Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects network connections to known ChatGPT Custom GPT ClickFix campaign infrastructure (IPs and URLs) as reported by Huntress. This rule covers the network_connection logsource only. Domain/DNS matching is covered by a separate dns_query rule, and file-hash matching is covered by a separate process_creation rule, as Sigma only supports one logsource per rule.
Detects network connections to known ChatGPT Custom GPT ClickFix campaign infrastructure (IPs and URLs) as reported by Huntress. This rule covers the network_connection logsource only. Domain/DNS matching is covered by a separate dns_query rule, and file-hash matching is covered by a separate process_creation rule, as Sigma only supports one logsource per rule.
Detects HTTP GET requests to external services 'trycloudflare.com' or 'workers.dev' that return a file content starting with the 'MZ' and 'PE' header signatures within the first 256 bytes, indicating a Windows executable payload download often associated with AvisLoader activity.
Detects anomalous remote access patterns on a single endpoint, specifically involving AnyDesk or TeamViewer sessions originating from multiple distinct geographical locations combined with usage by multiple distinct user accounts. This pattern is consistent with DPRK IT worker fraud (Wagemole) involving shared laptop farms.
This rule detects potential prompt injection attacks against internal AI-powered assistants, agents, or LLM gateways. It monitors network HTTP requests for common patterns used to override system instructions, bypass safety filters, or force the model to adopt a privileged, unauthorized persona (e.g., administrator or debug mode). These techniques are often used in social engineering to manipulate the AI's output or security posture.
Detects HTTP requests to popular LLM API services (OpenAI, Anthropic, Google, Cohere) containing common jailbreak or role-play patterns. These patterns attempt to bypass safety guardrails by using techniques such as persona-switching (e.g., 'DAN'), hypothetical scenario framing, or unauthorized security testing pretexts.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
Detects anomalous AI-assisted activity where multiple processes (specifically AI developer tools) appear to be chaining operations by writing to and reading from shared local directories (e.g., 'handoff', 'artifacts') followed by network requests to known AI service APIs. This pattern may indicate automated task chaining or unauthorized exfiltration of context/code to AI platforms.
This rule detects network connections from internal devices to a list of known malicious domains and IP addresses. These indicators are commonly associated with command and control (C2) infrastructure or malicious activity, and alerting on these connections can help identify compromised systems within the environment.
Detects network navigation to Google Sites pages that match patterns associated with known Ledger-impersonating phishing campaigns. These sites are often reached through redirect chains involving Google Ads, cloud storage, and rotating domains.
Detects HTTP POST requests containing potential credential exfiltration indicators, specifically targeting the '/google.php' endpoint with 'do=login&', 'user=', and 'pass=' parameters. This pattern is associated with FlowerStorm (Storm-1167) AiTM phishing kits.
Detects network activity (TCP, DNS, TLS, HTTP) associated with the UNC6240 threat actor's infrastructure, specifically targeting communications with known malicious IP addresses and domains used in a campaign leveraging PeopleSoft-related lures.
Detects the execution of the 'fanout.sh' utility from the /tmp directory, which subsequently spawns 'sshpass' child processes to perform rapid, non-interactive SSH authentication attempts ('StrictHostKeyChecking=no') against multiple internal hosts within a 10-minute window. This behavior is indicative of automated lateral movement, specifically observed by threat actor UNC6240.
This rule detects activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
This rule detects activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
This rule detects activity involving known malicious indicators of compromise (IOCs), including specific IP addresses, domains, and file hashes. It monitors network connections, file system activity, process execution, and email attachments, filtering out common security tools to reduce noise.
This rule detects potential persistence via scheduled tasks that masquerade as legitimate network components (e.g., 'System Health Monitor'), as well as abnormal use of WebDav via rundll32.exe or net.exe in the context of the Star Blizzard (COLDRIVER) campaign. It monitors for task creation/updates, schtasks command lines, registry artifacts related to task scheduling, and suspicious WebDav network utility usage, while excluding common security tool processes.
This rule detects potential persistence via scheduled tasks that masquerade as legitimate network components (e.g., 'System Health Monitor'), as well as abnormal use of WebDav via rundll32.exe or net.exe in the context of the Star Blizzard (COLDRIVER) campaign. It monitors for task creation/updates, schtasks command lines, registry artifacts related to task scheduling, and suspicious WebDav network utility usage, while excluding common security tool processes.
This rule monitors for network communication with known malicious infrastructure (IPs/domains) and the execution of specific suspicious file names. It correlates device network events, file system activity, and process execution, specifically flagging attempts to execute MSI installers or other binaries associated with the identified threat indicators.
This rule monitors for network communication with known malicious infrastructure (IPs/domains) and the execution of specific suspicious file names. It correlates device network events, file system activity, and process execution, specifically flagging attempts to execute MSI installers or other binaries associated with the identified threat indicators.
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