Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,084 detections
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Detects suspicious modifications or registrations of AI agent tools within the registry. The rule identifies three core indicators of compromise: usage of an unverified or external registry source, unauthorized tool definition modifications (hash mismatch against baseline), and a suspicious 'update chain' where a non-standard maintainer pushes a tool update that simultaneously increases requested operational scopes.
Detects attempts to bypass LLM safety alignment by utilizing roleplay or hypothetical framing (e.g., DAN mode) alongside evidence of prompt iteration, identified by repeated moderation blocks within the same session.
Detects the execution of suspicious child processes (e.g., cmd.exe, powershell.exe, bash, wget) spawned by processes associated with public-facing appliances like Fortinet SSL-VPN, Veeam Backup & Replication, Citrix ADC, and cPanel/WHM. This behavior is often indicative of exploitation of public-facing applications (T1190) for initial access, frequently associated with ransomware actors targeting unpatched infrastructure.
Detects malicious Android application installation or launch behavior consistent with the 'Corp MDM' implant. This rule specifically identifies instances where a package named 'com.corp.mdm' is installed or launched and rapidly requests a combination of high-risk permissions including SMS and telephony access (RECEIVE_SMS, READ_SMS, CALL_PHONE) alongside notification permissions, which is characteristic of the implant's initial setup phase.
Detects extension code implementing Caesar-shift-over-base64 decoding of a remote proxy server list fetched from dead-drop hosts, feeding a PAC-based proxy configuration
Detects UNC6240 PSEMHUB.war web shell/tunnel/trojanized installer artifacts by distinctive content markers (x.jsp, u.jsp, tunnel.jsp/jspx, Ple64.exe)
Detects incoming web requests containing a 'pagename' parameter with URL-encoded path traversal sequences, which could allow unauthorized file access or directory traversal attacks against WordPress page-template resolution as described in CVE-2026-87902.
Detects the registration or installation of an MCP (Model Context Protocol) server or agent tool containing suspicious prompt-injection strings (e.g., instructions to ignore safety guardrails or role overrides), immediately followed by the execution of shell commands or unauthorized network connections originating from that tool.
Detects high-frequency authentication attempts originating from user agents associated with automation frameworks (Selenium, Playwright, Puppeteer, etc.). This pattern is often indicative of automated credential stuffing, brute force attacks, or CAPTCHA/2FA bypass attempts orchestrated by headless browsers.
This rule monitors Salesforce lead creation events for potential prompt-injection payloads. It identifies submissions containing common AI manipulation instructions, HTML tags, or suspicious outbound URLs, which could be used to hijack internal user sessions or execute malicious content within the Salesforce environment.
Detects rapid termination of specific mobile messenger applications (Max) within seconds of starting, while indicators of the Frida dynamic instrumentation tool are concurrently detected on the device. This pattern suggests the application is identifying the presence of a hooking/instrumentation environment and self-terminating as a defense mechanism. The detection is further correlated with failed connection attempts to the application's backend.
Detects suspicious/unexpected usernames appearing in Cisco ISE access.log,
consistent with exploitation of CVE-2026-76460, an unauthenticated REST API
auth-bypass in Cisco ISE / ISE-PIC (CVSS 10.0, actively exploited, CISA KEV).
Cisco's own guidance is to hunt access.log for usernames not present in the
legitimate identity store; "dummyuser" is their published example artifact.
consistent with exploitation of CVE-2026-76460, an unauthenticated REST API
auth-bypass in Cisco ISE / ISE-PIC (CVSS 10.0, actively exploited, CISA KEV).
Cisco's own guidance is to hunt access.log for usernames not present in the
legitimate identity store; "dummyuser" is their published example artifact.
The following analytic identifies instances where CrushFTP has blocked access due to exceeding the maximum number of simultaneous connections from a single IP address. This activity may indicate brute force attempts, credential stuffing, or automated attacks against the CrushFTP server. This detection is particularly relevant following the discovery of CVE-2025-31161, an authentication bypass vulnerability in CrushFTP versions 10.0.0 through 10.8.3 and 11.0.0 through 11.3.0.
Detects potential poisoning of an AI agent's RAG knowledge base or vector store through suspicious bulk ingestion or injection of imperative instruction-style content. The rule correlates these ingestion events with subsequent anomalous tool usage patterns by the same agent session, indicating a possible prompt injection or data manipulation attack aimed at altering agent behavior.
Detects potential poisoning of an AI agent's RAG knowledge base or vector store through suspicious bulk ingestion or injection of imperative instruction-style content. The rule correlates these ingestion events with subsequent anomalous tool usage patterns by the same agent session, indicating a possible prompt injection or data manipulation attack aimed at altering agent behavior.
This rule detects specific JavaScript helper functions and state machine constants commonly used in 'ClickFix' phishing campaigns (e.g., Exvicy and ErrTraffic). These scripts typically prompt users to copy and paste malicious code snippets, often disguised as error fixes or CAPTCHA resolution, to facilitate initial access.
This rule detects potential prompt injection attacks against AI agents by monitoring tool-invocation parameters. It identifies indicators such as common instruction-overriding phrases, large base64-encoded blobs, or embedded shell metacharacters within parameters when the agent's context is derived from external content (web, email, URLs, etc.).
This rule detects potential prompt injection attacks against AI agents by monitoring tool-invocation parameters. It identifies indicators such as common instruction-overriding phrases, large base64-encoded blobs, or embedded shell metacharacters within parameters when the agent's context is derived from external content (web, email, URLs, etc.).
Detects abnormal bulk API operations (upsert, batch updates, or deletions) targeting vector database or Retrieval-Augmented Generation (RAG) knowledge stores. This activity is flagged when performed by non-authorized service identities or when ingestion volume exceeds a specific threshold within a short timeframe, potentially indicating an attempt to poison the agent's memory store or retrieval corpus to facilitate indirect prompt injection.
Detects an abnormally high frequency of tool/function invocations by an AI agent within a one-minute timeframe. This pattern is indicative of a potential hijack where an attacker forces the agent into a runaway loop to perform resource exhaustion (DoS), repetitive brute-force operations, or automated exfiltration of sensitive data via manipulated tool execution.
Detects unauthorized attempts to disable, reconfigure, or bypass AI safety guardrails and moderation services, particularly when followed by high-risk tool invocations such as file deletion, network egress, or credential access. This activity indicates an attacker attempting to impair an AI agent's defensive mechanisms to facilitate malicious actions.
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