Logger 6.6.1 Demo Script
- Pavan Raja
- Apr 8, 2025
- 19 min read
Summary:
Based on the information provided, here's a detailed summary of what we can infer about International plc and their operations:
### Company Overview **Name:** International plc **Registration Details:** Registered in England and Wales with company number 5134647. **Headquarters Address:** The Lawn, 22-30 Old Bath Road, Berkshire, RG14 1Q.
### Business Activities The text does not provide specific details about the exact nature of International plc's business activities. However, it mentions that they are involved in network management and cybersecurity, specifically mentioning Logger Smart Reporting for VLSM (Variable Length Subnet Mask) network management and the use of FortiGate devices for enterprise network security analysis.
### Key Points from the Text 1. **Logger Smart Reporting:** The text describes how to use Logger's features for advanced querying and reporting, which suggests that International plc provides services related to network monitoring and cybersecurity analytics. 2. **FortiGate Integration:** Mention of Fortinet devices indicates a focus on enterprise-level security solutions, suggesting possible roles as a systems integrator or provider of specialized networking hardware and software solutions. 3. **Dashboard View:** The ability to visualize key performance indicators across multiple tables points towards capabilities in data visualization and business intelligence services. 4. **Compliance and Data Security:** The mention of secure data integration through Voltage SecureData and ArcSight Smart Connectors indicates a commitment to compliance with data security regulations, suggesting possible roles as a professional service provider or technology vendor that focuses on solutions that respect and protect sensitive information.
### Conclusion From the provided text, International plc appears to be a company involved in providing network management services, cybersecurity solutions, and related business intelligence tools primarily for enterprise clients. Their focus seems to be on offering software products and professional services that enable organizations to manage their networks effectively while ensuring high standards of data security and compliance with regulatory requirements.
Details:
The provided document is a demonstration script for ArcSight Logger version 6.6.1, dated October 1, 2018, with a version number V2.7. It outlines various use cases and configurations to enhance the functionality of ArcSight Logger in a demonstration environment. Here's a summary of each section:
1. **Overview**: Introduces the demonstration script for ArcSight Logger 6.6.1, stating that it requires a demonstration virtual machine with at least Logger v6.6.1. The script is accompanied by PowerPoint slides showing the steps and interactions during the demonstration.
2. **How to Install a Demonstration License**: Provides instructions on installing a demonstration license for ArcSight Logger 6.6.1, ensuring that all necessary permissions are granted and that the license server details are correctly configured.
3. **Modification of Secure Data Configuration**: Offers guidance on enhancing the configuration of Secure Data within Logger to improve its performance during demonstrations. This includes setting up custom configurations or modifications as required by the demonstration scenario.
4. **Search for Malicious IP Addresses, using Logger Lookups**: Explains how to use Logger's lookup capabilities to identify and analyze malicious IP addresses in network traffic data. This involves configuring search queries based on pre-defined indicators of compromise (IoCs).
5. **ArcSight Categorization Makes It Easier – Device Independent Login Failures across Devices**: Discusses how categorization tools within ArcSight can simplify the analysis of failed login attempts from various devices, helping to identify patterns and potential security breaches.
6. **Ports and IPs: Analyzing HTTPS traffic; Who Talks to my Web Servers?**: Provides a walkthrough on analyzing HTTPS traffic through specific ports to understand which entities are communicating with web servers. This is crucial for network security monitoring and auditing.
7. **RARE EVENTS: Searching for the Needle in the Haystack FAST**: Offers strategies for efficiently searching for rare events using Logger, focusing on quick response times and effective data analysis techniques.
8. **User Investigation: Insider Threat, Data Leak Discovery**: Discusses how to use ArcSight Logger for investigating potential insider threats and detecting unauthorized data leakage through user behavior analytics.
9. **Compliance: Auditor Role, Read Only, Limited Access**: Explains how to configure the system as an auditor role with read-only access and limited administrative privileges to comply with security standards and audits.
