Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the presence of file system artifacts associated with the malicious Chromium extension 'Search for perplexity ai' (extension ID: flkebkiofojicogddingbdmcmkpbplcd) on an endpoint. This extension is known to perform search hijacking and keystroke exfiltration.
Shebangs (#!) are native to Unix-like operating systems (macOS and Linux). Standard Windows consoles (Command Prompt and PowerShell) do not natively use them. However, they do work on Windows when using tools such as the Python Launcher, Git Bash, Cygwin, or Unix-like environments such as WSL. In simple terms, a Shebang tells the operating system which interpreter should execute a script. For example: #!/usr/bin/python3
For this query, I would recommend performing some threat hunting first and creating a whitelist for known false positives or trusted devices (for example, devices managed by developers). Once the detection is properly tuned, it can be a good way to monitor the download or import of Shebang files on suspicious directories, making it a strong candidate for a threat detection rule.
For this query, I would recommend performing some threat hunting first and creating a whitelist for known false positives or trusted devices (for example, devices managed by developers). Once the detection is properly tuned, it can be a good way to monitor the download or import of Shebang files on suspicious directories, making it a strong candidate for a threat detection rule.
Detects unauthorized processes attempting to access sensitive browser data files (Login Data, Cookies, Web Data) that are typically used by web browsers to store credentials and session information. The rule filters out known legitimate browser processes, flagging potential credential theft or session hijacking activity.
Detects the creation of a specifically named exfiltration file ('edgeLog.txt') followed by an outbound network connection over port 443 originating from the same process storyline. This pattern is indicative of a process staging stolen data to disk and subsequently exfiltrating it over an encrypted channel to an external destination.
This rule detects the exploitation of CVE-2026-48558, a critical OIDC authentication bypass vulnerability in SimpleHelp. The detection logic correlates log events for 'Registering technician login' involving 'New Anon' sessions with subsequent configuration save requests occurring within 30 seconds. This pattern signifies the unauthorized creation of a privileged technician account by an unauthenticated attacker, bypassing standard identity verification.
This rule detects potential phishing activity by correlating emails containing links to a specific suspicious domain and path with network activity (DNS queries or direct network connections) to the same domain. It targets both the initial email delivery and subsequent user interaction (e.g., clicking the link or downloading files).
Detects indicators of exploitation attempts against the CVE-2026-55200 libssh2 heap out-of-bounds write vulnerability. The rule identifies the creation of known PoC artifacts on disk, execution of exploit harnesses or probe binaries, Python scripts masquerading as or interacting with the PoC server, and libssh2-dependent client applications making network connections to the non-standard port 2222 used by the exploit scaffold.
Detects unauthenticated HTTP requests to sensitive Gitea endpoints containing the 'X-WEBAUTH-USER' header set to 'admin'. This rule identifies exploitation attempts against misconfigured Docker deployments where 'REVERSE_PROXY_TRUSTED_PROXIES' is improperly set to a wildcard, allowing unauthorized users to impersonate administrative accounts (CVE-2026-20896).
This rule detects successful outbound SSH (port 22) connections originating from a private IP address on a device to a public IP address. This could indicate unauthorized remote access, data exfiltration, or command and control activity.
This rule detects potential SSH brute force attacks by monitoring syslog for multiple failed SSH login attempts, connection closures, or invalid user attempts from a single source IP address within a short time frame. It specifically looks for keywords like 'error', 'Connection closed', 'authentication failure', and 'invalid user' in SSHD logs.
This rule detects potential reverse shell command execution by monitoring process creation events (EventID 4688) for specific command-line strings commonly associated with reverse shells. It looks for 'bash -i', '/bin/bash', 'nc -e', and 'powershell -NoP' in the command line.
Detects suspicious execution patterns on CI/CD runners involving the decoding of base64-encoded payloads piped into sudo python3, which is often used for credential harvesting. The rule identifies this behavior through two methods: sibling process correlation where 'base64 -d' and 'sudo python3' occur within 60 seconds of each other, and the observation of interpreters (sh, bash, python, etc.) launched without arguments in conjunction with runner-specific process patterns, indicative of stdin-piped execution.
Detects Server-Side Request Forgery (SSRF) attempts using a double-slash URL manipulation technique. Adversaries append an absolute local file path (e.g., /etc/passwd or /proc/self/environ) after a GitHub blob URL to bypass URL validation logic commonly found in web proxies, API gateways, and serverless environments like GCP Cloud Run.
Detects potential data exfiltration (CVE-2026-42824) where an attacker leverages an SSRF vulnerability in Bing's search-by-image functionality to relay sensitive M365 Copilot data. The rule identifies outbound network requests to the image search endpoint containing a suspicious 'imgurl' parameter pointing to non-Microsoft infrastructure, initiated by common web browser processes.
This rule detects network connections or DNS queries originating from common web browsers (chrome.exe, msedge.exe, chromium.exe) towards domains related to Perplexity AI. Such activity may indicate data exfiltration or the use of AI tools for processing sensitive organizational data via browser-based interfaces.
Detects the presence, file creation, or execution of known proof-of-concept (PoC) scripts, binaries, and directories associated with the exploitation of the libssh2 CVE-2026-55200 vulnerability.
Detects the execution of npm install commands that include known malicious package names associated with a supply chain attack linked to the Lazarus Group. These packages are designed to impersonate the legitimate 'rollup-plugin-polyfill-node' package.
Detects potentially malicious activity involving MySQL processes, specifically focusing on the creation of files within the /var/lib/mysql-files/ directory, use of SQL 'INTO OUTFILE' for file output, or the use of 'LOAD_FILE()' to read sensitive system files like /etc/hostname or /proc/1/mountinfo, often indicative of SQL injection exploitation or unauthorized data access.
Detects the execution of command lines containing suspicious keywords associated with potential data encryption, database table destruction, or configuration tampering. These commands, such as those invoking encryption functions or dropping configuration tables, are indicative of malicious activity often performed by ransomware or wiper malware to hinder system recovery or exfiltrate and destroy data.
Detects signs of a supply chain attack, specifically referencing the IronWorm/Shai-Hulud pattern, involving the backdating of git commits, manipulation of git environment variables (GIT_COMMITTER_DATE/GIT_AUTHOR_DATE) to mask malicious activity history, and the use of 'touch' commands to modify file timestamps on project-related binaries and configuration files.
Detects the invocation of script interpreters (python, bash, powershell, etc.) initiated by package management utilities (pip, npm, gem). This pattern is often indicative of supply chain attacks, automated malicious script delivery, or post-exploitation activity where legitimate development tools are abused to execute encoded or obfuscated commands.
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