Use Cases

Compromised User and Host Detection

Cybercriminals steal credentials through spearphishing and other techniques, to pose as trusted employees and steal valuable data without raising any alarms. Niara’s multi-dimensional analytics are tuned to detect a user or host under the influence of an attacker by detecting small changes in behavior that may be suspicious, combining them with additional security context to confirm them as malicious and raise smart alerts that are correlated for an entity over time. Niara’s predictive analytics can help find advanced attacks before the damage is done.

Malicious Insider Threats

Discovering disgruntled and malicious employees engaging in fraud or sabotage is similarly challenging as they have privileges to freely move about your network and behave much the same as a compromised user — only with more impunity. Niara’s behavioral analytics detect the activities of malicious insiders by finding meaningful changes in their IT activity not only compared to their historical baseline, but within their peer groups as well. In addition, Niara’s ability to inform the machine learning models of business context focuses the attack detection on high-value asset downloads, exfiltration of sensitive information, etc.

Negligent Employee Detection

Careless actions by insiders and poorly configured assets pose significant security risks. Niara uses behavioral analytics to detect employee negligence (e.g., sharing password in violation of security policy, etc.) and misconfigured assets that may place high-value corporate information at risk.

Partner Access Protection

Business partners may not adhere to your cybersecurity requirements, despite being granted access to your corporate network to transact and exchange information. Compromised partner networks are a beachhead for attackers to gain a foothold in your network. By applying multi-dimensional analytics to activity between an enterprise and its partners, Niara will find and alert on telltale signs of partner compromise such as large increases in data flow, changes in access patterns, etc.

Threat Hunting

Organizations are becoming increasingly aggressive in proactively searching for signs of an attack that has not registered on their security systems. These groups of threat hunters tap into the expanding network of shared threat information and attack profiles and proactively look for evidence of their presence. Niara makes that easy by providing analysts a powerful workbench of both pre-configured searches and an ad hoc query language to intelligently tap into the massive volumes of data from diverse sources that Niara has collected and enriched. The analyst workbench enables the threat hunting team to quickly test complex hypotheses and find previously-unseen threats lurking inside the organization, going back months or years.

Alert Prioritization and Incident Investigation

With thousands, or even millions of daily alerts and events, where do analysts start? Niara maintains real-time entity risk scores for each entity type and graphically highlights the highest scores, the scores that have changed the most each day, watch-list focused high value users and assets, etc. Combined with comprehensive Entity360 profiles, analysts not only quickly prioritize alerts but launch immediately into efficient incident investigations and remediation.

Data Exfiltration

It’s difficult to distinguish between attackers with compromised credentials accessing and sending out sensitive information and legitimate users doing so as part of normal business. Niara applies analytics on exfiltration-sensitive activity sources (e.g., email, endpoint records, network activity to the internet, etc.) to provide the early warning analysts need to quickly detect and mitigate the impact of such attacks.

High Value Asset Protection

Sensitive assets such as source code repositories, financial information, PII data, and product design documents, are the crown jewels of an organization. A recent study found that among companies that experienced a data breach, internal actors were responsible for 43% of data loss. Protecting high-value assets from these types of internal risks is notoriously difficult because legitimate credentials are often used to access corporate resources, thereby evading existing perimeter defenses.

Niara’s behavioral analytics platform helps analysts detect and investigate potential threats to high-value assets posed by compromised users, negligent employees, or malicious insiders.

Niara solution brochure

Automated cyber and insider driven attack detection, incident prioritization and investigation and threat hunting in a single platform

F500 Financial Services Case Study

Security insights into compromised users and hosts, negligent and malicious insiders via comprehensive behavioral analytics and enabling cost-effective historical incident investigations