10. **IT Ops Use Case: Web Server Down, Unauthorized Changes**: Demonstrates how Logger can be used to detect unauthorized changes to web servers and handle incidents where a server is down or compromised.
11. **Application Development Use Case: Multi Line, App Dev**: Discusses the integration of Logger with application development environments to provide detailed logs for debugging and performance analysis.
12. **NetFlow Use Case: Who is Talking to My SQL Servers**: Explains how NetFlow data can be analyzed within Logger to understand network traffic patterns related to database servers like MySQL.
13. **Raw Events and Regex Use Case**: Covers the use of raw event data and regular expressions in Logger for more complex log analysis that may not fit into predefined categories.
14. **Finding failed logins from RAW events (“Discover Fields”)**: Provides a detailed guide on using "Discover Fields" to extract information from raw logs related to failed login attempts.
15. **Finding and masking credit card numbers**: Demonstrates techniques for identifying and optionally masking credit card numbers in log data, which is crucial for compliance with PCI DSS.
16. **Analyzing Machine Transactions**: Discusses how Logger can be used to analyze machine-generated transactions to detect anomalies or potential security breaches.
17. **Scheduled Updates for Logger LOOKUP**: Explains how to set up scheduled updates for log lookups in Logger, ensuring that the system remains current with threat intelligence and network changes.
18. **EVAL: URL Analysis – Length of a Field**: Provides an evaluation of analyzing fields related to URLs within logs to assess performance and usability.
19. **Smart Network Searches: Using Logger’s “insubnet” Operator**: Explains how the "insubnet" operator can be used in smart network searches within Logger for targeted log analysis.
20. **EVAL: Decoding URLs**: Demonstrates the process of decoding URLs within Logger to extract more detailed information from URL fields.
21. **Dashboard for 15 Tables**: Shows how to create a dashboard that integrates and displays data from 15 different tables, providing an overview view of multiple log sources.
22. **FortiGate - Logger partnership**: Discusses the integration between FortiGate firewalls and ArcSight Logger for enhanced network security monitoring.
23. **Dynamic Analysis using Smart Reports, Sparklines**: Explains how to use smart reports and sparklines in Logger to perform dynamic log analysis directly within the reporting interface.
24. **Device Types via “Tree Map” and “Packed Circles” Visualizations**: Demonstrates the use of visual analytics tools like Tree Map and Packed Circles to visualize different types of devices connected to the network based on log data.
25. **Secure Data**: Provides an overview of ArcSight Secure Data, emphasizing its role in protecting sensitive information within the organization's logs.
26. **Appendix A – Revision History**: Lists all revisions and updates made to this demonstration script since its initial release.
This document serves as a comprehensive guide for anyone looking to demonstrate or understand the capabilities of ArcSight Logger, covering various aspects from basic configuration to advanced log analysis techniques.
The provided information outlines several steps and considerations related to installing a demonstration license for Logger, configuring Secure Data settings for demonstrations, and utilizing Logger Lookups to find malicious IP addresses. Here's a summary of the key points:
1. **Installation of Demonstration License:**
ADP 2.0+, ArcMC 2.5+, and Logger 6.3+ demonstration platforms do not come with an ADP license by design.
To install your own license, you need:
1 x Logger ADP base license (applied to Logger)
1 x Logger capacity uplift license (applied in ArcMC)
Switch on ArcMC as an ADP license server, apply the base license in Logger, and then apply a capacity uplift license in ArcMC. This setup makes your device ADP managed.
2. **Configuration of Secure Data:**
The demonstration machine comes with pre-set valid Secure Data configuration including encrypted fields (rawEvent and destinationUserName).
To remove the red padlock indicating encryption during demonstrations not involving Secure Data:
Go to Configuration SecureData Configuration, remove the entry for destinationUserName.
If demonstrating Secure Data use case is intended, add back destinationUserName as an encrypted field.
3. **Utilizing Logger Lookups:**
Use Lookup Files for static correlation and enrichment of events with contextual information.
