Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects a Slowloris Slow HTTP DoS attack. It triggers when a single source IP sends 100 HTTP GET requests within a 300-second window to the internal network. Slowloris attacks work by holding open many HTTP connections to a web server, eventually exhausting the server's connection pool and making it unavailable to legitimate users.
This rule detects an application layer HTTP POST flood, which is a type of Denial of Service (DoS) attack. It triggers when a single destination receives 200 or more HTTP POST requests within a 10-second window. This high volume of POST requests is indicative of an attempt to exhaust server resources or bandwidth.
This rule detects a denial-of-service attack characterized by a high volume of HTTP GET requests targeting a server within a short timeframe. Specifically, it triggers if a single destination IP address receives 500 or more HTTP GET requests within a 10-second window, indicating a potential HTTP request flood aimed at exhausting service resources.
This rule detects a CHARGEN Reflection Amplification Attack. It specifically looks for UDP traffic on port 19 (the CHARGEN service port) directed towards the home network. A threshold of 50 packets within 5 seconds, tracked by destination, is used to identify potential amplification attempts, indicating a denial-of-service attack.
This rule detects potential C2 beaconing activity over HTTP. It specifically looks for HTTP GET requests where the URI path consists of 8 to 16 lowercase alphanumeric characters. The rule uses a threshold of 20 such requests within 60 seconds from the same source IP address to identify beaconing behavior.
This rule detects an 'Email Subscription Bomb' attack, where an attacker automates sign-ups to various services using a victim's email address. The goal is to flood the victim's inbox with confirmation emails, potentially causing a denial of service or distracting them from other malicious activities. The rule specifically looks for SMTP traffic to port 25 containing the phrase 'confirm your subscription' (case-insensitive) and triggers an alert if this content is seen 50 times within 60 seconds from the same destination IP address.
This rule detects attempts to replace cryptocurrency wallet addresses within HTTP POST requests. It specifically looks for patterns matching Bitcoin (P2PKH, P2SH, Bech32) and Ethereum (0x) wallet addresses in the client body of HTTP POST requests. This activity is indicative of clipboard hijacking or similar malware that aims to redirect cryptocurrency transactions to an attacker's wallet.
This rule detects potential tampering with financial transaction data during transit. It specifically looks for TCP traffic flowing to a server, where the data size is between 100 and 500 bytes, and the content contains both "amount" and "transfer" (case-insensitive). This combination suggests an attempt to modify financial transaction details.
This rule detects the use of AMQP (Advanced Message Queuing Protocol) on port 5672, specifically looking for the 'AMQP' content within the first 4 bytes of the TCP payload. It triggers an alert if this pattern is observed 5 times within 60 seconds from the same source IP, indicating potential Command and Control (C2) activity using AMQP as a communication channel.
FTP Used as C2 Command Channel
Suricata
This rule detects potential command and control (C2) activity over FTP by identifying a high frequency of 'RETR' (retrieve) commands. A threshold of 20 'RETR' commands within 60 seconds from the same source IP address triggers the alert. This pattern can indicate an attacker using FTP to download commands or tools from a C2 server.
This rule detects HTTP POST requests from the home network to any destination that contain a large amount of junk data padding in the client body. Specifically, it looks for a client body size greater than 1000 bytes and a PCRE match for at least 500 alphanumeric characters, indicating potential command and control (C2) communication using data padding for obfuscation or to bypass detection. A threshold is set to trigger an alert if 10 such requests are observed from the same source within 60 seconds.
This rule detects network traffic that uses a TLS certificate with the common name (CN) 'Major Cobalt Strike'. This specific CN is a known default value used by the Cobalt Strike command and control (C2) framework. Detection of this certificate indicates potential Cobalt Strike C2 communication within the network.
This rule detects unusual application traffic on TCP port 8443. It triggers an alert if a source IP address initiates more than 20 TCP connections to port 8443 within a 60-second window. This threshold-based detection aims to identify potentially malicious or anomalous communication patterns that might indicate command and control activity or data exfiltration over a non-standard port often used for HTTPS.
This rule detects DNS queries for TXT records that contain specific patterns indicative of DNS calculation C2 (Command and Control) activity. The pattern searched for is a PCRE regex matching two alphanumeric strings, each 4 to 8 characters long, separated by a dot (e.g., 'abcd.efgh.'). This type of activity is often associated with malware using DNS TXT records to encode C2 instructions or data, potentially involving IP math for dynamic C2 server resolution. The rule includes a threshold to prevent excessive alerts, triggering if 5 such queries are observed from the same source within 60 seconds.
This rule detects potential callback activity from a remote hardware implant. It specifically looks for HTTP requests where the URI contains common callback patterns like '/callback', '/checkin', '/ping', or '/heartbeat', and the User-Agent header indicates a scripting tool such as 'python', 'curl', or 'wget'. The rule also specifies that the HTTP body size should be between 1 and 199 bytes, and it uses a threshold to trigger an alert if 10 such events occur within 60 seconds from the same source.
This rule detects potential data staging activity on a remote SMB share. It specifically looks for traffic to port 445 (SMB) containing 'ADMIN$' (case-insensitive) with a data size greater than 65000 bytes. A threshold of 20 such events within 60 seconds from the same source IP will trigger an alert, indicating a high volume of data being transferred to an administrative share, which could precede exfiltration.
This rule detects potential RDP session hijacking attempts by looking for the string "tscon" within TCP traffic destined for port 3389 (RDP). The 'tscon' command can be used to connect to or take control of another user's RDP session.
This rule detects the planting of script files, specifically PowerShell scripts (.ps1), on shared network drives. It looks for SMB traffic directed to a server on port 445 (SMB) that contains both the string ".ps1" (case-insensitive) and the string "\\share\\" (case-insensitive). This activity is indicative of an attacker staging scripts on a network share for potential lateral movement within a network.
This rule detects a high volume of HTTP requests to the Confluence REST API endpoint '/rest/api/content'. This pattern of access could indicate an attempt to bulk download content from Confluence spaces, potentially for data exfiltration or reconnaissance purposes. The threshold is set to trigger if 30 such requests are observed from a single source IP within a 60-second window.
This rule detects a high volume of HTTP requests to a Confluence Wiki instance that include both '/wiki/' and 'export' in the URI. Specifically, it triggers if 10 such requests are observed from the same source IP within a 60-second window. This behavior could indicate an attempt to bulk export pages from a Confluence Wiki, potentially for data exfiltration.
This rule detects bulk data access from an internal information repository. It triggers when a single source IP address performs 50 or more HTTP GET requests within a 30-second window to any destination. This behavior could indicate an attempt to exfiltrate or rapidly collect large amounts of data from internal web-based resources.
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