Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects HTTP responses from a web server to a client that contain JavaScript code attempting to redirect the user's browser. Specifically, it looks for the string "window.location.replace" within the HTTP response body (file.data) when the HTTP referer header indicates the request originated from Google or Bing search results. This pattern is often associated with content injection attacks where malicious code is injected into legitimate search results to redirect users to malicious sites.
Detects potential “HashJack” prompt injection attempts in AI tool activity. This technique, known as HashJack, attempts to manipulate AI models by hiding instructions after the '#' in a URL. The rule specifically looks for URLs within submitted prompts that contain fragments with suspicious keywords indicative of prompt injection, such as "ignore previous", "override instructions", "system prompt", etc.
Detects the presence of HTML tags within the URL query parameters of Claude chat application pre-fill URLs. Attackers can use this to embed invisible instructions (prompt injection) that the AI processes but the user does not see in the chat interface.
Detects attempts to inject path traversal or SQL-like syntax into the 'kid' (Key ID) parameter of a JSON Web Token (JWT) header. This may indicate an attempt to manipulate the server's key retrieval process to force signature validation with an improper key, potentially leading to an authentication bypass.
Detects successful content injection leading to process execution
Detects unexpected file creation and execution originating from common browser processes (e.g., Chrome, Firefox, Edge) combined with anomalous network content that may indicate injected payloads served via web traffic. Based on MITRE DET0349 detection guidance.
Detects suspicious file creations in temporary or user application data directories immediately following browser process activities, indicating potential injected content saved to disk. Aligns with MITRE DET0349 guidance.
SQL Database Version Discovery
Suricata
This rule detects attempts to discover the version of a SQL database, often a precursor to SQL injection attacks or other reconnaissance activities. It specifically looks for SQL queries containing keywords like 'select' and 'version' in various common formats used to retrieve database version information.
Detects malicious ASP.NET webshell activity associated with the CL0P Ransomware Gang exploiting CVE-2023-34362. The rule looks for specific HTTP headers used by the webshell, indicators of Azure Blob Storage interaction, or SQL injection attempts.
Detects agentic AI jailbreak attempts that try to establish persistent control over M365 Copilot through rule injection, universal triggers, response automation, system overrides, and persona establishment techniques. The detection analyzes the PromptText field for keywords like "from now on," "always respond," "ignore previous," "new rule," "override," and role-playing commands (e.g., "act as," "you are now") that attempt to inject persistent instructions. The search computes risk by counting distinct jailbreak indicators per user session, flagging coordinated manipulation attempts.
Detects potential prompt injection or jailbreak attempts against Ollama API endpoints by identifying requests with abnormally long response times. Attackers often craft complex, layered prompts designed to bypass AI safety controls, which typically result in extended processing times as the model attempts to parse and respond to these malicious inputs. This detection monitors /api/generate and /api/chat endpoints for requests exceeding 30 seconds, which may indicate sophisticated jailbreak techniques, multi-stage prompt injections, or attempts to extract sensitive information from the model.
Detects SQL injection attempts targeting FortiWeb (CVE-2025-25257) in HTTP GET requests to /api/fabric/device/status. The rule identifies known exploit payloads in the Authorization header, generic SQL injection patterns, and SQL statements like DROP, DELETE, INSERT, UPDATE, CREATE. It also detects known malicious source IPs targeting the vulnerable endpoint.
This analytic leverages alerts from Splunk AppDynamics SecureApp to identify and monitor exploit attempts targeting business applications. It specifically looks for vulnerabilities in web applications, including injection attacks (SQL, API abuse), deserialization vulnerabilities, remote code execution attempts, LOG4J, and zero-day attacks. These attacks typically aim to gain unauthorized access, exfiltrate sensitive data, or disrupt application functionality. Splunk AppDynamics SecureApp provides real-time detection by analyzing application-layer events and correlating attack behavior with known vulnerability signatures, categorizing attack severity, providing visibility into attacker tactics, and generating risk-based scoring and contextual alerts.
KQL Query from file: Critical Identities OAuth Grant
KQL Query from file: CloudApp Privilege OAuth Grant
KQL Query from file: Detecting BYOVDLL Abuse
KQL Query
This query searches for a string pattern detected in evasive PowerShell usage. Jupyter or SolarMarker will iterate on this pattern multiple times to read data and call additional processes. This query is not fully specific to Jupyter or SolarMarker, and will also return other malicious malware, but is unlikely to return false positives.
'Potential code injection into web server roles via IIS logs scan. Represents attempt to gain initial access using drive-by compromise technique. Detection flags events for review and filtering of authorized activity.'
This query helps hunting for BEC - File sharing tactics - Dropbox
'Identifies a match for SQL Injection attack in the Application gateway WAF logs. The Threshold value in the query can be changed as per your infrastructure's requirement.
References: https://owasp.org/Top10/A03_2021-Injection/'
References: https://owasp.org/Top10/A03_2021-Injection/'
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