Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
97 detections
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Get all filtering events done by the Windows filtering platform.
This includes any blocks done by Windows Firewall rules, but also blocks triggered by some 3rd party firewalls.
When no Firewall rules are configured, the default behavior is to block all incoming network connections.
This includes any blocks done by Windows Firewall rules, but also blocks triggered by some 3rd party firewalls.
When no Firewall rules are configured, the default behavior is to block all incoming network connections.
This rule identifies when an Azure Kubernetes network policy is modified or deleted. Network policies control the traffic flow between pods/namespaces and to/from external network endpoints. Unauthorized modification or deletion of these policies can lead to security vulnerabilities, such as allowing unauthorized network access to sensitive services or disrupting legitimate communication within the cluster, potentially leading to a denial of service or data exfiltration.
Detects the removal of a deployment from a Kubernetes cluster.
This could indicate disruptive activity aiming to impact business operations.
This could indicate disruptive activity aiming to impact business operations.
This analytic detects previously unseen processes within the Kubernetes environment on master or worker nodes. It leverages process metrics collected via an OTEL collector and hostmetrics receiver, with data pulled from Splunk Observability Cloud. The detection compares processes observed in the last hour against those seen in the previous 30 days. Identifying new processes is crucial as they may indicate unauthorized activity or attempts to compromise the node. If confirmed malicious, these processes could lead to data exfiltration, privilege escalation, denial-of-service attacks, or the introduction of malware, posing significant risks to the Kubernetes cluster.
This analytic identifies a large volume of DNS ANY queries, which may indicate a DNS amplification attack. It leverages the Network_Resolution data model to count DNS queries of type "ANY" directed to specific destinations. This activity is significant because DNS amplification attacks can overwhelm network resources, leading to Denial of Service (DoS) conditions. If confirmed malicious, this activity could disrupt services, degrade network performance, and potentially be part of a larger Distributed Denial of Service (DDoS) attack, impacting the availability of critical infrastructure.
The analytic detects ARP Poisoning attacks by monitoring for Dynamic ARP Inspection (DAI) errors on Cisco network devices. It leverages logs from Cisco devices, specifically looking for events where the ARP inspection feature has disabled an interface due to suspicious activity. This activity is significant because ARP Poisoning can allow attackers to intercept, modify, or disrupt network traffic, leading to potential data breaches or denial of service. If confirmed malicious, this could enable attackers to perform man-in-the-middle attacks, compromising the integrity and confidentiality of network communications.
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.
This analytic identifies failed attempts to delete AWS IAM groups. It leverages AWS CloudTrail logs to detect events where the DeleteGroup action fails due to errors like NoSuchEntityException, DeleteConflictException, or AccessDenied. This activity is significant as it may indicate unauthorized attempts to modify IAM group configurations, which could be a precursor to privilege escalation or other malicious actions. If confirmed malicious, this could allow an attacker to disrupt IAM policies, potentially leading to unauthorized access or denial of service within the AWS environment.
This rule detects when an OpenCanary honeypot's NTP service receives a 'monlist' request. The 'monlist' command is a deprecated feature in NTP that can be abused for amplification attacks (Network Denial of Service). Detecting this activity on a honeypot indicates an adversary is likely scanning for vulnerable NTP servers or attempting to use the honeypot in an amplification attack.
This rule detects Denial of Service (DoS) activity originating from an Amazon EC2 instance, as identified by AWS GuardDuty. It specifically looks for GuardDuty findings where the product event type indicates a DenialOfService event and filters out any sample findings.
Detects instances where an NTP service on an OpenCanary node has had a NTP monlist request.
Amazon GuardDuty detects a Denial of Service (DoS) activity in an Amazon EC2 instance.
Yara rule that detects ChinaZ trojan.
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