Login Failures Anomaly Report

Tracking login failures and the cause of the failures can be difficult. Knowing which failed login events are anomalies can be even harder to track and understand. This report combines login failure events with related events to provide analysts with contextual understanding of the login failures.

LCE keeps an average count (over all collected data) of failed login attempts per hour for each IP address. This enables LCE to 'learn' the average count of events for certain times of the day. If for a certain hour, the count of failed login attempts is significantly more or less than the average for that hour, an anomaly event is triggered. Counts of events per hour are not compared to other hours to generate anomalies; a count is compared only to the average count of events for that specific hour for days in the past. An anomaly is thus a deviation from what historically occurred at that time of day, not a deviation from what occurred earlier in the day.

There are several legitimate reasons for the occasional login failure, which means that not every login failure is an attack. However, how can security analysts tell the difference between a login failure after a user changes their password, and a login failure while an attacker conducts a slow password guessing attack? The "login failure" event type denotes any authentication event where credentials were presented and were incorrect. If the event is an attack, there will most likely be other events also, such as ThreatList events, intrusion events, and Never Before Seen (NBS) events. By correlating the login failure events with other related events, analysts can begin to deduce the likelihood of an attack.

This report provides a detailed review of failed login attempts, with event counts, trend analysis, and Login Failure Anomaly events. The next 3 chapters provide details of the login failure events over 3 time periods: 12 hours, 72 hours, and 7 days. The time period chapters provide a high-level analysis of the events that have occurred during the respective time period. The final chapter uses the plugin Stats Daemon Event Statistics (800029) and finds each system with a login failure anomaly. For each system discovered, a normalized summary is provided for the NBS, login failure, threat list, and intrusion events.

The report is available in the Tenable.sc Feed, a comprehensive collection of dashboards, reports, assurance report cards and assets. The report can be easily located in the Tenable.sc Feed under the category Monitoring. The report requirements are:

• Tenable.sc 4.8.2
• LCE 6.0.0

Tenable.sc Continuous View (Tenable.sc CV) allows for the most comprehensive and integrated view of network health. Tenable.sc CV provides a unique combination of detection, reporting, and pattern recognition, utilizing industry recognized algorithms and models.  Tenable.sc CV utilizes the Log Correlation Engine (LCE) to provide deep log and event inspection to continuously discover and track users, applications, and authentication events. LCE tightly integrates with SIEMs, log management tools, malware defenses, the PVS network sensor, NetFlow, BYOD, firewalls, web, and authentication systems.

Chapters

Executive Summary – The chapter provides a high-level summary count of login failure events. The normalized events have been separated into seven different categories, each of which provides a focused view into the login failures detected.

Anomaly Analysis - This chapter leverages the LCE's user ID tracking to display the last seven days of login failures, first time seen login failures, and anomalies in login failures. For each trend line, the list of matching user IDs (if any) associated with the activity is displayed. The LCE associates user IDs with any type of event, including login failures. Displaying login failures by user ID can be very enlightening, as it often highlights access control problems not readily seen when working with IP addresses.

12 Hour Analysis - This chapter provides a detailed review of login failure events that occurred in the last 12 hours. The events collected show analysts the most recent events and provides a recent baseline to compare to the subsequent historic chapters.

72 Hour Analysis - This chapter provides a detailed review of login failure events that occurred in the last 72 hours. The events collected show analysts the recent events and provides a recent baseline to compare to the previous and subsequent chapter.

7 Day Analysis - This chapter provides a detailed review of login failure events that occurred in the last 7 days.  The events collected show analysts the recent events and provides a recent baseline to compare to the previous chapters.

Login Failure Anomaly Details - This chapter provides the contextual analysis for systems with login failure anomalies detected. The chapter first provides a summary table listing all the systems with a login failure anomaly detected using the stats informational event vulnerability. Then for each system, four tables are presented: Login Failure Summary, Intrusion Summary, NBS Summary, and Threat List. By correlating these events together, analysts can gain a better understanding of other events occurring at the same time as the failure.