Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
154 detections
Filters
Last updated
All Time
Detection languages
90
22
15
15
4
Contributors
38
20
18
12
9
Categories
60
40
30
28
23
Platforms
52
49
33
17
9
Products / Services
22
21
20
17
14
MITRE Techniques
18,104
15,609
12,572
8,382
6,201
CVEs
8
8
4
3
3
IDS Classtypes
19
2
1
IDS Protocols
8
5
4
3
2
Detects abnormal PHP execution volume storms, process crashes handled by crash reporters (such as werfault.exe, apport, systemd-coredump), or application error events related to PHP, which may indicate denial of service attacks, exploitation attempts, or severe application instability.
Detects abnormal PHP execution volume storms, process crashes handled by crash reporters (such as werfault.exe, apport, systemd-coredump), or application error events related to PHP, which may indicate denial of service attacks, exploitation attempts, or severe application instability.
Detects repeated PHP memory exhaustion (OOM) errors combined with segmentation faults or session warnings within a short timeframe, which may indicate application instability, resource exhaustion attacks, or exploitation attempts.
Detects abnormal PHP execution volume storms, process crashes handled by crash reporters (such as werfault.exe, apport, systemd-coredump), or application error events related to PHP, which may indicate denial of service attacks, exploitation attempts, or severe application instability.
Detects abnormal PHP execution volume storms, process crashes handled by crash reporters (such as werfault.exe, apport, systemd-coredump), or application error events related to PHP, which may indicate denial of service attacks, exploitation attempts, or severe application instability.
Detects inbound UDP traffic on port 443 (QUIC) targeting known HTTP/3-capable server processes (such as Caddy, Traefik, Cloudflared) followed closely by the termination or crash of that process, which may indicate an exploit attempt or vulnerability leading to denial of service.
Detects an inbound QUIC/UDP port 443 burst targeting a Bun process (bun.exe or bun) from external IP addresses, followed by the process going completely silent on the network within a short time window. This pattern correlates with potential exploitation or denial-of-service conditions involving network parsing anomalies.
Detects repeated PHP memory exhaustion (OOM) errors combined with segmentation faults or session warnings within a short timeframe, which may indicate application instability, resource exhaustion attacks, or exploitation attempts.
Detects an unusual rate of terminated connections at the BIG-IP. Mass termination
can indicate resource exhaustion, a denial of service in progress, or an attacker
disrupting the application tier — and the load balancer sees it before the
application does.
Onboarding: F5BIGIP is ingested via Syslog (Bloo extractor 81).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=firewall where sourcename='F5BIGIP' and action='CONNECTION_TERMINATED'
| duration 10m
| groupby srcip, dstip, dstport, app
| select srcip, dstip, dstport, app, count(*) as cnt
| having cnt > 100
can indicate resource exhaustion, a denial of service in progress, or an attacker
disrupting the application tier — and the load balancer sees it before the
application does.
Onboarding: F5BIGIP is ingested via Syslog (Bloo extractor 81).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=firewall where sourcename='F5BIGIP' and action='CONNECTION_TERMINATED'
| duration 10m
| groupby srcip, dstip, dstport, app
| select srcip, dstip, dstport, app, count(*) as cnt
| having cnt > 100
Identifies high Ollama runner counts and large model buffer allocations as possible resource pressure indicators. Memory values vary with model size and hardware, and these operational logs do not establish malicious intent; validate against host capacity and workload baselines.
Detects potential abuse of the Linux Magic SysRq (System Request) key by adversaries with root or sufficient privileges to manipulate or destabilize a system.
Writing to /proc/sysrq-trigger can crash the system, kill processes, or bypass standard logging.
Monitoring SysRq abuse helps detect stealthy post-exploitation activity.
Correlate with related EXECVE or PROCTITLE events to identify the process or user responsible for the access or modification.
Writing to /proc/sysrq-trigger can crash the system, kill processes, or bypass standard logging.
Monitoring SysRq abuse helps detect stealthy post-exploitation activity.
Correlate with related EXECVE or PROCTITLE events to identify the process or user responsible for the access or modification.
Detects high-frequency, short-duration UDP flow activity on NetScaler VPN ports (443/4433) indicative of volumetric or malformed DTLS handshake probing, potentially associated with exploitation attempts like CVE-2026-88772.
Detects repeated crashes or restarts of the Citrix NetScaler packet engine (nsppe) correlated with a concurrent spike in inbound DTLS traffic. This pattern is indicative of potential memory-overflow exploitation attempts (consistent with CVE-2026-88772) targeting the VPN virtual server functionality, leading to a Denial of Service (DoS) condition.
Detects high volumes of DTLS/UDP session-initiation traffic targeting NetScaler VPN virtual servers that are immediately followed by appliance-level error logs or crashes. This behavior is indicative of active probing or exploitation attempts, such as those associated with CVE-2026-88772, where malicious payloads cause service instability.
Detects high-frequency restarts, HA failovers, or process crashes (e.g., nsppe, nsaaad) on Citrix NetScaler appliances. This behavior is indicative of potential denial-of-service exploitation, such as the CVE-2026-88772 DTLS memory-overflow vulnerability.
This rule detects an exploitation attempt targeting a memory overflow vulnerability in Citrix NetScaler Gateway, specifically identifying oversized DTLS handshake length fields in UDP traffic. The rule triggers when a DTLS packet exceeds the specified size threshold, which is indicative of a buffer overflow attack intended to cause a service crash (Denial of Service).
This rule detects an exploitation attempt targeting a memory overflow vulnerability in Citrix NetScaler Gateway, specifically identifying oversized DTLS handshake length fields in UDP traffic. The rule triggers when a DTLS packet exceeds the specified size threshold, which is indicative of a buffer overflow attack intended to cause a service crash (Denial of Service).
This rule detects an exploitation attempt targeting a memory overflow vulnerability in Citrix NetScaler Gateway, specifically identifying oversized DTLS handshake length fields in UDP traffic. The rule triggers when a DTLS packet exceeds the specified size threshold, which is indicative of a buffer overflow attack intended to cause a service crash (Denial of Service).
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.
This rule detects potential exploitation of CVE-2026-86134, a NULL pointer dereference vulnerability in WatchGuard Fireware. It identifies a burst of authentication-related requests (login, authd, management) targeting a device, followed by system logs indicating a service crash, daemon restart, or core dump within a short correlation window. This behavior is indicative of a Denial of Service attack.
Detects attempts to perform a Denial of Service (DoS) attack against an AI-enabled system by flooding the inference API with high volumes of requests or overly large inputs (high token counts). The rule identifies potential resource exhaustion by correlating high request rates or large input sizes with system-wide impacts, such as increased inference queue depth or excessive GPU utilization, which could impede service availability for other users.
Page 1 of 8