudWatch alarms are critical for monitoring metrics and triggering alerts when thresholds are exceeded. An adversary may delete alarms to impair visibility, silence alerts, and evade detection following malicious activity. This behavior may occur during post-exploitation or cleanup phases to remove traces of compromise or disable automated responses.

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Detects the deletion of an Amazon CloudWatch Log Group using the "DeleteLogGroup" API. CloudWatch log groups store operational and security logs for AWS services and custom applications. Deleting a log group permanently removes all associated log streams and historical log data, which can eliminate forensic evidence and disrupt security monitoring pipelines. Adversaries may delete log groups to conceal malicious activity, disable log forwarding, or impede incident response.

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Detects the deletion of an Amazon CloudWatch log stream using the "DeleteLogStream" API. Deleting a log stream permanently removes its associated log events and may disrupt security visibility, break audit trails, or suppress forensic evidence. Adversaries may delete log streams to conceal malicious actions, impair monitoring pipelines, or remove artifacts generated during post-exploitation activity.

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Identifies when a user has queried for deprecated Amazon Machine Images (AMIs) in AWS. This may indicate an adversary looking for outdated AMIs that may be vulnerable to exploitation. While deprecated AMIs are not inherently malicious or indicative of a breach, they may be more susceptible to vulnerabilities and should be investigated for potential security risks.

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Identifies the removal of access permissions from a shared AWS EC2 EBS snapshot. EBS snapshots are essential for data retention and disaster recovery. Adversaries may revoke or modify snapshot permissions to prevent legitimate users from accessing backups, thereby obstructing recovery efforts after data loss or destructive actions. This tactic can also be used to evade detection or maintain exclusive access to critical backups, ultimately increasing the impact of an attack and complicating incident response.

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Detects when an Amazon Elastic Block Store (EBS) snapshot is shared with another AWS account or made public. EBS snapshots contain copies of data volumes that may include sensitive or regulated information. Adversaries may exploit ModifySnapshotAttribute to share snapshots with external accounts or the public, allowing them to copy and access data in an environment they control. This activity often precedes data exfiltration or persistence operations, where the attacker transfers stolen data out of the victim account or prepares a staging area for further exploitation.

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Identifies a change to an AWS Security Group Configuration. A security group is like a virtual firewall, and modifying configurations may allow unauthorized access. Threat actors may abuse this to establish persistence, exfiltrate data, or pivot in an AWS environment.

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Identifies discovery request DescribeInstanceAttribute with the attribute userData and instanceId in AWS CloudTrail logs. This may indicate an attempt to retrieve user data from an EC2 instance. Adversaries may use this information to gather sensitive data from the instance such as hardcoded credentials or to identify potential vulnerabilities. This is a New Terms rule that identifies the first time an IAM user or role requests the user data for a specific EC2 instance.

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Identifies the first time, within the configured history window, that a long-term IAM access key ID (prefix AKIA) is used successfully from a given source.ip in AWS CloudTrail. Long-term access keys belong to IAM users or the account root user. They are a common target after credential theft or leakage, including supply-chain and exposed-key scenarios. Temporary security credentials (prefix ASIA) and console sessions are excluded so the signal emphasizes programmatic access patterns.

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Detects the first time an AWS identity successfully deletes an IAM managed policy whose ARN contains guardrail-related keywords (for example Boundary, Deny, Restrict, Guard, SCP, Guardrail). Adversaries who have obtained elevated IAM privileges may delete policies to remove restrictive permissions boundaries, eliminate deny-based guardrails, or clean up after a privilege escalation operation. Infrastructure-as-code tools (Terraform, CloudFormation, Pulumi, and Ansible) are excluded because policy lifecycle management is a routine part of automated deployments. A policy deletion by an identity not seen performing this activity during the prior seven days may indicate newly compromised credentials being used to modify the account's permission structure.

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Identifies a single principal directly invoking AWS Lambda functions at a high volume within a one-hour window. Adversaries may drive excessive invocations to abuse functions for resource hijacking or cryptomining, to inflate costs in a denial-of-wallet attack, or to enumerate function behavior. This is a volumetric heuristic: the threshold is environment-dependent and high-throughput applications can exceed it, so tune it to the deployment. This rule relies on AWS Lambda data event logging, which is not enabled by default.

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Detects when credentials issued through AssumeRoleWithWebIdentity for a Kubernetes service account identity are later used for several distinct AWS control-plane actions on the same session access key. Workloads that use EKS IAM Roles for Service Accounts routinely exchange a projected service-account token for short-lived IAM credentials; this rule highlights sessions where that exchange is followed by a spread of sensitive APIs—reconnaissance, secrets and parameter access, IAM changes, or compute creation—beyond what routine pod traffic usually shows. High-volume S3 object reads and writes are excluded from the correlation set to reduce noise from normal data-plane work.

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Identifies a high number of failed S3 operations against a single bucket from a single source address within a short timeframe. This activity can indicate attempts to collect bucket objects or cause an increase in billing to an account via internal "AccessDenied" errors.