In a demonstration scenario involving known malicious IP addresses, import these into a Lookup Table named Malicious_Addresses.
Perform a search using the lookup table to identify connections from malicious IPs to web servers on port 443 (use queries like 'dpt=443' or 'destinationPort=443').
These steps and considerations ensure that demonstration setups are tailored for specific use cases, enhancing security analysis and compliance during demonstrations.
The provided text discusses how to narrow down search results for events involving communication on port 443, specifically looking for malicious IP addresses. It suggests using the lookup operator for static correlation to compare source IP addresses with entries in a Lookup File called "Malicious_Addresses." This method significantly reduces the number of entries from over 100,000 to just a few dozen, making it easier to identify relevant events.
The text also briefly touches on improvements to the Logger User Interface and how indexed fields can affect search times. It explains that Lookup Files can enrich events with contextual data, providing summarized fields like deviceProduct and deviceVendor from the Logger, as well as category and score information based on the Lookup File.
Additionally, there's a section about creating a new Lookup File based on search results, demonstrating how to export search results to a CSV file and then converting this into a new Lookup File. The text also briefly mentions using SmartConnector categorization for further query refinement before suggesting workarounds due to a regression bug in Logger 6.5.
Finally, the text provides instructions on customizing the chart layout to display event details more effectively, such as recognizing an SQL injection attack based on the category and score from the Lookup File.
In summary, this text is about optimizing search operations for network events involving specific ports by leveraging static correlation with a malicious IP address lookup file in a Logger interface.
The text provides a step-by-step guide on how to use Logger for various tasks such as creating a dashboard with top malicious domains and IPs, utilizing ArcSight Categorization for logging failed logins across different devices, and analyzing network traffic using ports and IP addresses. It emphasizes the flexibility and value of these features when dealing with varying device types or adding new vendors. The text suggests that by leveraging Logger's capabilities like categorization and customizable reports, organizations can efficiently manage and analyze security events without extensive modification for each change in device or event type.
The provided text discusses how to use Logger for analyzing network traffic events such as HTTP traffic on port 443. It explains various methods including using fields like sourceAddress and destinationPort to filter data, grouping by product names and addresses, and categorizing outcomes. Additionally, it covers advanced features like the "top" command which aggregates common events, the "tail" command for least common occurrences, and the "sum" command for traffic volume analysis. The text also highlights Logger's ability to normalize and categorize data effectively, making it useful for detecting unusual activities or anomalies in network traffic.
Logger Super Indexing is a feature that significantly enhances search performance in large datasets by automatically maintaining indexes for specific fields such as source and destination IP Addresses, Hostnames, and Usernames. This method offers impressive scan rates, potentially reaching tens of millions of events per second, and can be incredibly effective even when searching for rare or non-existent events.
In the demonstration provided, Logger Super Indexing was used to find a login event from 7 years worth of data in just under 10 seconds, demonstrating its efficiency. The search term didn't exist within the dataset, but with Super Indexing, it returned results almost instantly, showcasing its effectiveness when searching for rare or non-existent events.
Another significant feature discussed is the ability to use a custom Login Banner within Logger, which allows companies to display their policies and ensure users have acknowledged them. This feature adds an extra layer of security and compliance by providing a customizable login interface.
The user investigation section covers how to investigate potential insider threats using Logger for data leak discovery in incident response scenarios. Customizing the login banner is one action that can be taken as part of this process, enhancing the overall security posture of the organization.
Finally, various dashboards within Logger are discussed, showcasing different panels and functionalities based on user roles and interests. This includes a Security dashboard with features like NetFlow Top Destination Ports and customizability options for panel displays. The use of role-based access control ensures that users only have access to relevant data and events.
The provided text outlines a series of steps demonstrating how to use a hypothetical system called "Logger" for analyzing logs and generating reports. The Logger interface is designed with user-friendly features such as a simple Google-like search bar, customizable field sets, advanced operator options like Contains, Starts With, Ends With, =, !=, and graphical charting tools.
