Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects network traffic containing specific User-Agent strings used by the BurrowShell implant and the Rust-based keylogger to masquerade as legitimate Windows Update or browser traffic. These User-Agent strings are 'Windows-Update-Agent/10.0.10011.Client-Protocol/2.50' and 'Mozilla/5.0 (compatible; SecureNet/1.2)'.
This rule detects network connections to or from known suspicious IP addresses and requests to known suspicious domains. These indicators are often associated with command and control (C2) activity, malware distribution, or other malicious infrastructure.
Detects DNS queries for domains associated with an active adversary-in-the-middle (AiTM) phishing campaign targeting AWS credentials.
Detects the beaconing activity of the HeaconLoad Golang downloader, a component of the BoryptGrab campaign. This malware sends HTTP POST requests containing system information to the "/healthcheck" endpoint on port 8088.
This rule is based on a phishing method that abuses normal sign-in links instead of relying on an obviously fake website at the start. The trick works by sending a person to a real sign-in service with settings that force an error and then pass the browser along to the attacker’s page. The rule stays narrow by looking for both the hidden sign-in setting and the clearly bad scope value together. That matters because silent sign-in by itself can appear in normal environments, but the bad scope value changes the story and makes the pattern much more suspicious. In plain language, this rule is trying to spot a link that pretends to be a normal sign-in step but is really being used as a doorway to a phishing or malware page after the trusted service does the redirect. Keeping both parts together helps the rule stay tied to the abusive redirect trick instead of ordinary sign-in traffic.
Detects the "EtherHiding" technique used by the FakeGit campaign. The malware queries a Polygon Mainnet smart contract via a public RPC node to resolve its current C2 server address. This rule looks for network connections to known blockchain RPC providers containing the specific function selectors used by the malware's V1 and V2 contracts.
Detects a high volume of network connections from a browser process to a high port on the local host (127.0.0.1 or ::1). This pattern can indicate a malicious website attempting to brute-force credentials for a local service, such as the OpenClaw AI agent, by abusing the browser's permission to establish WebSocket connections to localhost. The vulnerable service may not rate-limit these local connections, allowing for rapid password guessing.
Detects network connections to the primary C2 IP and port (103.106.67.63:1244) used across all modules of the StegaBin infostealer toolkit. This specific IP and port combination is highly indicative of StegaBin activity.
Detects network traffic matching patterns used by the Chrysalis backdoor for C2 communications. The malware was observed using the domain 'api.skycloudcenter.com' and mimicking DeepSeek AI API URL paths to evade detection.
This rule is meant to help analysts quickly spot a high-confidence indicator related to Google AuraInspector Salesforce Aura Audit. It is written to be easy to understand and to keep false alarms low by focusing on a very specific match: an HTTP POST to a Salesforce /aura endpoint that includes specific Aura method strings. A match does not automatically prove an attacker is currently active, and it does not prove a file was executed, but it does mean the event is important because it lines up with a public threat intelligence source. When this triggers, start by identifying the host, user, and timeframe involved, then decide whether the activity is expected for that system. If it is unexpected, preserve the related logs and any files, and look for nearby events that could explain how the indicator appeared, such as a download, a new process, or a new connection. If the same indicator appears on multiple systems, treat it as a scoping signal and expand the investigation window. Use the reference link (https://cloud.google.com/blog/topics/threat- intelligence/auditing-salesforce-aura-data-exposure) to document where the indicator came from and to support incident notes and reporting.
Detects network connections to Hugging Face to download a large Large Language Model (LLM) module, a technique used by the SURXRAT Android RAT to induce network lag and degrade device performance.
This rule set detects various activities associated with the Dohdoor malware campaign (UAT-10027). It includes detection for known malware hashes, suspicious network communication patterns such as DNS over HTTPS (DoH) to Cloudflare with specific user agents, staging URL patterns, and odd-cased infrastructure domains. Additionally, it identifies endpoint activities like curl downloading batch/command files and DLL sideloading attempts using specific DLL names and LOLBins executed from common public writeable directories. The intent is to provide strong leads for investigation into potential Dohdoor infections.
Identifies network connections to known command and control (C2) and dropper distribution infrastructure associated with the EncystPHP web shell campaign.
Detects network connections from the Claude Code CLI ('claude' or 'claude.exe') to a destination other than the official 'api.anthropic.com' endpoint. This indicates that the 'ANTHROPIC_BASE_URL' environment variable has likely been overridden by a malicious '.claude/settings.json' configuration file in an attempt to intercept and exfiltrate API keys, as described in CVE-2026-21852.
This rule detects activity associated with a specific threat actor targeting FortiGate devices. It identifies network connections to known threat actor infrastructure IPs, attempts to access FortiGate management ports (443, 8443, 10443, 4443) over TCP, and successful administrative or VPN authentications from the threat actor's IPs in Fortinet/FortiGate logs. Additionally, it looks for DCSync-style directory replication access (event ID 4662) in Windows Security logs, indicating potential Active Directory compromise.
This rule detects activity related to the EmEditor watering hole attack, specifically looking for PowerShell execution making requests to known malicious lookalike domains and network connections to the associated infrastructure. A match suggests a potential download of malicious code during what appeared to be a legitimate install or update. Investigation should focus on identifying the host, user, source of activity, and legitimacy of the install source, followed by evidence preservation, credential reset, and a search for follow-up malicious activity.
This rule detects suspicious network connections to known threat actor infrastructure associated with FortiGate exploitation, successful administrative or VPN logins to FortiGate devices from these IPs, and DCSync-style directory replication access (EventCode 4662) on Windows systems. The rule is composed of three distinct parts targeting different aspects of the attack chain.
Detects non-browser processes making outbound connections to specific Google Sheets API endpoints used by the GRIDTIDE backdoor for command and control. This activity is indicative of the malware using legitimate cloud services to disguise its C2 traffic.
This rule detects activity associated with UNC6201 exploiting Dell RecoverPoint VM (CVE-2026-22769), which involves the SLAYSTYLE/BRICKSTORM/GRIMBOLT malware. It identifies attempts to deploy WAR files via Tomcat Manager, suspicious WAR file uploads or modifications in Tomcat directories on Linux appliances, modifications to a persistence script named 'convert_hosts.sh', network communication with a GRIMBOLT C2 endpoint (149.248.11.71), and specific file hashes linked to the threat actor.
This rule detects a potential quishing (QR code phishing) attack followed by a suspicious successful sign-in to Entra ID (formerly Azure AD). It correlates URL click events or device network events containing deep link indicators (like 'tg://login', 'wa.me/settings/linked_devices', 'signal://', 'line://') or '.apk' file downloads with a successful Entra ID sign-in by the same user within a 30-minute window. This behavior suggests a user may have scanned a malicious QR code, clicked a phishing link, or downloaded a malicious application, leading to a successful but potentially compromised authentication.
This rule detects activity associated with the DYNOWIPER malware, identified by specific SHA256 hashes on endpoint telemetry or by network connections to known command and control (C2) IP addresses. The rule is split into two parts: one for endpoint detection based on file hashes and another for network/authentication logs based on IP addresses.
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