
Arnold Chan
@slazTrusted contributorCompletionist
2 followers2,099 downloads4,374 copies51 likes26,083 views
7,555 detections
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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 AI agent tooling (e.g., Copilot, Cursor, Ollama) that makes outbound network calls to known AI model providers followed by the execution of suspicious shell commands within a short duration. The rule flags high-severity activities such as download-cradles, credential reconnaissance, LOLBin usage, and persistence mechanisms. Informational alerts are generated for standard CLI activity within the same timeframe.
Detects instances where AI-based coding or agent-driven tools (e.g., Cursor, Claude Code, AutoGPT) perform suspicious file archiving/packaging activities followed by network egress to unauthorized or known exfiltration-prone services. This helps identify potential data exfiltration by AI agents or compromised development environments.
Detects AI coding assistants and LLM agent frameworks attempting to access, read, or export sensitive credential files, registry hives, or application secrets. The rule monitors both file system operations on known secret locations and process execution patterns indicative of credential dumping or API token retrieval by these tools.
This rule monitors for execution of suspicious files or processes and network communication associated with known malicious indicators (hashes, domains, and IP addresses) typically used by specific threat actors for command and control (C2) and payload delivery.
Detects a behavioral pattern characteristic of Everest ransomware, where a sequence of rapid process terminations occurs within a 20-second window. The rule identifies the coordinated termination of security/analysis tools, antivirus/backup/database services, and other high-memory processes on a single device, excluding known legitimate maintenance processes.
Detects clicks on sponsored search engine ads that redirect users to Google Cloud Storage (GCS) buckets with names or paths designed to impersonate the 'Ledger' brand. These artifacts are indicative of a malvertising campaign using typosquatted storage paths to deliver malicious payloads or credential harvesting pages.
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.
This rule detects HTTP POST requests to Vercel-hosted domains containing suspected phishing telemetry (such as device fingerprinting, keystrokes, and user agent collection) originated from a Google Sites frame. This is a common pattern for phishing kits masquerading as legitimate Ledger service pages to harvest credentials and hardware information.
Detects rapid, large-scale deletion of Azure storage accounts by a single identity within a short timeframe. This behavior is indicative of destructive activity, such as a malicious actor attempting to disrupt service availability or impact organizational data, rather than typical administrative teardown.
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