The process begins with performing an unstructured search using the term "dgchung" to find all instances of this term across different devices or vendors. The system then provides a summary view by vendor, showing the number of events related to dgchung and their respective percentages. This initial search can be adjusted within the Field Summary section or by switching field sets like Security, expanding on more detailed analysis.
For structured searches, users can define specific criteria such as server hostname containing "finance", using operators like Contains. The system then displays results color-coded in a block view, making it easier to interpret the data structure. Users have the flexibility to add multiple search conditions by chaining terms with OR or AND logic and even apply graphical visualizations tailored to their needs.
The Logger also includes an Advanced Search mode where users can craft complex queries using various operators and built-in functions like | (pipe), which helps in refining searches for specific events, such as FTP transactions linked to China. The interface offers a search helper feature that suggests available commands and provides graphical representations of the query results.
For data visualization and reporting, Logger supports multiple chart types including pie, column, bar, area, line, stacked column, and stacked bar charts. These visualizations can be customized according to user preferences regarding entry count or format changes. Additionally, users have options to export search results in various formats such as local save, direct export to Logger, PDF, CSV, etc.
Finally, the system allows for creating reports through a Dashboard feature that aggregates data from different modules like Compliance and Network Operations, providing a comprehensive overview of relevant activities filtered by specific criteria set by the user. This integrated reporting functionality is crucial for generating compliance dashboards or network operation insights tailored to meet regulatory requirements or operational needs.
The main A Reports Dashboard in SANS Top Logger menu displays customizable reports including IDS Alerts and a link to ArcSight. Users can create their own groups of reports called Favorites for easy access. Logger allows users to run ad-hoc reports or schedule automatic delivery, and export reports in various formats such as Adobe PDF, MS Word, MS Excel, and CSV. Compliance with regulatory standards like PCI is facilitated through customizable dashboards and compliance insight packages provided by ArcSight, which include preconfigured top reports tailored for specific compliance efforts.
The provided text discusses Logger, a system designed to analyze network data such as logs from devices like web servers and firewalls. It outlines two use cases: default account usage alert configuration for compliance purposes, and investigating a web server down incident in an IT operations context.
For the first use case, the text explains how alerts can be configured based on specific conditions to trigger notifications when certain events occur—in this case, related to PCI (Payment Card Industry) requirements for data storage. Alerts can have multiple destinations including email, SNMP, Syslog, and a correlation engine, which are configurable in Logger. The process involves logging in as an admin, navigating through the configuration menus to set up alerts that trigger based on specified conditions. It also covers how to configure storage groups for different types of logs with varying retention periods depending on the sensitivity or regulatory requirements (like PCI logs needing to be stored for at least one year).
The second use case focuses on addressing an IT operations issue where a web server is down, and unauthorized changes are suspected. The process begins by logging in as an admin, then using the search feature within Logger to analyze log data related to the web server—specifically searching for events like modifications or Denial of Service (DoS) attacks detected from North Korea. This involves categorizing events into understandable formats that can be used to build filters and rules for further analysis, which simplifies understanding complex logs even if you're not an expert in networking or firewalls.
Overall, the text demonstrates how Logger can be used by IT teams to efficiently monitor network data, detect issues, and respond quickly to maintain service quality and security.
The passage outlines several use cases and actions related to Logger software functionalities for monitoring events and analyzing system activities.
1. **Device Configuration Events Reporting**: Describes how to access and customize reports on device configuration events using a Logger menu. It includes steps to select specific configurations, filter criteria, and generate customized reports. The report can be automated or interactive based on user needs and preferences.
2. **Real-Time Event Monitoring**: Demonstrates the use of Live Event Viewer to monitor real-time events related to web server issues. This feature allows for focused reporting by setting search terms and filtering specific configurations, which is crucial for ongoing system monitoring during troubleshooting sessions.
3. **Multi Line Log Analysis**: Discusses Logger's ability to handle multi-line log files typical in application development environments. The process involves entering a keyword (e.g., RAA), selecting the appropriate field set, and filtering results based on specific events like 'ERROR'. This is useful for analyzing complex logs that need preservation of multiline messages as single events.
