Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This analytic detects the macOS osascript utility executing JavaScript for Automation (JXA) code, identified by
the "-l JavaScript" interpreter flag, with references to the Objective-C bridge. Adversaries may abuse JXA and
Objective-C APIs to interact with macOS applications, access native system functionality, execute commands, or
perform post-exploitation activity.
the "-l JavaScript" interpreter flag, with references to the Objective-C bridge. Adversaries may abuse JXA and
Objective-C APIs to interact with macOS applications, access native system functionality, execute commands, or
perform post-exploitation activity.
Detects the execution of rclone.exe or renamed binaries with command-line flags indicative of data exfiltration to cloud storage providers such as S3, Mega, OneDrive, or Google Drive. This behavior is frequently associated with ransomware actors, including Akira, Qilin, and Storm-2570, who use Rclone to perform mass exfiltration of sensitive file share data prior to encryption (double extortion).
Detects unauthorized modifications to AI agent configuration files, including system prompts, tool allow-lists, and MCP server registration files. Such changes are often performed by processes outside of approved configuration management or infrastructure-as-code pipelines, potentially allowing for persistent manipulation of AI model behavior and capabilities.
Detects various persistence mechanisms used by the CARBONATO botnet on Linux systems, including registration of cron jobs, systemd services/timers, and the usage of 'chattr +i' to make persistence files immutable.
TokenGrabber Builder: Nuitka/PyInstaller AV-Evasion Compilation - detects Python builder scripts compiling an embedded stealer.py payload into a native executable via Nuitka or PyInstaller with AV-evasion flags
This rule detects artifacts and behaviors associated with the WaterPlum/Contagious Interview (also known as DeceptiveDevelopment) malware suite, including BeaverTail, InvisibleFerret, and related payloads. The rule specifically targets the presence of embedded family-name strings, as well as the execution of suspicious npm package installations triggered by VS Code task automation (tasks.json) or trust prompts, common in fake technical interview attack scenarios.
Detects the execution of cloud CLI tools (aws, az, gcloud) using Unix shells (bash, sh) to perform sensitive operations such as listing secrets, keys, or metadata, which may indicate credential discovery or exfiltration.
Matches archived SHA-256 hashes of known malicious CRX builds from the 'VPN for X' proxy farm extension family
Detects command-line execution patterns that exhibit hallmark traits of LLM-generated code, such as overly verbose and explanatory comments, appearing alongside common obfuscation or decoding primitives (e.g., base64, iex, eval). This combination suggests the use of AI to assist in creating decoy logic or burying malicious payloads within legitimate-appearing scripts to evade detection.
Detects the presence of an XMRig cryptocurrency miner masquerading as the systemd-logind process. The rule identifies processes named 'systemd-logind' that either reside in an incorrect file path ('/usr/sbin/systemd-logind') or utilize command-line arguments characteristic of XMRig mining activity. This behavior is associated with the CARBONATO botnet.
Detects anomalous, chained execution patterns initiated by AI agents integrated with Model Context Protocol (MCP) servers. The rule identifies a multi-stage sequence involving the invocation of browser automation tools followed by shell execution and subsequent outbound network activity, potentially indicating an AI-driven attack chaining filesystem, shell, or cloud-API access in an unauthorized manner.
Detects potential supply chain or local configuration tampering involving the Model Context Protocol (MCP). The rule identifies modification of common MCP configuration files, followed by the execution of a tool runner (node, python, npx) that spawns a scripting shell, which subsequently initiates an unusual outbound network connection.
Detects potential supply chain or local configuration tampering involving the Model Context Protocol (MCP). The rule identifies modification of common MCP configuration files, followed by the execution of a tool runner (node, python, npx) that spawns a scripting shell, which subsequently initiates an unusual outbound network connection.
Detects potential supply chain or local configuration tampering involving the Model Context Protocol (MCP). The rule identifies modification of common MCP configuration files, followed by the execution of a tool runner (node, python, npx) that spawns a scripting shell, which subsequently initiates an unusual outbound network connection.
Detects files matching known SHA256 hashes of the masqueraded MSP360 RMM v2.5.0.67 installer and associated ScreenConnect/utility payloads used in phishing-to-dual-RMM campaigns
Detects files matching known SHA256 hashes of the masqueraded MSP360 RMM v2.5.0.67 installer and associated ScreenConnect/utility payloads used in phishing-to-dual-RMM campaigns
Detects files matching known SHA256 hashes of the masqueraded MSP360 RMM v2.5.0.67 installer and associated ScreenConnect/utility payloads used in phishing-to-dual-RMM campaigns
Detects the installation of machine learning or AI software dependencies (pip, conda, npm, poetry) that either pull from unauthorized registries or match known malicious/typosquatting naming patterns (e.g., LiteLLM supply-chain compromise). The rule also monitors for newly published packages that have been flagged as suspicious.
Detects known file hashes associated with the Macfinger ClickFix campaign, including instruction text, bash scripts, and AMOS malware payloads (arm64/x86_64).
Detects CARBONATO botnet activity where malicious processes are masquerading as legitimate Linux system components. This includes XMRig mining software running as /usr/sbin/systemd-logind, process arguments attempting to mimic kernel kworker threads, or processes running from directories associated with netd-svc/resolved container images.
Detects the staging of a potential RatHat malware component by observing a native Go binary being moved into /data/local/tmp via ADB shell (uid 2000), followed by an associated service binding to local port 7912 within a 5-minute window. This sequence is characteristic of the deployment process for this specific Android threat.
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