Employees or other users within an organisation may become compromised if an adversary gains access to their credentials. Bad actors can masquerade as legitimate employees going about their normal business, making them hard to detect. Their under-the-radar activities often take weeks or months to be discovered, resulting in more severe data breaches or remediation costs.
Lateral Movement
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Lateral movement is a growing problem, with nearly 60% of external attacks utilising this stealthy tactic. Adversaries use lateral movement to pass systematically through a network to find sensitive data or high value assets. After gaining initial access, attackers probe other assets for vulnerabilities to compromise other accounts, escalate privileges and ultimately exfiltrate data or do other damage. Traditional security tools are unable to distinguish between lateral movement activity associated with compromised accounts and normal user behavior.
Exabeam prescribes key data sources for engineers to ingest so analysts can detect risky access and techniques, like pass the hash, pass the ticket, and more. Exabeam behavioral models put anomalous activity, like first time or failed access to hosts and assets in the context of the historical behavior of that user, their peers, and their organisation to clearly identify adversary behavior from normal activity.
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