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Identifies the addition of an expiration lifecycle configuration to an Amazon S3 bucket. S3 lifecycle rules can automatically delete or transition objects after a defined period. Adversaries can abuse them by configuring auto-deletion of logs, forensic evidence, or sensitive objects to cover their tracks. This rule detects the use of the PutBucketLifecycle or PutBucketLifecycleConfiguration APIs with Expiration parameters, which may indicate an attempt to automate the removal of data to hinder investigation or maintain operational secrecy after malicious activity.

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Detects successful S3 GetObject calls targeting high-value credential and secret files commonly stored in S3 buckets: AWS credentials files (".aws/credentials", ".aws/config"), SSH private keys ("id_rsa", "id_ed25519", "id_ecdsa", "id_dsa"), environment files (".env"), PEM and PuTTY key files, and other private key patterns. These file types are high-yield targets for credential harvesting from S3. The rule excludes AWSService identity type to suppress S3 replication, Glacier restore, and other AWS-internal data movement that legitimately reads these files.

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Identifies when the same AWS principal, from the same source IP, successfully invokes read-only S3 control-plane APIs that reveal bucket posture across many buckets in a short period. This pattern can indicate automated reconnaissance or security scanning, similar to CSPM tools and post-compromise enumeration. The rule excludes AWS service principals, requires programmatic-style sessions (not Management Console credentials), and requires populated resource and identity fields so nulls do not skew cardinality.

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Identifies AWS CloudTrail events where an unauthenticated source is attempting to access an S3 bucket. This activity may indicate a misconfigured S3 bucket policy that allows public access to the bucket, potentially exposing sensitive data to unauthorized users. Adversaries can specify --no-sign-request in the AWS CLI to retrieve objects from an S3 bucket without authentication. This is a New Terms rule, which means it will trigger for each unique combination of the source.address and targeted bucket name that has not been seen making this API request.

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Identifies rapid secret retrieval activity from AWS Secrets Manager using the GetSecretValue or BatchGetSecretValue API actions. Adversaries who compromise an IAM user, instance role, or temporary credentials may attempt to enumerate or exfiltrate secrets in bulk to escalate privileges, move laterally, or gain persistence. This rule detects 20 or more unique secret retrievals by the same user identity within a short time window, which may indicate credential compromise or automated secret harvesting.

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Identifies when a single AWS principal makes GetServiceQuota API calls for the EC2 service quota L-1216C47A, across more than 10 AWS regions within a 30-second window. This quota represents the vCPU limit for on-demand EC2 instances. Adversaries commonly enumerate this quota across regions to assess capacity for large-scale instance deployment, including cryptocurrency mining, malware hosting, or command-and-control infrastructure. This behavior may indicate cloud infrastructure discovery using compromised credentials or a compromised workload.

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Detects the execution of commands or scripts on EC2 instances using AWS Systems Manager (SSM), such as RunShellScript, RunPowerShellScript or custom documents. While legitimate users may employ these commands for management tasks, they can also be exploited by attackers with credentials to establish persistence, install malware, or execute reverse shells for further access to compromised instances. This is a New Terms rule that looks for the first instance of this behavior by a user or role.

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Identifies process start events where the parent process is the AWS Systems Manager (SSM) Session Manager worker. Session Manager provides interactive shell access to EC2 instances and hybrid nodes without bastion hosts or open inbound ports. Adversaries abuse it for remote execution and lateral movement using legitimate AWS credentials and IAM permissions. This rule surfaces endpoint execution occurring under that worker for visibility and hunting. Expect noise from authorized administrative sessions.

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Identifies when a service has assumed a role in AWS Security Token Service (STS). Services can assume a role to obtain temporary credentials and access AWS resources. Adversaries can use this technique for credential access and privilege escalation. This is a New Terms rule that identifies when a service assumes a role in AWS Security Token Service (STS) to obtain temporary credentials and access AWS resources. While often legitimate, adversaries may use this technique for unauthorized access, privilege escalation, or lateral movement within an AWS environment.

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Identifies role chaining activity. Role chaining is when you use one assumed role to assume a second role through the AWS CLI or API. While this a recognized functionality in AWS, role chaining can be abused for privilege escalation if the subsequent assumed role provides additional privileges. Role chaining can also be used as a persistence mechanism as each AssumeRole action results in a refreshed session token with a 1 hour maximum duration. This is a new terms rule that looks for the first occurance of one role (aws.cloudtrail.user_identity.session_context.session_issuer.arn) assuming another (aws.cloudtrail.resources.arn).

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Detects an identity minting a service account token via the AKS (Azure Kubernetes Service) TokenRequest API (serviceaccounts/token), excluding known AKS control-plane and platform identities. Adversaries request service account tokens from a compromised identity to impersonate a workload, move laterally, or escalate privileges within the cluster. Coverage includes workload service accounts (system:serviceaccount:*), so a compromised in-cluster token minting a token for another service account is not excluded.

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Detects AKS (Azure Kubernetes Service) service account or node identities invoking self-subject access or rules review APIs. Non-human identities rarely enumerate their own permissions outside known controllers; this can indicate stolen tokens probing effective RBAC before privilege escalation.

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Identifies when an Azure Automation runbook is created or modified. An adversary may create or modify an Azure Automation runbook to execute malicious code and maintain persistence in their target's environment.