4. **NetFlow Use Case**: Focuses on using NetFlow data to track communication with Microsoft SQL Servers. The process involves setting up a search query ('netflow dpt=1433') and visualizing the results in real-time, highlighting sources that communicate with SQL servers over port 1433. This is particularly valuable for network administrators looking into server communications.
Each of these use cases showcases Logger's capabilities in handling diverse types of log data (from configuration events to application development logs) and performing targeted analysis, both via automated reporting and real-time event monitoring.
The text provided is a summary of various operations and functionalities within a network monitoring tool or system called "Logger." Here's a breakdown of what it covers:
1. **Network Flow Events Analysis**: The Logger software analyzes large portions of byte values, often reaching up to 62 bytes, which might be significant for network engineers. This analysis involves looking at events destined for SQL server ports (specifically port 1433) and visualizing the most popular source addresses using netflow data.
2. **Dynamic Charting in Logger**: The software allows users to dynamically change chart types such as pie charts, which can be adjusted based on user preferences and auto-refresh settings. Features include displaying percentages of events and numbers of occurrences when hovering over slices of the pie chart.
3. **Exporting Results**: Users have multiple options for exporting results including saving locally, to Logger, or in PDF or CSV formats. This is particularly useful for generating reports based on network data.
4. **Raw Event Analysis with Regex Helper**: The system supports parsing raw events using a regex helper tool that automatically extracts and names fields from the event content. This feature is especially useful for complex searches where standard field extraction methods are insufficient, such as when searching for failed logins by adding specific keywords like "loss nagios ALERT" into the search query.
5. **Utilizing Logger Regex Helper**: The regex helper allows users to extract meaningful data from raw events and assign names to parsed variables. For example, it can be used to identify fields like Round Trip Average (RTA) which is crucial for network latency analysis.
Overall, this text outlines the various ways in which a network monitoring tool named Logger can assist with detailed analysis of network traffic and event data using both structured and raw formats. It emphasizes its flexibility and user-friendly interface that allows quick adjustments to search parameters and visualizations based on immediate needs or ongoing investigations.
This summary outlines various use cases and functionalities of the Logger tool. It begins with finding keywords such as "login" and "failed attempt" in raw events, highlighting them for analysis. Logger's Discover Fields feature is introduced, which helps identify fields within RAW events automatically. The process involves using the GEAR icon to access Discover Fields, entering a search term (like "not cef login failed attempt"), clicking Go!, adjusting time windows if necessary, and then examining field summaries on the left side of the screen.
Another key function is the use of Logger's new Discover Fields feature for identifying fields in RAW events. This involves searching through raw logs to find patterns such as usernames, which are analyzed for counts, percentages, and sorting by username. A real-time chart showing top usernames related to "login" and "failed" is generated quickly with minimal effort.
A specific use case focuses on discovering and masking credit card numbers from raw events. This involves using Logger's Regex Helper to parse the data for relevant fields, which can then be masked or renamed as needed for reporting purposes. The tool automatically adds a column named ccnum to display this information across all events, allowing users to generate reports that obscure sensitive details while still providing necessary analytical data.
Lastly, an example of analyzing machine transactions demonstrates Logger's capabilities in handling higher-level event grouping and parsing without SmartConnectors or external integrations. This use case showcases how Logger can read log files directly using File Receivers, parse events on-board without additional connectors, and group these events into a TRANSACTION for easier analysis. The demo uses events from POSTFIX to illustrate this functionality.
This document outlines a demonstration of how to use the Logger VM for managing and analyzing Postfix mail transfer agent events. The process involves setting up a "Mail Logs" File Receiver, enabling it, waiting for the EPS In rate to stabilize, disabling it, and then viewing the retrieved events in the dashboard. Key points include:
1. **Setting Up the Mail Logs File Receiver**:
Navigate to Receivers > Receivers by typing RECE in the "Take me to..." field and clicking on "Here".
