Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This detection identifies execution of the file synchronization utility "rclone".
It leverages Cisco Network Visibility Module logs, specifically flow data in order to capture process executions
initiating network connections.
While rclone is a legitimate command-line tool for syncing data to cloud storage providers, it has been widely abused by threat actors for data exfiltration.
This analytic inspects process name and arguments for rclone and flags usage of suspicious flags.
If matched, this could indicate malicious usage for stealthy data exfiltration or cloud abuse.
It leverages Cisco Network Visibility Module logs, specifically flow data in order to capture process executions
initiating network connections.
While rclone is a legitimate command-line tool for syncing data to cloud storage providers, it has been widely abused by threat actors for data exfiltration.
This analytic inspects process name and arguments for rclone and flags usage of suspicious flags.
If matched, this could indicate malicious usage for stealthy data exfiltration or cloud abuse.
This analytic identifies the use of Chromium-based browsers (like Microsoft Edge) running in headless mode with the `--dump-dom` argument.
This behavior has been observed in attack campaigns such as DUCKTAIL, where browsers are automated to stealthily download content from the internet using direct URLs or suspicious hosting platforms.
The detection focuses on identifying connections to known file-sharing domains or direct IPs extracted from command-line arguments and cross-checks those against the destination of the flow.
Since it leverages Cisco Network Visibility Module telemetry, the rule triggers only if a network connection is made.
This behavior has been observed in attack campaigns such as DUCKTAIL, where browsers are automated to stealthily download content from the internet using direct URLs or suspicious hosting platforms.
The detection focuses on identifying connections to known file-sharing domains or direct IPs extracted from command-line arguments and cross-checks those against the destination of the flow.
Since it leverages Cisco Network Visibility Module telemetry, the rule triggers only if a network connection is made.
Detects DNS lookups and outbound network connections to known command and control (C2) and staging domains associated with the STAC4924 campaign. The rule performs strict matching on domain names to ensure that subdomains are identified while avoiding false positives from partial string matches within URLs.
This rule detects security alerts (IDS, WAF, or infrastructure logs) indicating exploitation attempts against JFrog Artifactory instances related to CVE-2026-66384, specifically involving cache poisoning techniques observed in recent threat campaigns.
This rule detects potential command injection attacks targeting the Zimbra 'swatchdog' service, specifically involving the abuse of SNMP trap notifications (CVE-2026-73570). The attack works by injecting malicious shell metacharacters into the 'zimbra-MIB::zmServiceName' argument, which is processed by a Perl-invoked 'swatchdog' script. The rule monitors process execution events for shell commands spawned by the swatchdog utility that contain suspicious shell operators and the targeted MIB parameter.
Detects instances where a browser extension is installed, followed within a two-hour window by the browser process making network connections to generative AI service domains. This behavior is indicative of potential malicious browser extension activity, such as scraping or exfiltrating session/browsing data to third-party AI backend services.
This rule monitors package installation logs for indicators of packages potentially generated or suggested by AI tools (e.g., Copilot, code assistants) being installed in a target environment. It specifically looks for a low volume of installations (<=3) for packages that have been published within the last 14 days, which is a pattern often associated with the 'Publish Hallucinated Entities' technique in AI systems, where malicious or hallucinated code packages are introduced into the supply chain.
This rule detects anomalous increases in inbound network connection volume or unique remote IP address counts associated with a specific process running on a Linux host. This behavior can be indicative of automated scanning, brute-forcing attempts, or a Denial of Service (DoS) attack targeting an exposed API service.
Detects container runtime processes (e.g., docker, podman, crictl) launching containers with elevated privilege flags (such as --privileged, --net=host, or mounting the host root directory) or pulling images from non-standard IP-based registries. These activities are indicative of potential container escapes, persistence mechanisms, or the use of untrusted/malicious container images.
Detects non-CLI and non-DevOps utility processes accessing sensitive cloud credential and configuration files, including AWS SSO caches, AWS credentials, kubeconfig, and gcloud configuration files. This behavior is indicative of credential theft or discovery by infostealers attempting to gain unauthorized access to cloud environments.