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Identifies synchronous command execution on a virtual machine (VM) or virtual machine scale set (VMSS) in Azure via the action-based Run Command ("runCommand/action"). A Virtual Machine Contributor role lets you manage virtual machines, but not access them, nor access the virtual network or storage account they’re connected to. However, commands can be run on the VM via the Run Command feature, which execute as System (Windows) or root (Linux). Other roles, such as certain Administrator roles, may be able to execute commands on a VM as well.

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This rule detects when a base64 decoded payload is piped to an interpreter on Linux systems. Adversaries may use base64 encoding to obfuscate data and pipe it to an interpreter to execute malicious code. This technique may be used to evade detection by host- or network-based security controls.

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Both ~/.bash_profile and ~/.bashrc are files containing shell commands that are run when Bash is invoked. These files are executed in a user's context, either interactively or non-interactively, when a user logs in so that their environment is set correctly. Adversaries may abuse this to establish persistence by executing malicious content triggered by a user’s shell.

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Identifies the execution of a binary by root in Linux shared memory directories: (/dev/shm/, /run/shm/, /var/run/, /var/lock/). This activity is to be considered highly abnormal and should be investigated. Threat actors have placed executables used for persistence on high-uptime servers in these directories as system backdoors.

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Detects execution of bpftool commands used to detach eBPF programs or links, or to delete or modify eBPF maps. These actions can disable, alter, or interfere with kernel-level instrumentation and enforcement mechanisms implemented through eBPF. In environments relying on eBPF-based networking, observability, or security controls, unexpected use of these operations may indicate defense evasion or runtime tampering.

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Identifies attempts to clear or disable Windows event log stores using Windows wevetutil command. This is often done by attackers in an attempt to evade detection or destroy forensic evidence on a system.

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Identifies attempts to disable the code signing policy through the registry. Code signing provides authenticity on a program, and grants the user with the ability to check whether the program has been tampered with. By allowing the execution of unsigned or self-signed code, threat actors can craft and execute malicious code.

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Identifies PowerShell, PowerShell ISE, or Cmd execution spawned from Windows Script Host or MSHTA.

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Identifies process execution events where the command line value contains a long sequence of whitespace characters or multiple occurrences of contiguous whitespace. Attackers may attempt to evade signature-based detections by padding their malicious command with unnecessary whitespace characters. These observations should be investigated for malicious behavior.

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Identifies Component Object Model (COM) hijacking via registry modification. Adversaries may establish persistence by executing malicious content triggered by hijacked references to COM objects.

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Identifies DNS queries to known Large Language Model domains by unsigned binaries or common Windows scripting utilities. Malwares may leverage the capabilities of LLM to perform actions in the affected system in a dynamic way.

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Adversaries may implement command and control (C2) communications that use common web services to hide their activity. This attack technique is typically targeted at an organization and uses web services common to the victim network, which allows the adversary to blend into legitimate traffic activity. These popular services are typically targeted since they have most likely been used before compromise, which helps malicious traffic blend in.

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This rule detects when a container management binary is run from inside a container. These binaries are critical components of many containerized environments, and their presence and execution in unauthorized containers could indicate compromise or a misconfiguration.

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Generates a detection alert each time a 'Container Workload Protection' alert is received. Enabling this rule allows you to immediately begin triaging and investigating these alerts.

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Identifies attempts to export a registry hive which may contain credentials using the Windows reg.exe tool.

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This rule monitors for (ana)cron jobs being created or renamed. Linux cron jobs are scheduled tasks that can be leveraged by system administrators to set up scheduled tasks, but may be abused by malicious actors for persistence, privilege escalation and command execution. By creating or modifying cron job configurations, attackers can execute malicious commands or scripts at predefined intervals, ensuring their continued presence and enabling unauthorized activities.

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This rule detects the use of the "curl" command-line tool with SOCKS proxy options, launched from an unusual parent process. Attackers may use "curl" to establish a SOCKS proxy connection to bypass network restrictions and exfiltrate data or communicate with C2 servers.

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Identifies the occurrence of a CyberArk Privileged Access Security (PAS) non-error level audit event which is recommended for monitoring by the vendor. The event.code correlates to the CyberArk Vault Audit Action Code.

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This is a New Terms rule that identifies the first occurrence of setsid or nohup being used to directly execute a process on a host. Attackers may leverage these tools to execute commands in a new session and/or to ignore signals.

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This rule identifies the creation of directories in the /bin directory. The /bin directory contains essential binary files that are required for the system to function properly. The creation of directories in this location could be an attempt to hide malicious files or executables, as these /bin directories usually just contain binaries.

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LSA protecton is provided to prevent nonprotected processes from reading memory and injecting code. This feature provides added security for the credentials that LSA stores and manages. Adversaries may modify the RunAsPPL registry and wait or initiate a system restart to enable Lsass credentials access.

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User Account Control (UAC) can help mitigate the impact of malware on Windows hosts. With UAC, apps and tasks always run in the security context of a non-administrator account, unless an administrator specifically authorizes administrator-level access to the system. This rule identifies registry value changes to bypass User Access Control (UAC) protection.

