Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 detects VNC-based lateral movement activities within an internal network (East-West traffic).
Detects HTTP requests to download the BoryptGrab stealer, which uses a specific URL pattern containing a hardcoded build name. This activity is characteristic of the initial launchers used in the BoryptGrab campaign to fetch the main stealer component from a C2 server.
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 network traffic to known command and control (C2) domains used by the Iranian APT group Seedworm to distribute the Fakeset backdoor. These domains are hosted on the Backblaze cloud storage service.
Detects VNC-based lateral movement activities. East to West traffic
Detects the JavaScript XOR-based string reconstruction pattern used by the Coruna iOS exploit kit. This pattern maps an array of integers through String.fromCharCode with XOR to reconstruct code at runtime. Coruna contained 23 iOS exploits targeting iOS 13.0 through 17.2.1 and was used by UNC6353 (Russian espionage) and UNC6691 (Chinese financially motivated).
This rule is meant to help analysts quickly spot a high-confidence indicator related to Google ShinyHunters SaaS Defense Guidance. It is written to be easy to understand and to keep false alarms low by focusing on a very specific match: a DNS lookup to a specific domain mentioned in the report. 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/defense-against-shinyhunters- cybercrime-saas) to document where the indicator came from and to support incident notes and reporting.
This rule detects network communication with known AI model providers by checking `RemoteUrl` against a list of AI API URLs from an external CSV file. It aims to identify potential unauthorized use of AI services, data exfiltration to AI models, or to monitor AI usage within an environment.
Detects the complete CVE-2026-21902 exploitation chain against Juniper Junos OS Evolved On-Box Anomaly Detection Framework. Requires all four steps: command creation, DAG creation, DAG instance scheduling, and commit.
Detects attempts to perform Indirect Prompt Injection (IDPI) by embedding malicious instructions for AI agents or Large Language Models (LLMs) within web content. This rule identifies when common prompt injection keywords are present in conjunction with CSS techniques used to hide the text from being rendered in a browser, a method used to evade human review while targeting automated systems.
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.
Detects DNS queries for domains that match the pattern used by the PLASMAGRID malware's Domain Generation Algorithm (DGA). This malware, delivered by the Coruna iOS exploit kit, uses a DGA seeded with "lazarus" to generate 15-character domains with a ".xyz" TLD for command and control fallback.
Detects network connections to known command-and-control (C2) and distribution domains associated with the Coruna exploit kit campaigns. This includes the domain used in the Ukrainian campaign by UNC6353 and the larger set from the financially motivated UNC6691 group.
Detects Indirect Prompt Injection (IDPI) attempts where malicious instructions are dynamically injected into the DOM using JavaScript or concealed within HTML data attributes. Attackers use these methods to bypass static analysis tools and deliver hidden prompts to AI/LLM agents that process raw web content.
Detects HTTP POST requests to the SolarWinds Web Help Desk (WHD) AjaxProxy endpoint that contain hex-encoded JSON keys or values (e.g., `\xNN`).
Attackers use this technique to bypass security filters and achieve remote code execution, as detailed in the exploit chain for CVE-2025-40552 and CVE-2025-40553.
Attackers use this technique to bypass security filters and achieve remote code execution, as detailed in the exploit chain for CVE-2025-40552 and CVE-2025-40553.
Detects web content containing strings associated with destructive commands or unauthorized financial transactions, often embedded as part of an Indirect Prompt Injection (IDPI) attack. These prompts are designed to be executed by an AI agent or LLM, potentially leading to data loss, denial of service, or financial theft.
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.
COLDRIVER ROBOT chain - DNS lookup for TI delivery/C2 domains
This rule detects potential indicators of compromise related to CVE-2026-20127 in Cisco Catalyst SD-WAN systems. It focuses on two main areas: 1) suspicious successful SSH authentications for the 'vmanage-admin' account, and 2) SD-WAN control plane connection events indicating a new 'up' state. The first part looks for specific log entries related to publickey authentication for 'vmanage-admin' from any source IP. The second part identifies control connection state changes to 'up' and extracts peer type, peer system IP, and public IP from the raw logs. The rule aims to surface events that require human confirmation by comparing them against known network designs and change records, as these events can indicate unexpected relationships between devices or unauthorized privileged access.
UNC5142 CLEARSHORT - injected Web3 + BSC contract addresses in HTTP response
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