Detection catalogue

Query searches for outbound block rules deleted by non AI.

Query searches for inbound block rules deleted by non AI.

A rule was created which granted a user access to a large, built-in, group of assets.

Find users who gained access to the largest number of target assets in the selected time range

Identifies when a JIT Rule connection is new or rare by a given account today based on comparison with the previous 14 days. JIT Rule creations are indicated by the Activity Type Id 20

Detects when a api token has been created.

Detects when a machine is removed from protection.

Identifies potential hijacking of the Microsoft Update Orchestrator Service to establish persistence with an integrity level of SYSTEM.

Identifies suspicious use of whoami.exe which displays user, group, and privileges information for the user who is currently logged on to the local system.

Identifies newly observed execution of SoftPerfect Network Scanner or Advanced IP/Port Scanner on a Windows host. Adversaries commonly use these legitimate scanners during post-compromise discovery to map live hosts, open ports, and reachable systems, then select targets for lateral movement.

Identifies abuse of the Console Window Host (conhost.exe) to execute commands via proxy. This behavior is used as a defense evasion technique to blend-in malicious activity with legitimate Windows software.

Identifies remote access to the Windows Protected Storage Service through the IPC$ share. Attackers may abuse this named pipe to interact with the Protected Storage Service and extract sensitive credentials, certificates, or DPAPI backup keys.

Identifies a Windows Installer package (MSI) originating from the internet, which when executed, installs a recognized RMM product. Attackers use RMMs commonly in social engineering campaigns to gain access and control over the victim's system. This rule does not establish that the origin, installer, or RMM product is inherently malicious. It also excludes installations covered by the companion rule "RMM Software Installation from a Commonly Abused Web Service".

Identifies Windows Installer (MSI) packages that originate from commonly abused web services and install a recognized remote monitoring and management (RMM) product. Adversaries may abuse legitimate RMM software in social engineering campaigns to gain remote access and control over victim systems. This rule does not establish that the origin, installer, or RMM product is inherently malicious.

Detects an MSI installer execution followed by the execution of commonly abused Remote Management Software like ScreenConnect. This behavior may indicate abuse where an attacker triggers an MSI install then connects via a guest link with a known session key.

Monitors for the execution of different processes that might be used by attackers for malicious intent. An alert from this rule should be investigated further, as hack tools are commonly used by blue teamers and system administrators as well.

Adversaries may create or modify Linux firewall rules with DROP, ACCEPT, or REJECT actions to affect how a host receives or sends network traffic. This activity may be used to bypass security controls, block defensive tooling, or gain unauthorized access to the network.

This rule detects a memfd_create syscall event on Linux where the combination of host and process lineage (parent executable and executable path) has not been seen before. This can indicate fileless execution using memfd-backed executables.

This rule detects unusual DNS queries to commonly abused top level domains. Malware authors may use these domains to host command and control infrastructure, exfiltrate data, or to download payloads for later execution.

Identifies a one-on-one Microsoft Teams chat created by a user from a foreign tenant whose display name, member profile, or email local-part resembles IT help desk or Microsoft security staff. Adversaries abuse cross-tenant Teams external access to impersonate support personnel and socially engineer victims into granting remote access or disclosing credentials.

Identifies a high number of failed inbound SSH authentication attempts on a macOS host within a short time window, using sshd authentication messages collected by the macOS Security Events integration. Adversaries may perform password brute force or password spraying against exposed SSH services to obtain unauthorized access.

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

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.

Detects the use of curl to upload files to an internet server. Threat actors often will collect and exfiltrate data on a system to their C2 server for review. Many threat actors have been observed using curl to upload the collected data. Use of curl in this way, while not inherently malicious, should be considered highly abnormal and suspicious activity.

Detects HTTP requests to web servers whose URL or query string references cloud instance metadata endpoints or equivalent encoded variants. Attackers exploit server-side request forgery (SSRF) vulnerabilities in web applications to reach link-local metadata services on AWS, GCP, Azure, and similar cloud providers and harvest temporary credentials, tokens, or instance details.

This rule assists in detecting rare user agents, which may indicate web browsing activity by an unconventional process different from the usual ones. The rule specifically searches for UserAgent strings that have not been seen in the past 14 days. This query will perform better when run over summarized data

This query utilizes built-in KQL anomaly detection algorithms to identify anomalous data transfers to public networks. It detects significant deviations from a baseline pattern, allowing the detection of sudden increases in data transferred to unknown public networks, which may indicate data exfiltration attempts. Investigating such anomalies is crucial. The score indicates the degree to which the data transfer deviates from the baseline value. A higher score indicates a greater deviation.

Detects any failed event for a particular user.

Detects failed events based on created time.