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Identifies use of the Set-MpPreference or Add-MpPreference PowerShell commands to disable or weaken certain Windows Defender settings, including detection of base64-encoded variants used to bypass command-line inspection.

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This rule detects the creation of files named release_agent or notify_on_release, which are commonly associated with the abuse of Linux cgroup release mechanisms. In Docker or containerized environments, this behavior may indicate an attempt to exploit privilege escalation vulnerabilities such as CVE-2022-0492, where attackers use the release_agent feature to execute code on the host from within a container.

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This rule detects potential Docker socket enumeration activity by monitoring processes that attempt to interact with the Docker socket file (/var/run/docker.sock). Docker socket enumeration is a common technique used by attackers to interact with the Docker daemon and perform various operations, such as creating, starting, stopping, and removing containers. Attackers may abuse Docker socket enumeration to gain unauthorized access to the host system, escalate privileges, or move laterally within the environment.

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Identifies the use of WinRAR or 7-Zip to create encrypted archives. Adversaries often compress and encrypt data in preparation for exfiltration.

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Identifies concurrent azure signin events for the same user and from multiple sources, and where one of the authentication event has some suspicious properties often associated to DeviceCode and OAuth phishing. Adversaries may steal Refresh Tokens (RTs) via phishing to bypass multi-factor authentication (MFA) and gain unauthorized access to Azure resources.

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Identifies potential session hijacking or token replay in Microsoft Entra ID. This rule detects cases where a user signs in and subsequently accesses Microsoft Graph from a different IP address using the same session ID. This may indicate a successful OAuth phishing attack, session hijacking, or token replay attack, where an adversary has stolen a session cookie or refresh/access token and is impersonating the user from an alternate host or location.

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Detects Microsoft Entra ID sign-ins consistent with Tycoon2FA phishing-as-a-service (PhaaS) adversary-in-the-middle (AiTM) activity: the Microsoft Authentication Broker requesting tokens for Microsoft Graph or Exchange Online, or the Office web client application authenticating to itself, combined with Node.js-style user agents (node, axios, undici). Tycoon 2FA bypasses MFA by relaying authentication and capturing session material, often targeting Microsoft 365 and Gmail. Baseline legitimate automation and developer tooling before tuning.

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Identifies potential brute-force attacks targeting Microsoft 365 user accounts by analyzing failed sign-in patterns in Microsoft Entra ID Sign-In Logs. This detection focuses on a high volume of failed interactive or non-interactive authentication attempts within a short time window, often indicative of password spraying, credential stuffing, or password guessing. Adversaries may use these techniques to gain unauthorized access to Microsoft 365 services such as Exchange Online, SharePoint, or Teams.

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Detects rare non-interactive sign-ins where an Entra ID client application authenticates on behalf of a principal user using an application (client) ID that is not commonly associated with that user's historical sign-in behavior. Adversaries with stolen credentials or OAuth tokens may abuse Entra ID–managed or first-party client IDs to perform on-behalf-of (OBO) authentication, blending into legitimate cloud traffic while avoiding traditional interactive sign-in flows. This technique is commonly observed in OAuth phishing, token theft, and access broker operations, and may precede lateral movement, persistence, or data access via Microsoft Graph or other cloud resources. The rule uses a New Terms approach to identify first-seen combinations of the UPN and Client ID within a defined history window, helping surface unexpected client usage that may indicate compromised identities, malicious automation, or unauthorized application impersonation.

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Identifies native Windows host and network enumeration commands spawned by the Windows Management Instrumentation Provider Service (WMIPrvSE).

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Identifies the execution of macOS built-in commands related to account or group enumeration. Adversaries may use account and group information to orient themselves before deciding how to act.

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Monitors for kernel processes with associated process executable fields that are not empty. Unix kernel processes such as kthreadd and kworker typically do not have process.executable fields associated to them. Attackers may attempt to hide their malicious programs by masquerading as legitimate kernel processes.

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Identifies an executable created by a Microsoft Office application and subsequently executed. These processes are often launched via scripts inside documents or during exploitation of Microsoft Office applications.

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This rule detects potentially dangerous commands spawned by the GitHub Actions Runner.Worker process or by shell interpreters launched via a runner entrypoint script on self-hosted runner machines. Adversaries who gain the ability to modify or trigger workflows in a linked GitHub repository can execute arbitrary commands on the runner host. This behavior may indicate malicious or unexpected workflow activity, including code execution, reconnaissance, credential harvesting, or network exfiltration initiated through a compromised repository or unauthorized workflow.

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Identifies execution via MSSQL xp_cmdshell stored procedure. Malicious users may attempt to elevate their privileges by using xp_cmdshell, which is disabled by default, thus, it's important to review the context of it's use.

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Detects suspicious child process execution from the OpenClaw, Moltbot, or Clawdbot AI coding agents running via Node.js. These tools can execute arbitrary shell commands through skills or prompt injection attacks. Malicious skills from public registries like ClawHub have been observed executing obfuscated download-and-execute commands targeting cryptocurrency wallets and credentials. This rule identifies shells, scripting interpreters, and common LOLBins spawned by these AI agents.