Click on "Enable" for the "Mail Logs" File Receiver, which will read events into the Logger. The EPS In rate should increase after a few seconds.
Once the rate drops back down from around 200, click "Disable" to turn off the receiver. Ensure it remains disabled.
2. **Viewing Events**:
The events are already read into the Logger and can be viewed in the dashboard by clicking on the Mail Logs receiver's name for details.
Configure Field Set to include fields like Time, hostname, process name, subprocessname, PID, and QueueID when expanding an event.
3. **Transaction Operation**:
The Transaction operation groups email events with the same QueueID into "transactions" or groups, assigning a transactionid and counting the number of events in each group.
This can be used to define business transactions across various events.
4. **Analyzing Events**:
Use the Mail Counts and Mail Transaction Lengths charts on the Dashboards > Mail section to analyze event counts and durations associated with QueueIDs.
Drill down into specific columns or details for further investigation using the Logger's drillable dashboards feature.
5. **Exporting Content**:
The Logger supports exporting and importing various content types such as Alerts, Dashboards, Filters, Parsers, Saved Searches, and Source Types, facilitating content development and sharing among users.
This guide provides a step-by-step method for utilizing the Logger VM to effectively manage and analyze Postfix mail events without requiring domain expertise in Postfix logs.
This text discusses the features and capabilities of ArcSight Logger, a tool designed to provide flexibility, control, and advanced search functionalities for security analysts. The article highlights several key aspects including on-board parsing, saved searches, drillable dashboards, dynamic data loading from external sources (such as updating Tor Exit Nodes), and scheduled updates for lookup tables.
One of the specific features mentioned is the ability to load and update lookup tables from external sources without direct control over the process, which can be facilitated by provided scripts. The article provides a detailed guide on how to manually update a lookup table used to correlate IP addresses with Tor Exit Nodes using a demo script available for Logger's demo VM. This demonstration includes adding a specific magic IP address to simulate data retrieval and formatting.
Additionally, the text discusses the use of Logger within larger security operations, such as conducting URL analysis where operators can utilize the 'len(somefield)' function to assess the length of URLs. This feature helps in identifying potential indicators of malware or compromise by analyzing the size of these fields across a network's traffic data.
The article concludes with practical advice on how to implement and use Logger effectively, emphasizing its role in facilitating quick lookups and detailed analysis within an organization’s security infrastructure. It underscores that even without direct support for certain functions, such as updating lookup tables, the tool can be highly effective when used alongside provided scripts or through manual data entry following a clear guide.
The document provides a guide on how to perform various searches and analyses in Logger, an application used for event management in networks using VLSM (variable-length subnet mask). Here's a summary of the key points:
1. **Searching within Subnets**: To search for events within specific subnets, use the "insubnet" operator. For example, searching with `sourceAddress insubnet "10.0.0.0/18"` will find all activities within that subnet. Adjusting the prefix length (e.g., to "/21") changes the scope of the search and reveals different networks.
2. **Using Wildcard Expressions**: You can specify wildcard expressions like `sourceAddress insubnet "10.0.*.*"` to search for addresses with unspecified right-hand side bits, allowing broader or more specific searches based on available information.
3. **Address Ranges**: Specifying address ranges (e.g., "10.0.0.0-10.10.0.0") allows searching within a defined range of IP addresses. This can be useful for auditing and monitoring purposes across multiple subnets or networks.
4. **Interpreting Search Results**: When specific events are identified, such as the IP address "10.0.27.221", details like deviceProduct can help identify the type of network devices involved (e.g., Fortigate). Further investigation into these networks is encouraged by examining individual charts and refining search queries further.
5. **Refining Search Queries**: Advanced searches can be performed using logical operators, such as AND, to narrow down results based on multiple criteria. For instance, `sourceAddress insubnet "10.0.0.0-10.10.0.0" AND deviceProduct CONTAINS "IntruShield" AND categorySignificance CONTAINS "/Compromise"` can be used to find compromised events from specific devices or categories.
