Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This analytic detects suspicious downloads from common file sharing and content delivery platforms using known living-off-the-land binaries (LOLBins) such as 'curl.exe', 'certutil.exe', 'msiexec.exe', 'powershell.exe', 'wmic.exe', and others. It leverages Cisco Network Visibility Module logs to correlate network flow activity with process context, including command-line arguments, process path, and parent process information. These tools are often abused by adversaries and malware to retrieve payloads from public hosting platforms such as GitHub, Discord CDN, Transfer.sh, or Pastebin. This detection helps identify potential initial access, payload staging, or command and control activity using legitimate services.
The following analytic detects MSIExec making network connections over ports 443 or 80. This behavior is identified by correlating process creation events from Endpoint Detection and Response (EDR) agents with network traffic logs. Typically, MSIExec does not perform network communication to the internet, making this activity unusual and potentially indicative of malicious behavior. If confirmed malicious, an attacker could be using MSIExec to download or communicate with external servers, potentially leading to data exfiltration, command and control (C2) communication, or further malware deployment.
The following analytic detects the creation of files in the Windows %startup% folder, a common persistence technique. It leverages the Endpoint.Filesystem data model to identify file creation events in this specific directory. This activity is significant because adversaries often use the startup folder to ensure their malicious code executes automatically upon system boot or user logon. If confirmed malicious, this could allow attackers to maintain persistence on the host, potentially leading to further system compromise and unauthorized access to sensitive information.
The following analytic identifies the execution of RAR utilities to archive files on a system. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on process names, GUIDs, and command-line arguments. This activity is significant as threat actors, including red-teamers and malware like DarkGate, use RAR archiving to compress and exfiltrate collected data from compromised hosts. If confirmed malicious, this behavior could lead to the unauthorized transfer of sensitive information to command and control servers, posing a severe risk to data confidentiality and integrity.
The analytic detects potential data exfiltration using plain HTTP POST requests. It monitors network traffic logs, specifically the `stream_http` data source, for POST methods containing suspicious form data such as "wermgr.exe", "svchost.exe", "name=\"proclist\"", "ipconfig", "name=\"sysinfo\"", or "net view". This activity is commonly associated with malware like Trickbot, trojans, keyloggers, or APT adversaries, which use plain text HTTP POST requests to communicate with remote C2 servers. If confirmed malicious, this activity could lead to unauthorized data exfiltration, compromising sensitive information and potentially leading to further network infiltration.
Detects a potential Oracle E-Business Suite (EBS) authentication bypass attempt, associated with the exploitation of CVE-2025-61882. This activity involves an HTTP POST request to the '/OA_HTML/SyncServlet' endpoint, which is the initial step observed in the exploit chain used by threat actors like GRACEFUL SPIDER.
Detects a variety of HTTP exploitation attempts associated with the RondoDox botnet campaign. This campaign uses a 'shotgun' approach, targeting numerous vulnerabilities in internet-facing devices like routers, DVRs, and web servers.
This rule detects VPN connections originating from countries that are not the user's usual work country. It leverages VPN logs, specifically Zscaler VPN logs, to identify active connections and compares the source IP's country with a lookup of the user's expected work country. Alerts are generated when a mismatch is found, indicating a potentially unauthorized or suspicious access attempt.
Detects potential exploitation attempts against FortiWeb CVE-2025-52970. The detection looks for individual HTTP GET requests to a specific API endpoint with a crafted APSCOOKIE_FWEB cookie containing 'Era=9'. The rule enriches alerts with information about known malicious IPs without strictly filtering on them.
Detects connections to interplanetary file system (IPFS) containing a user's email address which mirrors behaviours observed in recent phishing campaigns leveraging IPFS to host credential harvesting webpages.
Detects attempts to exploit multiple vulnerabilities (CVE-2025-52905, CVE-2025-52906, CVE-2025-52907) in TOTOLINK X6000R routers. Attackers can leverage argument injection, unauthenticated command injection, and security bypasses through the '/cgi-bin/cstecgi.cgi' endpoint to achieve remote code execution or denial of service.
This rule detects the presence of Olymp Loader malware by identifying known malicious file hashes (SHA256) and network communication with associated distribution domains. It looks for these indicators across various data sources, normalizing fields for consistent output. The rule aims to identify systems infected with or communicating with Olymp Loader infrastructure.
Detects Acreed infostealer's cryptocurrency clipper activity. This rule identifies when a host first communicates with a known Acreed C2 domain (`trustdomainnet.live`) to fetch malicious wallet addresses, and then communicates with a QR code generation API (`api.zile42o.dev`) used to replace legitimate QR codes with malicious ones.