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Detects attempts to execute a program on the host from the Windows Subsystem for Linux. Adversaries may enable and use WSL for Linux to avoid detection.

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This rule detects the creation of files in world-writable directories by an unusual process. Attackers may attempt to hide their activities by creating files in world-writable directories, which are commonly used for temporary file storage. This behavior is often associated with lateral movement and can be an indicator of an attacker attempting to move laterally within a network.

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An adversary with access to a compromised AWS service such as an EC2 instance, Lambda function, or other service may attempt to leverage the compromised service to access secrets in AWS Secrets Manager. This rule looks for the first time a specific user identity has programmatically retrieved a secret value from Secrets Manager using the GetSecretValue action. This rule assumes that AWS services such as Lambda functions and EC2 instances are setup with IAM role's assigned that have the necessary permissions to access the secrets in Secrets Manager. An adversary with access to a compromised AWS service would rely on its' attached role to access the secrets in Secrets Manager.

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Identifies a newly observed RMM-related code-signature subject across the Windows Elastic Defend hosts. Attackers often use RMM tools to gain remote access to victim machines and deploy malware.

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This detection correlates FortiGate's application control SOCKS events with Elastic Defend network event to identify the source process performing SOCKS traffic. Adversaries may use a connection proxy to direct network traffic between systems or act as an intermediary for network communications to a command and control server to avoid direct connections to their infrastructure.

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Detects suspicious access to the /Library/Preferences/com.apple.TimeMachine.plist file, indicating a potential attempt to verify or exploit Full Disk Access (FDA) permissions. This file is often checked by malware to confirm FDA privileges, which allow unrestricted access to sensitive user data.

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Identifies when a firewall rule is created in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be configured to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may create a new firewall rule in order to weaken their target's security controls and allow more permissive ingress or egress traffic flows for their benefit.

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Identifies when a firewall rule is deleted in Google Cloud Platform (GCP) for Virtual Private Cloud (VPC) or App Engine. These firewall rules can be configured to allow or deny connections to or from virtual machine (VM) instances or specific applications. An adversary may delete a firewall rule in order to weaken their target's security controls.

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Identifies GenAI agent CLIs started with permission-bypass or auto-approval flags that disable human-in-the-loop guardrails. These modes are intended for isolated sandboxes but are frequently misused on internet-connected developer workstations, allowing prompt injection, compromised dependencies, or malicious skills to execute commands, modify files, or reach sensitive paths without confirmation.

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This rule detects child processes spawned by Git hooks. Git hooks are scripts that Git executes before or after events such as commit, push, and receive. The rule identifies child processes spawned by Git hooks that are not typically spawned by the Git process itself. This behavior may indicate an attacker attempting to hide malicious activity by leveraging the legitimate Git process to execute unauthorized commands.

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This rule detects the use of git to clone a repository or download files from GitHub using wget or curl, followed by the creation of files in suspicious directories such as /tmp, /var/tmp, or /dev/shm. This behavior may indicate an attempt to download a payload, exploit or tool.

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Detects when there is activity on a private GitHub repository from an unusual IP address. Adversaries may access private repositories from unfamiliar IPs to exfiltrate sensitive code or data, potentially indicating a compromise or unauthorized access.

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Detects the deletion of a GitHub app either from a repo or an organization.

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This rule detects setting modifications for protected branches of a GitHub repository. Branch protection rules can be used to enforce certain workflows or requirements before a contributor can push changes to a branch in your repository. Changes to these protected branch settings should be investigated and verified as legitimate activity. Unauthorized changes could be used to lower your organization's security posture and leave you exposed for future attacks.

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Detects a single authenticated GKE identity from one source IP issuing a burst of API calls across many distinct actions and resources with a mix of successful and failed outcomes. That pattern is consistent with automated RBAC permission enumeration rather than steady-state controller traffic. Anonymous probing is covered by a separate rule.

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Detects creation or modification of a GKE Service with type NodePort. NodePort exposes a static port on every worker node that hosts matching pods, which widens the cluster's external attack surface and can bypass load-balancer and firewall controls. Attackers may create NodePort Services to intercept traffic or establish a direct path into the cluster.

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Detects GKE secrets get or list requests from a previously unseen combination of source IP, identity, and user agent, excluding the default Kubernetes client placeholder. Attackers who compromise a pod or steal a kubeconfig often use curl, custom scripts, or atypical clients from a new host to read service-account tokens, registry credentials, or application secrets. Anonymous identities are excluded; use dedicated anonymous-access rules for unauthenticated probing.

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Detects the first time a Google Workspace user successfully signs in from a given source ASN within a 14-day historical window. Most users have a stable set of egress ASNs (home ISP, corporate VPN, mobile carrier). A new ASN for a user is a meaningful anomaly as it surfaces ISP changes and travel, but also catches AiTM phishing-kit relays whose egress ASN was never previously associated with the user.

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This rule identifies a high number (10) of process terminations via pkill from the same host within a short time period.

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The hosts file on endpoints is used to control manual IP address to hostname resolutions. The hosts file is the first point of lookup for DNS hostname resolution so if adversaries can modify the endpoint hosts file, they can route traffic to malicious infrastructure. This rule detects modifications to the hosts file on Microsoft Windows, Linux (Ubuntu or RHEL) and macOS systems.

