Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects SYSTEM privilege escalation attempts via ctfmon.exe or cloudfiles.exe processes.
Detects Python processes attempting to decrypt browser credential databases using DPAPI or CryptUnprotectData. This behavior is characteristic of malware like InvisibleFerret, which targets stored browser credentials.
Detects Python searching local vaults and configuration for password managers such as KeePass, 1Password, Bitwarden, or LastPass. This activity is associated with the InvisibleFerret malware.
Detects attempts to exfiltrate environment variables by piping the output of 'env' or 'printenv' commands into 'curl'. This technique can be used by adversaries, such as the Miasma malware, to quickly steal sensitive API keys or other credentials stored in environment variables.
Detects the gh-token-monitor script using grep to extract GitHub Classic or Fine-Grained tokens (matching the ghp_ or gho_ structure) from the filesystem. This rule specifically looks for process command lines containing 'grep' and the regex pattern 'gh[po]_[a-zA-Z0-9]{36}', which is indicative of searching for GitHub tokens.
Detects attempts by non-browser processes like Python, Node.js, CScript, or WScript to access browser-related SQLite database files such as 'Login Data', 'Cookies', or 'Web Data'. This activity is indicative of credential access or data exfiltration.
Detects a non-Firefox process creating staged copies of at least three NSS, login, cookie, history, or preference files from Firefox-style profiles. The logic requires the reported SessionGate, Remus, or AnimateClipper structure rather than a standalone executable name.
Detects suspicious device access patterns and multiple failed authentication attempts from unmanaged devices and outside the corporate network, combined with Azure AD Identity Protection risk states. This rule identifies potential credential access attempts or account compromise.
Detects potential credential access attempts indicative of infostealer activity or brute-force attacks, where an account experiences multiple failed login attempts followed by a successful login within a defined timeframe (5 minutes to 8 hours). This pattern suggests an adversary may be using stolen credentials or attempting to brute-force an account.
Detects PowerShell invoking Windows.Internal.InstallService.Control to create an install work item via the UNCanny coercion primitive. This COM-based API call triggers the Windows Store Install Service to process a work item from an attacker-controlled UNC path, resulting in NTLM machine account coercion or SYSTEM-level DLL execution.
Detects scripts (Python/Node/VBS) directly accessing Chrome or OS-level DPAPI structures (Login Data, Cookies) to extract user credentials.
Correlates the execution of an executable initiated by cscript.exe with the subsequent access of Chrome's 'Login Data' file, indicating an attempt at offline DPAPI decryption, potentially by the Laravel Stealer malware.
Detects suspicious access to network device configuration files or routing table exports, potentially indicating compromise by the Salt Typhoon threat actor. This rule correlates file access events on critical configuration files (e.g., running-config, startup-config, BGP routes) within sensitive directories with network or remote interactive logons by local administrators.
This rule detects processes that exhibit behavior consistent with XWorm RAT's clipboard hijacking capabilities. It identifies processes making persistent OpenClipboard API calls or showing unusual access patterns to clipboard-related registry keys, specifically looking for modifications to the 'Run' registry key with data containing 'xworm', 'clipboard', or 'clip'. Common legitimate processes are excluded to reduce false positives.
Detects suspicious file read or access events targeting cryptocurrency wallet files (e.g., wallet.dat, keystore, .metamask, Exodus wallet) and browser extension data stores (e.g., Chrome Local Extension Settings, MetaMask, BraveSoftware). The rule specifically excludes common browser processes to reduce false positives, indicating an attempt by an unauthorized process to enumerate or scrape sensitive cryptocurrency-related data.
This rule detects potential credential exposure by identifying HTTP requests to IIS servers (W3CIISLog) that contain keywords like 'password' or 'token' in the URI query string, with a successful status code (200). This could indicate sensitive information being passed insecurely.
Detects access to LSA Secrets stored in registry for service account credentials
Detects abuse of Active Directory Certificate Services for credential forgery
This YARA rule detects the presence of a credential stealer by identifying a cluster of file names commonly associated with Firefox profile data. The rule specifically looks for at least five out of seven distinct file names: 'key4.db', 'cert9.db', 'cookies.sqlite', 'logins.json', 'formhistory.sqlite', 'places.sqlite', and 'prefs.js'. These files are critical components of a Firefox profile, storing sensitive information such as encryption keys, certificates, cookies, login credentials, browsing history, and user preferences. The co-occurrence of these file names within a scanned target suggests an attempt to access, exfiltrate, or manipulate Firefox user data, often indicative of malware like credential stealers.
This rule detects attempts to access or dump the Local Security Authority Subsystem Service (LSASS) process memory or the NTDS.dit file, which can contain sensitive credential information. It specifically looks for Security Event ID 4656 (handle to an object was requested) where the target object is 'lsass.exe', 'lsass.bin', or 'ntds.dit', with specific access masks ('0x1fffff' or '0x1410'), and excludes common system accounts. A high count of such access attempts within an hour from a non-system user triggers the alert.
This rule detects suspicious sign-in attempts to Azure AD where Conditional Access policies were not applied, the sign-in was successful, and the user agent string indicates a bot, crawler, headless browser, or common scripting tools like curl, wget, or python. It specifically looks for multiple such logins or logins from multiple unique devices within a 5-minute window for the same user and risk detail.
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