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Detect Anomalies in Your Cloud User Accounts

Compromised Accounts, Malicious Insiders, and Privileged Users

Cisco Cloudlock provides cross-platform User and Entity Behavior Analytics (UEBA) for SaaS, IaaS, PaaS, and IDaaS environments. Cisco Cloudlock leverages advanced machine learning algorithms to detect anomalies based on factors such as activities outside of whitelisted countries and actions across distances at impossible speeds. Attackers are defeating today’s security controls that rely on the network perimeter, firewalls, or exclusively focus on a specific platform.

Activities across platforms are not correlated, making it difficult or impossible to identify suspicious behavioral patterns. At the same time, security teams are inundated with alerts that lack priority, useful information, or context. Faced with a flood of unhelpful alerts, the legitimate security breaches get overlooked. This problem is magnified with the use of cloud applications and platforms, as organizations often have little visibility into the activities of their users in their SaaS, PaaS, IaaS, and IDaaS environments.

Problems We Solve

Compromised Accounts

Attackers are compromising cloud application accounts at astonishing rates. Targeted attacks, such as spearphishing have reached a level of sophistication where they are virtually indistinguishable from legitimate communications. In many cases, there are not any files or malicious URLs involved in an attack, rendering traditional security solutions, including anti-malware and anti-phishing tools, incapable of addressing these threats.

Malicious Insiders

As malicious insiders are unlikely to trigger typical security telemetry when performing nefarious tasks, detecting insider threats is extremely difficult. Given the ease with which malicious individuals can leverage cloud applications to access, modify, distribute, and exfiltrate sensitive information, detecting and mitigating malicious insiders is crucial.

Dangerous Privileged Account Actions

Privileged users not only have access to a high volume of sensitive data, but also have administrative rights, such as configuration settings and user provisioning within applications. As such, ensuring the integrity of privileged accounts is critical to security.

How We Do It

User and Entity Behavior Analytics

Cisco Cloudlock detects activity indicative of account compromise by correlating and analyzing usage information across SaaS, IaaS, PaaS, and IDaaS environments to identify anomalies. Additionally, through advanced machine learning, Cisco Cloudlock adaptively learns user behavior to uncover suspicious behavior patterns. Additionally, Cisco Cloudlock integrates with IDaaS solutions to analyze login behavior for the thousands of applications connected to those services.

Policy-Based Enforcement

Cisco Cloudlock identifies suspicious behavior such as a single user logging in from geographically disparate locations in a short period of time, an unusually high volume of file downloads, and access outside of typical business hours triggers. Additionally, Cisco Cloudlock enables the whitelisting and blacklisting of specific IP addresses and IP ranges to defend against account compromise. When anomalies are detected, Cisco Cloudlock enables a range of automated remediation actions, including administrative alerting, end-user notification, and even requiring step-up authentication through integrations with IDaaS solutions.

Threat Protection

Cisco Cloudlock integrates with malware detection and threat emulation services to both detect cloud-resident malware and enable automated threat response workflows, including administrative alerting, end-user notification, file quarantine, and more. Cisco Cloudlock also enables the whitelisting and blacklisting of activity from both specific geographies and IP ranges for additional security confidence.

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