This analytic detects the use of `curl.exe` with insecure flags such as `-k`, `--insecure`, `--proxy-insecure`, or `--doh-insecure` which disable TLS certificate validation. It leverages Cisco Network Visibility Module (NVM) flow data and process arguments to identify outbound connections initiated by curl where TLS checks were explicitly disabled. This behavior may indicate an attempt to bypass certificate validation to connect to potentially untrusted or malicious endpoints, a common tactic in red team operations, malware staging, or data exfiltration over HTTPS.
Detects network traffic potentially associated with a scraper botnet variant that uses the "Hello-World/1.0" user-agent string and performs GET requests. This activity is indicative of reconnaissance or data scraping.
This analytic detects instances where an internal host attempts to communicate with over 500 ports on a single destination IP address. It includes filtering criteria to exclude applications performing scans over ephemeral port ranges, focusing on potential reconnaissance or scanning activities. Monitoring network traffic logs allows for timely detection and response to such behavior, enhancing network security by identifying and mitigating potential threats promptly.
NetworkSignatureInspected just means the network sensor saw and matched a signature (it inspected the packet) — it doesn’t mean the flow was blocked. That’s the problem.
If your machines are negotiating SMB or NTLM with unknown remote IPs, you’ve got a real risk on your hands: data leakage, credential relay, or worm-style propagation. SMB to the Internet is almost never legitimate; if you don’t recognize the remote IP, treat it as suspicious.
The KQL query includes multiple conditions to detect not only default connections on legacy (139) or modern (445) SMB ports, but also cases where SMB is running over non-standard ports (attempts to evade simple port-based detection). It also extracts the SMB negotiation state so you can spot repeated or incomplete negotiation attempts (useful to detect scanning, failed auths, or relay attempts).
If your machines are negotiating SMB or NTLM with unknown remote IPs, you’ve got a real risk on your hands: data leakage, credential relay, or worm-style propagation. SMB to the Internet is almost never legitimate; if you don’t recognize the remote IP, treat it as suspicious.
The KQL query includes multiple conditions to detect not only default connections on legacy (139) or modern (445) SMB ports, but also cases where SMB is running over non-standard ports (attempts to evade simple port-based detection). It also extracts the SMB negotiation state so you can spot repeated or incomplete negotiation attempts (useful to detect scanning, failed auths, or relay attempts).
This analytic detects intrusion events from known threat activity using Cisco Secure Firewall Intrusion Events. It leverages Cisco Secure Firewall Threat Defense IntrusionEvent logs to identify cases where one or multiple Snort signatures associated with a known threat or threat actor activity have been triggered within a one-hour time window. The detection uses a lookup table (cisco_snort_ids_to_threat_mapping) to map Snort signature IDs to known threat actors and their techniques. When multiple signatures associated with the same threat actor are triggered within the time window, and the count of unique signatures matches or exceeds the expected number of signatures for that threat technique, an alert is generated. This helps identify potential coordinated threat activity in your network environment by correlating related intrusion events that occur in close temporal proximity. Currently, this detection will alert on the following threat actors or malware families as defined in the cisco_snort_ids_to_threat_mapping lookup: ArcaneDoor, Static Tundra, AgentTesla, Amadey, AsyncRAT, Chafer, DCRAT, Lumma Stealer, Nobelium, Quasar, Remcos, Snake, Xworm. To add or update threat actors, update the cisco_snort_ids_to_threat_mapping.csv lookup file with new or modified threat names and associated Snort signature IDs.
This rule detects attempts to exploit CVE-2025-49706 in SharePoint by observing POST requests to a vulnerable aspx path, which could result in code execution or server compromise.
Detects network connections to the 'webhook.site' domain, which is used as an exfiltration endpoint by the 'Shai-Halud' supply chain attack campaign. The risk score is elevated if the specific malicious URL path is observed.
This analytic detects unexpected outbound network connections initiated by known webserver processes such as `httpd.exe`, `nginx.exe`, or `tomcat.exe` to common file sharing or public content hosting services like GitHub, Discord CDN, Transfer.sh, or Pastebin. Webservers are rarely expected to perform outbound downloads, especially to dynamic or anonymous file hosting domains. This behavior is often associated with server compromise, where an attacker uses a reverse shell, webshell, or injected task to fetch malware or tools post-exploitation. The detection leverages Cisco Network Visibility Module flow data, enriched with process context, to identify this highly suspicious behavior.
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