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Identifies ICMP Redirect messages (type 5 for IPv4, type 137 for IPv6) sourced from an internal IPv4 or IPv6 address. Legitimate redirects are normally sent only by on-path routers. A workstation or server emitting redirects can indicate route manipulation for adversary-in-the-middle activity.

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Identifies remote execution via Windows PowerShell remoting. Windows PowerShell remoting allows a user to run any Windows PowerShell command on one or more remote computers. This could be an indication of lateral movement.

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Identifies remote execution via Windows Remote Management (WinRM) remote shell on a target host. This could be an indication of lateral movement.

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This rule detects when an interactive shell is spawned inside a running container. This could indicate a potential container breakout attempt or an attacker's attempt to gain unauthorized access to the underlying host.

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This rule detects the loading of a kernel module from an unusual location. Threat actors may use this technique to maintain persistence on a system by loading a kernel module into the kernel namespace. This behavior is strongly related to the presence of a rootkit on the system.

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Detects the use of the insmod binary to load a Linux kernel object file. Threat actors can use this binary, given they have root privileges, to load a rootkit on a system providing them with complete control and the ability to hide from security products. Manually loading a kernel module in this manner should not be at all common and can indicate suspicious or malicious behavior.

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This rule detects kernel unpacking activity through several built-in Linux utilities. Attackers may use these utilities to unpack kernel images and modules to search for vulnerabilities or to modify the kernel.

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The kubeconfig file is a critical component in Kubernetes environments, containing configuration details for accessing and managing Kubernetes clusters. Attackers may attempt to get access to, create, or modify kubeconfig files to gain unauthorized initial access to Kubernetes clusters or move laterally within the cluster. This rule detects process discovery executions that involve kubeconfig files, particularly those executed from common shell environments or world-writeable directories.

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This rule detects potential kubectl network configuration modification activity by monitoring for process events where the kubectl command is executed with arguments that suggest an attempt to modify network configurations in Kubernetes. This could indicate an adversary trying to manipulate network settings for malicious purposes, such as establishing unauthorized access or exfiltrating data.

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This rule detects a container deployed with one or more dangerously permissive Linux capabilities. An attacker with the ability to deploy a container with added capabilities could use this for further execution, lateral movement, or privilege escalation within a cluster. The capabilities detected in this rule have been used in container escapes to the host machine.

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Detects the creation or modification of Kubernetes Roles or ClusterRoles that grant high-risk permissions, such as wildcard access or RBAC escalation verbs (e.g., bind, escalate, impersonate), which may enable privilege escalation or unauthorized access within the cluster.

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This rule detects attempts to create resources in Kubernetes clusters that are forbidden by the authorization policy. It specifically looks for creation requests that are denied with a "forbid" decision, indicating that the user or service account does not have the necessary permissions to perform the action. This activity is commonly associated with adversaries attempting to create resources in a Kubernetes environment without proper authorization, which can lead to unauthorized access, manipulation of cluster resources, lateral movement and/or privilege escalation.

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Adversaries who land credentials in a cluster—or abuse an over-privileged token—often map the environment before exfiltration or privilege escalation. A practical first pass is to learn where workloads run, how the cluster is partitioned, and what RBAC exists at namespace vs cluster scope. Rapid get/list traffic across distinct API resource kinds that answer those questions (namespaces, workloads, roles, cluster-wide roles) is a common setup and orientation pattern for both interactive attackers and automated recon scripts. It is less typical for steady-state controllers, which usually touch a narrow set of resources repeatedly. This rule highlights that cross-resource burst from a single client fingerprint within a one-minute bucket so analysts can separate routine automation from potential discovery and permission reconnaissance ahead of follow-on actions.

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This rule detects when a pod is created with a sensitive volume of type hostPath. A hostPath volume type mounts a sensitive file or folder from the node to the container. If the container gets compromised, the attacker can use this mount for gaining access to the node. There are many ways a container with unrestricted access to the host filesystem can escalate privileges, including reading data from other containers, and accessing tokens of more privileged pods.

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This rules detects an attempt to create or modify a pod attached to the host network. HostNetwork allows a pod to use the node network namespace. Doing so gives the pod access to any service running on localhost of the host. An attacker could use this access to snoop on network activity of other pods on the same node or bypass restrictive network policies applied to its given namespace.

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This rule detects an attempt to create or modify a pod attached to the host PID namespace. HostPID allows a pod to access all the processes running on the host and could allow an attacker to take malicious action. When paired with ptrace this can be used to escalate privileges outside of the container. When paired with a privileged container, the pod can see all of the processes on the host. An attacker can enter the init system (PID 1) on the host. From there, they could execute a shell and continue to escalate privileges to root.

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Kubernetes audit identities for kubelet (system:node:) and workloads (system:serviceaccount:) are meant to operate with tight, predictable API usage. Direct get or list on the Secrets API from those principals is often a sign of credential access. Attackers who stole a pod service-account token or node credentials sweep Secret objects for tokens, registry credentials, TLS keys, or application configuration. Even denied attempts still reveal intent to reach sensitive material. Legitimate controllers do read secrets they mount or manage, so this signal is most valuable when paired with triage (namespace scope, user agent, RBAC, and whether the identity should touch those secret names at all).

