Log management is the analysis, filtering, classification, and reporting of system event logs. For security teams to be able to leverage logs in an effort to spot potentially suspicious activity, a security operations center (SOC) likely needs an effective security information and event management (SIEM) platform to help sift log data and raise pertinent alerts.
A log file is, according to the cybersecurity infrastructure and security agency (CISA), “files that provide the data that are the bread and butter of incident response, enabling network analysts and incident responders to investigate and diagnose issues and suspicious activity from network perimeter to epicenter.”
A log file keeps a record of an event – usually of something incorrect that occurred – so that security teams can leverage SIEM technology to investigate and take action if necessary.
Centralized log management correlates the millions of daily events in an environment directly to users and assets taking those actions. The goal is to highlight risk across an organization and prioritize where to search if potentially suspicious activity is taking place.
Log management processes should be able to integrate with an existing security stack, providing correlated context in which to view data and customizing event and investigation reports. Log data, context, prioritized investigations, and detailed reporting: That’s the power of proper log management.
The difference between log management and SIEM is that SIEM tools are designed to combine log management capabilities with other functionalities, with the ultimate goal of enacting stronger security measures that can more thoroughly protect the organization.
At this point, anyone reading this would probably think a modern SIEM would be the way to go for one-stop-logging, data security analysis, and helpful, more actionable insights in the name of better protecting their environment.
However, each business and accompanying security organization is unique and has specific needs. Perhaps a log management tool is all that is needed. Or perhaps a separate log management tool with powerful capabilities focused specifically on logging is what is needed. It’s important to take stock of what is actually needed so that budget is allocated for the right tools to further the right goals.
Log management is important because it helps to centralize logs onto one tool so that a security organization can search, correlate, and derive insights from one location. With this ability, diagnostic personnel can pinpoint an issue and get it prioritized for remediation faster.
Log management tools are also important because of the following ways they can benefit IT and security organizations:
These benefits make a log management tool one of the most important aspects of a security organization. It's a must-have in the quest to automate the organization of mountains of data and search for actionable insights to continuously counter threats.
Just like with anything security-related, there can be challenges when attempting to implement a log management program or a SIEM platform that incorporates robust log management capabilities.
Many of today's logging solutions can handle lots of formats. Most, however, can’t do much with custom logs or flat log formats. It may not always be possible to structure or format logs nicely as access to the app or service source code may not be available to update the formats so that a logging solution can handle them.
Logs as data is the concept of using logs to extract key metrics or trends about system behavior. Logs can be a rich data source, provided a team can work with the log format AND perform analytical functions on key metrics extracted from log events.
Many traditional logging solutions have focused on being able to simply index and search logs. While being able to effectively and efficiently search logs is important for investigations and remediations, it’s critical to apply analysis to key metrics in log events.
It can be a difficult task to correctly correlate data. There are lots of tools out there that send log data into one big bucket and provide the user with largely unintelligible results. Being able to access, correlate, and gain actionable insights from logs in real time is a key performance indicator (KPI) for SOC success. Ensuring data security for those raw events is also critical.
Knowing what to look for can be the hardest challenge of all. This is one of the biggest issues with log management tools that focus on search and complex query languages. It doesn’t matter how powerful a search language is if it doesn’t show a user what to look for.
To not get bogged down by the above challenges, it's important to establish baseline best practices when standing up a log management tool or larger program that tackles log management capabilities.
Don't log blindly. Instead, carefully consider what is being logged and why. Logging, like any significant IT and/or security component, needs to have a strategy. When structuring DevOps setup or even releasing a single new feature, an organized logging plan is a must. Without a well-defined strategy, teams could eventually find themselves manually managing an ever-growing set of log data, ultimately complicating the process of identifying important information.
Logs should always be automatically collected and shipped to a centralized location, separate from a production environment. Consolidating log data facilitates organized management and enriches analysis capabilities, enabling a SOC to efficiently run cross analyses and identify correlations between different data sources.
Forwarding log data to a centralized location enables system administrators to grant developer, QA, and support teams access to log data without giving them access to production environments. As a result, these teams can use log data to debug issues without risk of impacting the environment.
End-to-end logging into a centralized location allows dynamic aggregation of various streams of data from different sources. These include applications, servers, and more for correlation of key trends and metrics. Correlating data enables quick and confident identification and understanding of events that are causing log management system malfunctions.
Troubleshooting and debugging only scratch the surface of what log data has to offer. Whereas logs were once considered a painful last resort for finding information, today’s logging tools can empower everyone from developers to data scientists to identify useful trends and key insights from their applications and systems.
Treating log monitoring and events as data creates opportunities to apply statistical analysis to user events and system activities. Grouping event types and summing values enables comparison of events over time. This level of insight opens the door to making better-informed business decisions based on data often unavailable outside of logs.
A log monitoring and management service that is only accessible to a highly technical team severely limits an organization’s opportunity to benefit from log data. A log management and analytics tool should give developers live-tail debugging; administrators real-time alerting; data-scientists aggregated data visualizations; and support teams live search and filtering capabilities. It should do all of this without requiring anyone to ever access the production environment.