Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
168 detections
Filters
Last updated
All Time
Detection languages
87
52
26
1
1
Contributors
44
38
21
15
10
Categories
88
69
30
24
19
Platforms
106
35
24
4
4
Products / Services
10,660
9,755
6,689
4,418
3,748
MITRE Techniques
59
49
36
35
24
CVEs
3
2
2
2
1
Detects HTTP proxy traffic containing specific header or cookie patterns associated with the Evilginx2 or BigBear adversary-in-the-middle (AiTM) phishing frameworks. These frameworks use these artifacts to proxy connections and facilitate the theft of session tokens for MFA bypass.
Detects outbound HTTP requests traversing a proxy where the User-Agent string contains structurally consistent but algorithmically randomized components. This pattern is characteristic of AI-generated C2 client code attempting to create plausible yet non-standard browser signatures for each beacon. Detection relies on identifying User-Agent strings that follow a standard browser template (e.g., Chrome/Safari) but include anomalous hex/alphanumeric tokens in the version fields.
Detects external reconnaissance activity targeting AI backend services. Adversaries scan for known AI infrastructure ports (such as TensorFlow Serving, Triton, or Ray) and common API paths (e.g., /v1/models, /predict) to identify potential targets. The detection utilizes proxy logs to correlate these suspicious network attributes, high request rates, or known scanning user agents.
Detects high volumes of HTTP redirect responses (3xx status codes) associated with a single client IP address, which is indicative of a redirect chain often used in malicious activity such as drive-by compromise or social engineering campaigns involving fake browser updates or 'ClickFix' lures.
Detects network activity associated with the GhostCode phishing kit backend. The rule monitors for specific API endpoints used for credential and MFA harvesting, including loading configurations, geolocation, and polling for captured data, combined with specific session cookie identifiers.
Detects an adversary-in-the-middle (AiTM) phishing pattern where the legitimate Microsoft authentication URL is embedded as a sub-path within an attacker-controlled proxy domain. This technique is characteristic of AiTM kits, such as Evilginx2, which proxy the legitimate Microsoft authentication flow to capture credentials and session cookies.
Detects attempts to perform prompt injection against internal Large Language Model (LLM) inference APIs. The rule monitors HTTP proxy logs for specific query parameters designed to trick the model into disclosing its underlying system instructions or hidden prompts.
This rule detects potential Adversary-in-the-Middle (AiTM) phishing attacks targeting Microsoft 365 authentication flows. It identifies suspicious proxy traffic that contains authentication-related URIs or session-related cookies (such as ESTSAUTHPERSISTENT or refresh tokens) originating from hosts other than recognized Microsoft domains. This behavior is indicative of an attacker using a reverse proxy, such as Evilginx2, to intercept user credentials and session cookies in real-time.
Detects the 'ted' backdoor or similar malicious activity attempting to manipulate HAProxy's internal connection counters by accessing or writing to the HAProxy process memory (/proc/[pid]/mem or /proc/self/mem). This behavior is characteristic of an attempt to evade backend logging and statistics tracking by directly modifying process memory structures.
Detects the creation or modification of files within the /tmp directory that follow a specific naming convention (t[number]_w.pipe) by an HAProxy process. This pattern is often associated with inter-process communication or potential post-exploitation activity where HAProxy is leveraged to handle named pipes for malicious command execution or data redirection.
This rule identifies a discrepancy between actual network connections processed by HAProxy and the corresponding entries in its server-side logs. Such inconsistencies can indicate the presence of a malicious backdoor compiled into or injected into the HAProxy process, designed to facilitate C2 traffic while evading standard monitoring by suppressing or omitting logging for those connections.
This rule detects potential exploitation or unauthorized interaction with an HAProxy service. It correlates process execution on Linux systems involving the HAProxy PID file with subsequent network traffic containing the suspicious string 'writeservice_info' within a one-hour window.
This rule identifies a discrepancy between actual network connections processed by HAProxy and the corresponding entries in its server-side logs. Such inconsistencies can indicate the presence of a malicious backdoor compiled into or injected into the HAProxy process, designed to facilitate C2 traffic while evading standard monitoring by suppressing or omitting logging for those connections.
Detects the 'ted' backdoor or similar malicious activity attempting to manipulate HAProxy's internal connection counters by accessing or writing to the HAProxy process memory (/proc/[pid]/mem or /proc/self/mem). This behavior is characteristic of an attempt to evade backend logging and statistics tracking by directly modifying process memory structures.
This rule identifies a discrepancy between actual network connections processed by HAProxy and the corresponding entries in its server-side logs. Such inconsistencies can indicate the presence of a malicious backdoor compiled into or injected into the HAProxy process, designed to facilitate C2 traffic while evading standard monitoring by suppressing or omitting logging for those connections.
Detects the 'ted' backdoor or similar malicious activity attempting to manipulate HAProxy's internal connection counters by accessing or writing to the HAProxy process memory (/proc/[pid]/mem or /proc/self/mem). This behavior is characteristic of an attempt to evade backend logging and statistics tracking by directly modifying process memory structures.
This rule detects potential exploitation or unauthorized interaction with an HAProxy service. It correlates process execution on Linux systems involving the HAProxy PID file with subsequent network traffic containing the suspicious string 'writeservice_info' within a one-hour window.
Detects the creation or modification of files within the /tmp directory that follow a specific naming convention (t[number]_w.pipe) by an HAProxy process. This pattern is often associated with inter-process communication or potential post-exploitation activity where HAProxy is leveraged to handle named pipes for malicious command execution or data redirection.
This rule detects potential exploitation or unauthorized interaction with an HAProxy service. It correlates process execution on Linux systems involving the HAProxy PID file with subsequent network traffic containing the suspicious string 'writeservice_info' within a one-hour window.
Detects the creation or modification of files within the /tmp directory that follow a specific naming convention (t[number]_w.pipe) by an HAProxy process. This pattern is often associated with inter-process communication or potential post-exploitation activity where HAProxy is leveraged to handle named pipes for malicious command execution or data redirection.
Detects the creation or modification of files within the /tmp directory that follow a specific naming convention (t[number]_w.pipe) by an HAProxy process. This pattern is often associated with inter-process communication or potential post-exploitation activity where HAProxy is leveraged to handle named pipes for malicious command execution or data redirection.
Page 1 of 8