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Detects read access to Kubernetes Secrets (get/list) with a user agent matching a curated set of non-standard or attacker-leaning clients, for example minimal HTTP tooling, common scripting stacks, default library fingerprints, or distribution-tagged strings associated with offensive-security Linux images. Legitimate in-cluster automation usually presents stable, purpose-specific user agents (for example controller or client-go variants used by known components).

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Detects a sequence where a principal creates or modifies a Role/ClusterRole to include high-risk permissions (e.g., wildcard access or escalation verbs) and then creates or patches a workload resource (DaemonSet, Deployment, or CronJob) shortly after, which may indicate RBAC-based privilege escalation followed by payload deployment. This pattern is often used by adversaries to gain unauthorized access to sensitive resources and deploy malicious payloads.

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Detects write operations performed by Kubernetes service accounts against RBAC resources (Roles, ClusterRoles, RoleBindings, ClusterRoleBindings). Service accounts typically do not manage RBAC directly; this activity may indicate token abuse, misconfigured permissions, or unauthorized privilege escalation.

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This rule detects when a process accesses Kubernetes service account secrets. Kubernetes service account secrets are files that contain sensitive information used by applications running in Kubernetes clusters to authenticate and authorize access to the cluster. These secrets are typically mounted into pods at runtime, allowing applications to access them securely. Unauthorized access to these secrets can lead to privilege escalation, lateral movement and unauthorized actions within the cluster.

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This rule detects when a service account or node attempts to enumerate their own permissions via the selfsubjectaccessreview or selfsubjectrulesreview APIs via an unusual user agent. This is highly unusual behavior for non-human identities like service accounts and nodes. An adversary may have gained access to credentials/tokens and this could be an attempt to determine what privileges they have to facilitate further movement or execution within the cluster.

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This rule detects a user attempt to establish a shell session into a pod using the 'exec' command. Using the 'exec' command in a pod allows a user to establish a temporary shell session and execute any process/commands in the pod. An adversary may call bash to gain a persistent interactive shell which will allow access to any data the pod has permissions to, including secrets.

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An adversary can establish persistence by installing a new launch agent that executes at login by using launchd or launchctl to load a plist into the appropriate directories.

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This rule monitors for the potential memory dump of the init process (PID 1) through gdb. Attackers may leverage memory dumping techniques to attempt secret extraction from privileged processes. Tools that display this behavior include "truffleproc" and "bash-memory-dump". This behavior should not happen by default, and should be investigated thoroughly.

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Indicates the creation of a scheduled task. Adversaries can use these to establish persistence, move laterally, and/or escalate privileges.

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Identifies an excessive number of Microsoft 365 mailbox items accessed by a user either via aggregated counts or throttling. Microsoft audits mailbox access via the MailItemsAccessed event, which is triggered when a user accesses mailbox items. If more than 1000 mailbox items are accessed within a 24-hour period, it is then throttled. Excessive mailbox access may indicate an adversary attempting to exfiltrate sensitive information or perform reconnaissance on a target's mailbox. This rule detects both the throttled and unthrottled events with a high threshold.

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Detects a burst of Microsoft 365 user account lockouts within a short 5-minute window. A high number of IdsLocked login errors across multiple user accounts may indicate brute-force attempts for the same users resulting in lockouts.

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Identifies brute-force authentication activity targeting Microsoft 365 user accounts using failed sign-in patterns that match password spraying, credential stuffing, or password guessing behavior. Adversaries may attempt brute-force authentication with credentials obtained from previous breaches, leaks, marketplaces or guessable passwords.

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A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with high probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious.

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A supervised machine learning model (ProblemChild) has identified a suspicious Windows process event with low probability of it being malicious activity. Alternatively, the model's blocklist identified the event as being malicious.

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Detects multi-factor authentication (MFA) deactivation with no subsequent re-activation for an Okta user account. An adversary may deactivate MFA for an Okta user account in order to weaken the authentication requirements for the account.

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This New Terms rule focuses on the first occurrence of a client application ID (azure.graphactivitylogs.properties.app_id) making a request to Microsoft Graph API for a specific tenant ID (azure.tenant_id) and user principal object ID (azure.graphactivitylogs.properties.user_principal_object_id). This rule may helps identify unauthorized access or actions performed by compromised accounts. Advesaries may succesfully compromise a user's credentials and use the Microsoft Graph API to access resources or perform actions on behalf of the user.

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Identifies when one or more features on Microsoft Defender are disabled. Adversaries may disable or tamper with Microsoft Defender features to evade detection and conceal malicious behavior.

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Identifies modification of the dynamic linker preload shared object (ld.so.preload). Adversaries may execute malicious payloads by hijacking the dynamic linker used to load libraries.

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Identifies changes to the Safari configuration using the built-in defaults command. Adversaries may attempt to enable or disable certain Safari settings, such as enabling JavaScript from Apple Events to ease in the hijacking of the users browser.

