Elastic Endpoint Security added kernel-driver-derived file and registry telemetry to detect access to sensitive credential stores, including browser data, Windows SAM and LSA secrets, cached domain credentials, credential files, and Windows Credential Manager. Its behavior protections can block high-confidence credential-theft activity associated with tools and malware such as Mimikatz, LaZagne, AgentTesla, FormBook, and Poulight Stealer; KQL and EQL hunting can also identify processes opening multiple sensitive stores or SMB access following a network logon.
Attackers commonly extract saved browser usernames, passwords, cookies, and session tokens from stores such as Chrome’s Login Data and Firefox’s key3.db, key4.db, and logins.json. They also dump Windows LSA secrets and cached domain credentials using utilities including Mimikatz, reg save, Impacket secretsdump.py, CrackMapExec, and gsecdump. Cached Windows credentials are generally stored as DCC2/MS-Cache v2 hashes and require offline cracking rather than pass-the-hash, while Linux Active Directory integrations may retain cached credentials in SSSD or Quest database files.

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Elastic Endpoint Security 7.15 introduced kernel-driver-derived file and registry access telemetry for sensitive credential stores, including browser data, SAM, LSA secrets, cached domain credentials, credential files, and Windows Credential Manager. The release also added behavior-protection rules and KQL/EQL hunting patterns for suspected credential theft.
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