Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects attempts by non-system, potentially unauthorized processes to access the LSASS process memory. This behavior is commonly associated with credential dumping techniques used by adversaries to harvest sensitive authentication material from the Local Security Authority Subsystem Service.
Detects unauthorized processes attempting to read, modify, or create files within common browser credential locations (Chrome, Firefox, Edge, and Windows Credential Manager). Legitimate browser processes and their known signers are excluded, focusing on suspicious secondary processes or tools frequently utilized by infostealers like Lumma and RedLine to dump credentials.
Detects attempts by non-system, potentially unauthorized processes to access the LSASS process memory. This behavior is commonly associated with credential dumping techniques used by adversaries to harvest sensitive authentication material from the Local Security Authority Subsystem Service.
Detects unauthorized access, creation, or modification of sensitive credential and token files (e.g., OAuth tokens, AWS credentials, gcloud tokens) in common user directories like AppData or .config by processes other than established browsers or legitimate cloud CLI tools. This behavior is indicative of credential theft or SaaS pivot attacks.
This rule monitors process execution events for the usage of common memory dumping utility names (e.g., procdump, memdump, coredump, crashdump) via command-line interfaces such as cmd.exe or powershell.exe. This activity is frequently associated with attackers attempting to dump sensitive process memory, such as LSASS, to extract credentials or other secrets from memory.
Detects unauthorized or non-standard processes attempting to create, modify, or access sensitive cloud configuration and credential files, such as AWS credentials, Azure CLI token caches, or GCP application default credentials. This behavior is indicative of potential credential theft or unauthorized access to cloud environment tokens.
Detects unauthorized access (File Creation, Modification, Rename, or Deletion) to common web browser cookie and credential storage files by non-browser processes. This behavior is a common indicator of information-stealing malware attempting to extract session cookies and credentials for later use.
Detects the creation of a Temporary Access Pass (TAP) by a service principal or agent identity, rather than a human administrator. This scenario indicates a potential compromise where a Temporary Access Agent with UserAuthMethod-TAP.ReadWrite.All permission is abused to generate a TAP for a Global Administrator.
Detects potentially unauthorized or suspicious child process execution originating from IDEs associated with Amazon Q/CodeWhisperer. The rule monitors for common shell execution (bash, sh, node) or AWS-related command-line activity that may indicate credential harvesting or exfiltration via IDE extensions.
This rule detects potential unauthorized access to AWS credentials by monitoring process creation events involving the 'get-caller-identity' command. It identifies scenarios where AWS access key environment variables are accessed or manipulated, and monitors common shell or node processes executing commands to query AWS identity information, which may indicate credential exfiltration or reconnaissance by an attacker.
Detects unauthorized processes reading, creating, or modifying sensitive files associated with local AI development tools and assistants (e.g., Claude, Codex, Gemini, Cline, Opencode, Kilo). This rule monitors for file operations outside of the known, legitimate AI tool processes, suggesting potential credential theft or configuration tampering by malicious software.
This rule detects unauthorized or suspicious processes attempting to access sensitive local browser extension data or known password manager vault files (e.g., .kdbx, vault.json, data.json). This behavior is characteristic of infostealer malware or credential-harvesting activities attempting to extract stored secrets.
Detects unauthorized mass access to AI development tool configuration files and credentials. The rule identifies processes reading sensitive files associated with tools such as Claude (mcp.json, projects), Codex (config.toml, sessions), Gemini (settings.json, .env), Cline, OpenCode, and Kilo.
This rule detects attempts by unsigned or suspicious processes (often residing in temporary directories) to access sensitive cryptocurrency wallet files such as 'wallet.dat', keystore JSON files, and files containing recovery seed phrases. This behavior is indicative of credential theft commonly associated with infostealer campaigns like DeepLoad and DeerStealer.
Detects the Djinn Stealer malware accessing sensitive configuration files and credential stores related to AI coding assistants (e.g., Claude, Codex, Gemini, Cline) and common development utilities (e.g., AWS, GKE, SSH) on Linux workstations. It also detects the creation of a 'linux-process-env.json' file, which is an artifact used by the stealer to exfiltrate environment variables harvested from process memory.
Detects behavior indicative of the InvisibleFerret information stealer, specifically focusing on Python execution spawned by development tools (VS Code/Node.js), unauthorized access to browser-based credential stores or local crypto wallets, and suspicious outbound network activity originating from Python processes spawned by development/automation tools.
Detects unauthorized cross-process handle requests to sensitive Windows authentication processes (lsass.exe and winlogon.exe) by non-system and non-whitelisted processes. This behavior is commonly associated with credential dumping techniques and malicious process injection aimed at stealing sensitive authentication data.
This rule detects file-related events (creation, modification, deletion, or renaming) targeting common SSH private key files (id_rsa, id_ed25519, id_ecdsa) and host keys. It filters out expected processes like standard SSH clients and key generation tools, flagging potential unauthorized access or credential harvesting by other applications.
Detects instances where a process not associated with a known web browser attempts to read sensitive browser credential stores (such as Chrome Login Data, Edge Login Data, or Firefox key4.db/logins.json). This behavior is characteristic of infostealers attempting to extract saved browser credentials.
This rule detects instances where development-related processes (such as Code.exe or node.exe) spawn web browser processes (like chrome.exe, firefox.exe, or msedge.exe). This pattern is often indicative of an adversary attempting to leverage developer environments or cross-platform applications to interact with browser-based session data, cookies, or cached credentials.
Detects unauthorized cross-process handle requests to sensitive Windows authentication processes (lsass.exe and winlogon.exe) by non-system and non-whitelisted processes. This behavior is commonly associated with credential dumping techniques and malicious process injection aimed at stealing sensitive authentication data.
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