6. **URL Decoding**: The document explains how to decode URLs that are encoded using percent-encoding (e.g., "%20"). This is done through the Logger interface by entering `name="Accessed URL" | eval decodedurl=urldecode(requestUrl)`, which converts encoded strings back into readable text form for easier interpretation.
7. **Dashboard View**: A dashboard showing 15 panels at once allows quick overviews of top values from various fields, as demonstrated by the "Top Values" dashboard in Logger's demo environment. This feature provides a consolidated view of key performance indicators and trends across multiple tables and metrics.
8. **FortiGate Integration**: The partnership between Micro Focus (now part of Broadcom) and Fortinet is highlighted with specific instructions on how to search for events from FortiGate devices, helping in the analysis of security threats within enterprise networks.
Overall, this document provides practical steps and examples to effectively utilize Logger's features for VLSM network management, including advanced querying techniques tailored for complex networking environments where variable-length subnet masks are employed.
The provided text discusses the use of Smart Reports in a Logger interface for dynamic analysis. It outlines steps for generating and running searches, creating reports, and utilizing visualizations such as bar charts, grids, and Sparklines to analyze data effectively. Here's a summarized version of the key points:
1. **Setting Up Data Analysis**: The user is required to select relevant fields like deviceVendor and deviceAction from a fieldset for specific analysis. In this case, they focus on Fortinet devices where actions such as Blocked indicated potential virus-infected files were blocked by the firewall.
2. **Running Searches**: Using filters like deviceVendor = "Fortinet" and deviceAction="blocked", users can run searches to identify issues (e.g., virus infections). The results show a field named 'name' that identifies specific virus-related blocks in files.
3. **Visualizing Data**: The user accesses FortiGate dashboard to view top actions performed by the firewall, which helps in understanding performance and potential threats. They can drill down further into individual device actions for more detailed analysis.
4. **Creating Smart Reports**: Users generate reports based on saved filters or specific queries. For instance, a search was conducted using "Demo User Logins" filter to analyze authentication attempts over the last 24 hours. The report is then modified to include enhanced features like value-based coloring and Sparklines for better data visualization and analysis capabilities.
5. **Utilizing Visualizations**: Reports are visualized in various ways such as bar charts, grids with dynamic tables of results, and sorting/filtering options (e.g., filtering by 'root' dynamically adjusts the displayed outcomes). Tools like Tree Map and Packed Circles help graphically represent event volumes across different device types.
6. **Interactivity**: The interface allows for interactivity where users can adjust settings on-the-fly, such as changing filters or visual elements in reports to better suit their analytical needs.
7. **Enhanced Reporting**: Reports are not only about displaying data but also about enhancing user experience through interactive and visually appealing formats that facilitate deeper insights into the analyzed data.
This summary captures the essence of how Smart Reports can be used for both basic exploratory analysis and advanced, interactive visualizations in a Logger interface, tailored to specific needs like cybersecurity analytics.
This text is a tutorial on how to use Logger Smart Reporting with Voltage SecureData for seamless inline decryption of events. It begins by explaining how to enable 'Edit Mode' in the upper right corner, then adding visualizations using the plus sign. The demonstration focuses on secure data integration between Voltage and ArcSight through Smart Connectors, which can transparently encrypt configured event fields and send them to any destination. Once enabled, Logger can decrypt sensitive values directly by talking natively to a Voltage server. This process involves entering specific search queries in the Logger interface for decryption. The text also provides tips on configuring secure data settings and handling pre-encrypted field values for easier demonstrations. Appendix A of the document outlines revisions made throughout different versions of Logger, from version 2.0 onwards, including updates related to Smart Reports, incorporating Secure Data Format-Preserving Encryption (FPE), and other enhancements in the context of compliance and protection of sensitive information.
This information is about a company called International plc. It was registered in England and Wales with the number 5134647. Its address where it's officially working from is The Lawn, 22-30 Old Bath Road, Berkshire, RG14 1Q.
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