Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
711 detections
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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 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 potential credential harvesting activity associated with the Hannibal Stealer. It looks for non-standard processes (processes other than the browsers themselves) that access sensitive browser credential stores (like 'Login Data', 'cookies.sqlite', or 'key4.db') and correlate these file access events with the loading of 'bcrypt.dll' or 'CefSharp.BrowsersSubprocess.dll', which are often used for decryption or browser automation/sub-processes during credential theft.
Detects the forceful termination of web browsers using taskkill.exe with the /F (force) and /IM (image name) flags. This behavior is a common precursor for information stealers attempting to unlock browser databases for credential harvesting.
Detects patterns indicative of DPAPI key exfiltration, specifically looking for the strings 'Local State', 'CryptUnprotectData', '/Key', and 'access_token' within a file or process memory. This combination suggests an attempt to decrypt and exfiltrate credentials or tokens.
This rule detects unauthorized access, creation, or modification of browser-specific sensitive credential files (such as 'Login Data' or 'cookies.sqlite') by processes that are not recognized web browsers or trusted update services. This behavior is a common indicator of information-stealer malware attempting to harvest session cookies and stored credentials.
Detects indicators of the June 2026 Mastra npm supply chain attack, in which
144 @mastra/* packages were compromised by injecting a typosquatted dependency
'easy-day-js' (a clone of the dayjs date library) carrying an obfuscated
postinstall infostealer. The payload disables TLS validation, fetches a
second-stage payload, executes it as a detached process, and self-deletes.
Detection targets the malicious dependency reference, the postinstall execution
chain, and TLS-validation-disabling behaviour.
144 @mastra/* packages were compromised by injecting a typosquatted dependency
'easy-day-js' (a clone of the dayjs date library) carrying an obfuscated
postinstall infostealer. The payload disables TLS validation, fetches a
second-stage payload, executes it as a detached process, and self-deletes.
Detection targets the malicious dependency reference, the postinstall execution
chain, and TLS-validation-disabling behaviour.
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 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 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.
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 by non-browser processes to access browser credential stores (Login Data, Cookies, Web Data). Specifically, it monitors file read, access, or copy actions on known credential database paths for Chrome, Edge, Firefox, Brave, and Opera, and flags any activity originating from processes other than the legitimate browser executables or common security software.
Detects access to Chrome Login Data SQLite file for credential theft
Detects a non-browser process searching for Chromium Login Data, Cookies, Local State, or Firefox logins and key databases. This activity is indicative of credential access attempts where an attacker tries to extract sensitive information stored by web browsers.
Detects access to Chrome Login Data SQLite file for credential theft
This rule detects events generated by Microsoft Defender for Endpoint's Attack Surface Reduction (ASR) rules in either Audit or Block mode.
(**Toggle by commenting out line 94/95. Default is both Audit & Block**).
It covers all 19 ASR rules by matching ActionType patterns or falling back to GUIDs found in AdditionalFields. The rule extracts the friendly name of the ASR rule, the mode (Audit/Block), and relevant process information.
This rule is especially noisy when ran over an entire environment. It's recommended to scope using Audit/Block, Machine Group, and filtering to the rules you want by commenting others out.
(**Toggle by commenting out line 94/95. Default is both Audit & Block**).
It covers all 19 ASR rules by matching ActionType patterns or falling back to GUIDs found in AdditionalFields. The rule extracts the friendly name of the ASR rule, the mode (Audit/Block), and relevant process information.
This rule is especially noisy when ran over an entire environment. It's recommended to scope using Audit/Block, Machine Group, and filtering to the rules you want by commenting others out.
This rule detects when a process other than Firefox itself attempts to access critical Firefox profile artifacts such as key4.db, cert9.db, logins.json, cookies.sqlite, places.sqlite, formhistory.sqlite, and prefs.js. This activity is highly suspicious as these files contain sensitive user data including credentials, browsing history, and preferences, and are typically targeted by malware for data exfiltration or credential theft. The rule leverages causality fields for investigation into the actor and the causal process.
This rule detects attempts to access or exfiltrate DPAPI (Data Protection API) credentials stored in the 'CREDHIST' folder. Specifically, it looks for file events within the `\Microsoft\Protect\CREDHIST` folder where the initiating process is either `dpapisnoop.exe` or `powershell.exe`. `dpapisnoop.exe` is a known tool for DPAPI credential extraction, and PowerShell can also be used for similar purposes.
Detects PowerShell accessing browser Local State files to steal credentials. This rule specifically looks for file access events where the file name is 'Local State' and the initiating process is 'powershell.exe' or 'pwsh.exe'.
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