Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detect web traffic to a recently expired domain followed by an exe file creation event
Detects an initiated network connection by a non browser process on the system to "azurewebsites.net". The latter was often used by threat actors as a malware hosting and exfiltration site.
Detects an executable initiating a network connection to "LocaltoNet" tunneling sub-domains. LocaltoNet is a reverse proxy that enables localhost services to be exposed to the Internet. Attackers have been seen to use this service for command-and-control activities to bypass MFA and perimeter controls.
Detects outbound network connections initiated by `dialer.exe`, an outdated Microsoft utility. This process is known to be targeted by info-stealers for process injection and used to establish command and control (C2) connections, with Rhadamanthys being a common example. The rule filters out connections to common local and private IP ranges to reduce false positives.
Detects outbound network connections initiated by msbuild.exe to common C2 ports (80, 443), which could indicate the use of Silenttrinity or other MSBuild-based execution for command and control.
This analytic identifies Snort signatures that have triggered only once in the past 7 days across all Cisco Secure Firewall IntrusionEvent logs. While these rules typically do not trigger in day-to-day network activity, their sudden appearance may indicate early-stage compromise, previously unseen malware, or reconnaissance activity against less commonly exposed services. Investigating these outliers can provide valuable insight into new or low-noise adversary behaviors.
Detects outbound network connection initiated by Microsoft Dialer.
The Microsoft Dialer, also known as Phone Dialer, is a built-in utility application included in various versions of the Microsoft Windows operating system. Its primary function is to provide users with a graphical interface for managing phone calls via a modem or a phone line connected to the computer.
This is an outdated process in the current conext of it's usage and is a common target for info stealers for process injection, and is used to make C2 connections, common example is "Rhadamanthys"
The Microsoft Dialer, also known as Phone Dialer, is a built-in utility application included in various versions of the Microsoft Windows operating system. Its primary function is to provide users with a graphical interface for managing phone calls via a modem or a phone line connected to the computer.
This is an outdated process in the current conext of it's usage and is a common target for info stealers for process injection, and is used to make C2 connections, common example is "Rhadamanthys"
Detects an executable initiating a network connection to "LocaltoNet" tunneling sub-domains.
LocaltoNet is a reverse proxy that enables localhost services to be exposed to the Internet.
Attackers have been seen to use this service for command-and-control activities to bypass MFA and perimeter controls.
LocaltoNet is a reverse proxy that enables localhost services to be exposed to the Internet.
Attackers have been seen to use this service for command-and-control activities to bypass MFA and perimeter controls.
Detects an executable initiating a network connection to "LocaltoNet" tunneling sub-domains.
LocaltoNet is a reverse proxy that enables localhost services to be exposed to the Internet.
Attackers have been seen to use this service for command-and-control activities to bypass MFA and perimeter controls.
LocaltoNet is a reverse proxy that enables localhost services to be exposed to the Internet.
Attackers have been seen to use this service for command-and-control activities to bypass MFA and perimeter controls.
The analytic detects unauthorized access or misuse of Kubernetes Secrets from unusual locations. It leverages Kubernetes Audit logs to identify anomalies in access patterns by analyzing the source of requests by country. This activity is significant for a SOC as Kubernetes Secrets store sensitive information like passwords, OAuth tokens, and SSH keys, making them critical assets. If confirmed malicious, this behavior could indicate an attacker attempting to exfiltrate or misuse these secrets, potentially leading to unauthorized access to sensitive systems or data.
This analytic detects the use of known suspicious SSL certificates by comparing the SHA1 fingerprint from Cisco Secure Firewall logs against a blacklist. This is crucial for identifying malware distribution, C2 infrastructure, or phishing campaigns that reuse or self-sign certificates. Detection of such activity may indicate beaconing, malware download, or data exfiltration over TLS/SSL.
This analytic highlights high-impact intrusion events detected by Cisco Secure Firewall. It leverages Cisco Secure Firewall Threat Defense logs, specifically the IntrusionEvent event type, and focuses on events with an `Impact` score of 1 or 2. If confirmed malicious, these events may indicate a potentially compromised host.