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This rule detects the execution of multiple base64 decoding commands to decode data. multi-decoded data is suspicious, and may be used by attackers to obfuscate malicious payloads or commands.

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This rule detects when a specific Okta actor has multiple device token hashes and multiple source IPs for a single Okta session. This may indicate an authenticated session has been hijacked or replayed from a different device and network. Adversaries may steal session cookies or tokens to gain unauthorized access to Okta admin console, applications, tenants, or other resources.

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Identifies multiple logon failures followed by a successful one from the same source address. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts.

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Identifies multiple consecutive logon failures from the same source address and within a short time interval. Adversaries will often brute force login attempts across multiple users with a common or known password, in an attempt to gain access to accounts.

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Detects when a user has started multiple Okta sessions with the same user account and different session IDs. This may indicate that an attacker has stolen the user's session cookie and is using it to access the user's account from a different location.

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This rule monitors for the execution of the cat command, followed by a connection attempt by the same process. Cat is capable of transfering data via tcp/udp channels by redirecting its read output to a /dev/tcp or /dev/udp channel. This activity is highly suspicious, and should be investigated. Attackers may leverage this capability to transfer tools or files to another host in the network or exfiltrate data while attempting to evade detection in the process.

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Identifies DNS queries to commonly abused Top Level Domains by common LOLBINs or executables running from world writable directories or unsigned binaries. This behavior matches on common malware C2 abusing less formal domain names.

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Detects the creation of a new Identity Provider (IdP) by a Super Administrator or Organization Administrator within Okta.

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Identifies NullSessionPipe registry modifications that specify which pipes can be accessed anonymously. This could be indicative of adversary lateral movement preparation by making the added pipe available to everyone.

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Detects sign-in events where authentication is carried out via a third-party Identity Provider (IdP) that has not been seen before. Adversaries may add an unauthorized IdP to an Okta tenant to gain persistent access. This rule uses New Terms detection to only alert when a previously unseen IdP is used for authentication, reducing noise from legitimate federated identity providers while highlighting potentially rogue IdP additions.

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Okta ThreatInsight is a feature that provides valuable debug data regarding authentication and authorization processes, which is logged in the system. Within this data, there is a specific field called threat_suspected, which represents Okta's internal evaluation of the authentication or authorization workflow. When this field is set to True, it suggests the presence of potential credential access techniques, such as password-spraying, brute-forcing, replay attacks, and other similar threats.

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Detects when a specific Okta actor has multiple sessions started from different geolocations. Adversaries may attempt to launch an attack by using a list of known usernames and passwords to gain unauthorized access to user accounts from different locations.

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This rule identifies when the openssl client or server is used to establish a connection. Attackers may use openssl to establish a secure connection to a remote server or to create a secure server to receive connections. This activity may be used to exfiltrate data or establish a command and control channel.

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Detects the creation of a PHP file in the WordPress plugin directory, which is a common technique used by attackers to establish persistence on a compromised web server. Attackers may upload a malicious PHP file and call it from a web browser to gain remote access to the server.

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This rule detects PAM version discovery activity on Linux systems. PAM version discovery can be an indication of an attacker attempting to backdoor the authentication process through malicious PAM modules.

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This rule detects a known command and control pattern in network events. The FIN7 threat group is known to use this command and control technique, while maintaining persistence in their target's network.

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Detects PowerShell scripts that reference Antimalware Scan Interface (AMSI) bypass classes, methods, or known bypass strings. Attackers attempt AMSI bypass to disable scanning and run malicious PowerShell content undetected.

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Identifies potential ransomware note being uploaded to an AWS S3 bucket. This rule detects the PutObject S3 API call with an object name commonly associated with ransomware notes. The keywords detected here rarely overlap with common file names and have been attributed to ransomware notes with high-confidence. Adversaries with access to a misconfigured S3 bucket may retrieve, delete, and replace objects with ransom notes to extort victims.

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This rule detects SSH session ID change followed by a suspicious SSHD child process, this may indicate the successful execution of a potentially malicious process through the Pluggable Authentication Module (PAM) utility. PAM is a framework used by Linux systems to authenticate users. Adversaries may create malicious PAM modules that grant them persistence onto the target every time a user logs in by executing a backdoor script or command.

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This rule monitors for suspicious activities that may indicate an attacker attempting to execute arbitrary code within a PostgreSQL environment. Attackers can execute code via PostgreSQL as a result of gaining unauthorized access to a public facing PostgreSQL database or exploiting vulnerabilities, such as remote command execution and SQL injection attacks, which can result in unauthorized access and malicious actions, and facilitate post-exploitation activities for unauthorized access and malicious actions.

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Identifies potential relay activities against a Computer account by identifying authentication events using the computer account coming from from hosts other than the server that owns the account. Attackers may relay the computer account hash after capturing it using forced authentication.

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Identifies the execution of a Chromium based browser with the debugging process argument, which may indicate an attempt to steal authentication cookies. An adversary may steal web application or service session cookies and use them to gain access web applications or Internet services as an authenticated user without needing credentials.

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This rule identifies when a User Account starts the Active Directory Replication Process. Attackers can use the DCSync technique to get credential information of individual accounts or the entire domain, thus compromising the entire domain.

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