This rule identifies suspicious post-exploitation activity where an anomalous or unauthenticated NetScaler VPN session (potentially exploiting CVE-2026-88771 or CVE-2026-88772) is followed by the creation or modification of SSH authorized_keys files or related credential manipulation commands on internal hosts, suggesting an attacker establishing persistence.
This rule detects potential credential stuffing attacks by monitoring high-volume authentication attempts against web application login endpoints. It specifically flags scenarios where a high number of unique source IP addresses interact with a login endpoint (e.g., /login, /signin) within a short window, which is characteristic of automated, distributed credential stuffing tools using proxy networks to rotate IPs.
Detects HTTP requests containing common web exploit patterns (SQLi, XSS, RCE) that exhibit characteristics of automated, mutating payload generation often utilized in AI-assisted fuzzing or vulnerability scanning tools. The rule monitors for encoded, obfuscated, or highly varied payload syntax within URI query strings.
Detects inbound HTTP POST requests to the /generate endpoint of a Hugging Face Text Generation Inference (TGI) server. Such requests indicate attempts to use or interact with the inference API, potentially without authentication, which could lead to unauthorized resource utilization or model interaction if the service is not properly secured.
Detects high-frequency outbound network connections to known large language model (LLM) API providers (OpenAI, xAI, Anthropic) originating from a single endpoint within a short timeframe. This activity is indicative of potential API key theft, where an attacker uses a compromised legitimate key to exhaust credit quotas or exfiltrate data via unauthorized API calls, bypassing the intended application.
Detects a non-root user invoking 'busctl call' against the system bus - the core of the
ptrace_may_dream / AccountsService abuse path (CVE-2026-46333 class). Enriched by decoding
the D-Bus call target (service/member), a CallCategory verdict (AccountsService account
modification, systemd run-as-root, polkit, PackageKit, generic mutating call), a burst
counter that surfaces the pidfd_getfd race loop, RiskScore / TriagePriority and DeviceInfo
context. NOTE: the FD-theft primitive itself is invisible to MDE; this detects the busctl
trigger and account-modification aftermath. Detection logic adapted from Elastic Security Labs.
ptrace_may_dream / AccountsService abuse path (CVE-2026-46333 class). Enriched by decoding
the D-Bus call target (service/member), a CallCategory verdict (AccountsService account
modification, systemd run-as-root, polkit, PackageKit, generic mutating call), a burst
counter that surfaces the pidfd_getfd race loop, RiskScore / TriagePriority and DeviceInfo
context. NOTE: the FD-theft primitive itself is invisible to MDE; this detects the busctl
trigger and account-modification aftermath. Detection logic adapted from Elastic Security Labs.
Detects usage of the Rclone utility (or renamed binaries) to transfer data to various cloud storage backends (S3, Mega, pCloud, SFTP, WebDAV). The detection correlates this activity with the execution of common archival tools (7-Zip, WinRAR, TAR) within one hour prior to the data transfer, which is a common behavior of adversaries preparing data for exfiltration.
Detects the creation of application-specific passwords named 'ZimbraWeb' in Zimbra environments. This pattern is associated with potential persistence mechanisms or credential access attempts where an adversary creates a dedicated service or app password to maintain access, as identified in CVE-2025-66376.
Detects the installation or execution of known MALFEX malicious packages via npm or Node.js, which are used as entry points for polyglot or disguised payload delivery.
Detects the creation of scheduled tasks (Windows), cron jobs (Linux), or systemd timers where the initiating process is a common scripting or runtime interpreter (e.g., Python, Node.js, PowerShell, Java). This activity is often indicative of persistence mechanisms being established by a compromised agent or script-based process.
Detects unauthorized creation or modification of AI agent system prompts, guardrails, or policy configuration files. This rule monitors for changes made by processes or users other than those identified as authorized CI/CD deployment agents or service accounts, helping to prevent unauthorized tampering with AI agent behavior or safety policies.
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