This analytic detects a single source computer accessing Windows administrative shares (C$, Admin$, IPC$) on 30 or more remote endpoints within a 5-minute window. It leverages Windows Event IDs 5140 and 5145, which are generated for file share events. This behavior is significant as it may indicate an adversary enumerating network shares to locate sensitive files, a common tactic used by threat actors for reconnaissance and lateral movement. If confirmed malicious, this activity could lead to unauthorized access to critical data, lateral movement, and potential compromise of multiple systems within the network.
The following analytic identifies access to GCP Storage buckets from new or previously unseen remote IP addresses. It leverages GCP Storage bucket-access logs ingested via Cloud Pub/Sub and compares current access events against a lookup table of previously seen IP addresses. This activity is significant as it may indicate unauthorized access or potential reconnaissance by an attacker. If confirmed malicious, this could lead to data exfiltration, unauthorized data manipulation, or further compromise of the GCP environment.
The analytic detects potential reverse shell activity by identifying connections involving ports commonly associated with remote access tools, shell listeners, or tunneling utilities. It leverages Cisco Secure Firewall Threat Defense logs and monitors destination ports against a list of non-standard, high-risk port values often used in post-exploitation scenarios. Adversaries frequently configure tools like netcat, Meterpreter, or other backdoors to listen or connect over uncommon ports such as 4444, 2222, or 51820 to bypass standard monitoring and firewall rules. If confirmed malicious, this activity may represent command and control (C2) tunneling, lateral movement, or unauthorized remote access.
This analytic detects the use of Plink (including renamed versions like pvhost.exe) for protocol tunneling, which may be used for egress or lateral movement within an organization. It identifies specific command-line options (-R, -L, -D, -l, -N, -P, -pw) commonly used for port forwarding and tunneling by analyzing process execution logs from Endpoint Detection and Response (EDR) agents. This activity is significant as it may indicate an attempt to bypass network security controls or establish unauthorized connections. If confirmed malicious, this could allow an attacker to exfiltrate data, move laterally across the network, or maintain persistent access, posing a severe threat to the organization's security. The detection covers both the original Plink executable and potential renamed versions, enhancing its ability to catch evasion attempts.
This analytic detects network connections flagged by Cisco Secure Firewall's Encrypted Visibility Engine (EVE) with a high threat confidence score (80% or greater). This indicates that the encrypted traffic is highly likely to be malicious, potentially associated with malware command and control (C2), remote access tools, or suspicious tunneling behavior. Such activity could signify covert communication from compromised hosts.
The analytic identifies excessive DNS query failures by counting DNS responses that do not indicate success, triggering when there are more than 50 occurrences. It leverages the Network_Resolution data model, focusing on DNS reply codes that signify errors. This activity is significant because a high number of DNS failures can indicate potential network misconfigurations, DNS poisoning attempts, or malware communication issues. If confirmed malicious, this activity could lead to disrupted network services, hindered communication, or data exfiltration attempts by attackers.
This analytic identifies remote code execution (RCE) attempts targeting F5 BIG-IP, BIG-IQ, and Traffix SDC devices, specifically exploiting CVE-2020-5902. It uses regex to detect patterns in syslog data that match known exploit strings such as "hsqldb;" and directory traversal sequences. This activity is significant because successful exploitation can allow attackers to execute arbitrary commands on the affected devices, leading to full system compromise. If confirmed malicious, this could result in unauthorized access, data exfiltration, or further lateral movement within the network.
The following analytic identifies high inbound or outbound network I/O anomalies in Kubernetes containers. It leverages process metrics from an OTEL collector and Kubelet Stats Receiver, along with data from Splunk Observability Cloud. A lookup table with average and standard deviation values for network I/O is used to detect anomalies persisting over a 1-hour period. This activity is significant as it may indicate data exfiltration, command and control communication, or unauthorized data transfers. If confirmed malicious, it could lead to data breaches, service outages, financial losses, and reputational damage.
This analytic identifies suspicious DNS TXT records using a pre-trained deep learning model. It leverages DNS response data from the Network Resolution data model, categorizing TXT records into known types via regular expressions. Records that do not match known patterns are flagged as suspicious. This activity is significant as DNS TXT records can be used for data exfiltration or command-and-control communication. If confirmed malicious, attackers could use these records to covertly transfer data or receive instructions, posing a severe threat to network security.
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