Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

7,143 detections

Detects unauthorized access to sensitive credential files, such as credentials.json or .env, through HTTP GET requests, or the creation/staging of a credentials file at /tmp/creds.json, which may indicate attempts to exfiltrate or steal credentials from the local system.
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Duo Tech@duotech
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Detections.ai Community
4 months ago
105
These YARA rules detect the presence of compiled executables written in Rust, Golang, or Nim by matching specific language-related artifacts, such as compiler-generated metadata, runtime library paths, or symbol patterns within Windows PE or Linux ELF binaries.
100daysofyara 2025@100daysyara2025
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100 Days of YARA 2025
3 months ago
000
This rule detects potentially unauthorized access or activity related to MySQL databases. It monitors for external network connections to the MySQL default port (3306) that originate from non-private IP addresses, and identifies suspicious process command lines using Python's PyMySQL library that attempt to authenticate as the 'root' user.
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Duo Tech@duotech
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Detections.ai Community
4 months ago
105
Detects a Node.js process termination followed by a quick respawn of a new Node.js process by the same parent process. This pattern suggests a watchdog persistence mechanism where the parent process monitors the child, automatically restarting it if it is terminated, consistent with behaviors observed in malware such as Void Dokkaebi.
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Ethan Andrews@eandrews
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Federal Signal Detections
4 months ago
207
Detects the use of Git commands (filter-branch, rebase -i, or force-push) that rewrite local or remote commit history. These operations are often used by adversaries to hide malicious code injections, remove evidence of unauthorized changes, or manipulate developer repository integrity.
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Ethan Andrews@eandrews
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Federal Signal Detections
4 months ago
607
Detects file system artifacts indicating installation of the malicious 'ascii-fetcher' VS Code extension (v1.0.0) from the Open VSX marketplace, which bundles the malicious npm dependency '@jaymara/jsononifier' to hide its logic from static analysis.
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Ethan Andrews@eandrews
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Federal Signal Detections
4 months ago
007
Detects instances where the same file (identified by SHA256) with common lure names like 'resume', 'headshot', or 'faceswap' is being created or modified by multiple different users across the environment. This behavior is often indicative of an adversary distributing malicious files or a coordinated effort to access sensitive or tempting filenames, potentially related to social engineering or lateral movement.
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Duo Tech@duotech
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Detections.ai Community
4 months ago
003
Detects OS fingerprinting commands executed as child processes of a process that is actively listening on a network port, consistent with DOGLEASH.
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Duo Tech@duotech
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Detections.ai Community
4 months ago
005
This rule detects suspicious activity where a process initiates a network listening connection, launches a shell (sh, bash), and engages in file read or rename operations within a short 15-minute window. This behavior is indicative of a potential backdoor setup, lateral movement, or malicious script execution.
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Duo Tech@duotech
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Detections.ai Community
4 months ago
105
Detects execution of Node.js applications that utilize specific Jscrambler obfuscation versions or the presence of these versions in package.json files, which may indicate the use of compromised or unauthorized supply chain dependencies.
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Duo Tech@duotech
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Detections.ai Community
3 months ago
000
Detects the execution of a file named 'intro.js' by the Node.js runtime located within a 'node_modules' directory. This pattern is often associated with the execution of suspicious scripts, persistent backdoors, or malicious packages that attempt to masquerade as standard dependencies.
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Duo Tech@duotech
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Detections.ai Community
3 months ago
000
This rule detects the execution of mitmproxy, mitmweb, or mitmdump in reverse-proxy mode configured specifically to target login.microsoftonline.com. This behavior is highly characteristic of an adversary setting up an Adversary-in-the-Middle (AiTM) platform to perform TLS interception on authentication traffic, potentially leading to credential and session cookie theft.
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Ethan Andrews@eandrews
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Federal Signal Detections
4 months ago
406
This rule monitors for the creation of files containing the string 'readme_ransom' or the execution of processes that reference 'readme_ransom', specific known ransomware wallet addresses, or associated contact email addresses, which are indicative of post-encryption ransomware activity.
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Duo Tech@duotech
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Detections.ai Community
4 months ago
504
Detects the execution of cron jobs that utilize file transfer utilities (curl, wget) piped directly into a shell (sh, bash). This is a common "living off the land" technique used by attackers to fetch and execute remote malicious payloads for initial staging and persistence.
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Luís Marques@remotecodeexecution
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SIBS Cyberwatch
4 months ago
006
Detects Python command lines referencing the specific authencesn cryptography string used to exploit the Copy Fail vulnerability (CVE-2026-31431).
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Luís Marques@remotecodeexecution
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SIBS Cyberwatch
4 months ago
206
Detects the use of the usermod to modify the users permissions.
Which can be an indication of privilege escalation attempts on Linux systems
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Luís Marques@remotecodeexecution
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SIBS Cyberwatch
4 months ago
1306
Detects potential remote code execution (RCE) via CVE-2026-55200 in libssh2-linked applications. The rule monitors for two signals: firstly, a post-exploitation child process (such as a shell or interpreter) spawned by a common libssh2-reliant application (e.g., ssh, curl, git, php) shortly after an outbound connection to TCP ports 22 or 2222; secondly, anomalous outbound network connections to port 2222 originating from these same libssh2-linked binaries.
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Ethan Andrews@eandrews
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Federal Signal Detections
4 months ago
22054
This rule identifies endpoints that have transferred a total of more than 50MB of data to a single external, non-private IP address. The detection filters out RFC1918 private subnets and local loopback traffic, aggregating byte counts and connection attempts per endpoint, computer, and destination. This is indicative of potential data staging or exfiltration activities.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
10015
Detects large outbound network transmissions occurring on a host shortly after the creation of staged or archive files. This behavior is indicative of an attacker consolidating sensitive data (such as credentials or intelligence) into an archive and subsequently exfiltrating it over a Command and Control (C2) or other established network channel.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
12015
Detects network connection events where the requested URL contains 'dogleash' and includes common architecture suffixes (mips, arm, x64) or shell script extensions (.sh), often indicative of downloading stage payloads associated with the Dogleash malware family.
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Duo Tech@duotech
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Detections.ai Community
4 months ago
504
Detects zip archives matching the .zx_ filename prefix convention used by CrashStealer to stage encrypted exfiltration data in /tmp prior to transmission to its C2 server.
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Duo Tech@duotech
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Detections.ai Community
3 months ago
000
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