Having a bit of an issue here with configuration and I hoping someone can kick me in the right direction Screen Shot at 2. I assume at this stage that this is where the "var. However, when I try and fire up Filebeat with this variable change in place Filebeat bombs right away and I get the attached error:. If anyone has a tip they could pass along or has perhaps encountered the same thing I'd sure appreciate some feedback on this!
It immediately starting throwing a bunch of JSON related errors immediately. In the meantime if someone else has some other feed back to share I would be most grateful.
Thank you! I can definitely confirm that all the logs are definitely in JSON format and the var. Oh well I am wondering if there is some possible incompatibilities between Filebeat 7. I pulled the source for Zeek from their GitHub as of July 21st, Screen Shot at 8. Screen Shot at 9. I'm asking because I appear to have the same problem. I'm trying to load bro log files into elasticsearch via filebeat and its zeek module. The same error messages show up and the bro files are not loading into elasticsearch.
The system software is only slightly different: Centos 7. I ended up kinda "giving up" in a way Ever since I did that its worked like a charm FWIW, an hour or two after I posted, elasticsearch starting loading bro data.
Zeek Package: IRC Feature Extractor
Unfortunately, I'm not sure why. I did a couple things awhile before it started working including upgrading to Elastic 7. I'd be happier if I'd seen a more clear cut reason for the fix or more helpful error message, but at least it's working. I think the big difference with your config file was wrapping the path names in [""] I don't think I did that My setup is working and cranking away as we speak so I don't think I'll mess with it at this stage but great to know you got it working!
This topic was automatically closed 28 days after the last reply.Zeek/Bro Logs 101: Zeek/Bro's SSL Log
New replies are no longer allowed. Using Filebeat with Zeek issue with configuration Beats. Good afternoon everyone! I think var. Hope this helps! Hi Michael, Did you ever find a solution to your issue? Good Morning and my apologies for taking a bit to get back to you Thanks for the response!The goal for the feature extraction is to describe an individual IRC communications that occur in the pcap file as accurately as possible.
The package was created during our research in the Aposemat project, a joint project between Avast and CVUT, where we proposed a technique for detecting malicious IRC communications in the network. The log will look like this:. Every line consists of a line descriptor followed by a content described by the descriptor.
Lines describes predefined values that determine the structure of the log. Line 6 indicates the time when the package starts evaluation and Line 10 when the package ends the evaluation.
Line 7 contains extracted feature names, line 8 contains data types of each feature, and line 9 contains feature values. Once the data was obtained from network traffic capture, there was a process to extract the features. We separated the whole pcap into IRC connections for each individual user.
The source port is neglected in separation to include multiple TCP connections in a single IRC connection - when a new TCP connection is established between two IP addresses, the source port is randomly chosen from the unregistered port range, and that is why the source port differs in multiple TCP connections.
This is shown in Figure 1, where there are two connections from the source IP address Figure 1. Source port is neglected, and therefore one IRC connection can have multiple source ports. The IP addresses and ports are chosen randomly for demonstration purposes. Here, we will describe the complete list of features that are extracted by the package for each IRC Connection that we obtained from a pcap file.
The features were manually chosen to provide us a meaningful representation of the IRC connection biased towards the malware detection we were trying to solve. Size of total amount of all packets in bytes that were sent in IRC connection.
It reflects how many messages were sent and how long they were. Time duration of IRC connection in milliseconds - i. As we have mentioned before, the source port is neglected in unifying communication into IRC connections because it is randomly chosen when a TCP connection is established.
We suppose that artificial users could use a higher number of source ports than the real users since the number of connections of the artificial users was higher than the number of connections of the real users.Zeek can be used to log the entire HTTP traffic from your network to the http.
This file can then be used for analysis and auditing purposes. In the sections below we briefly explain the structure of the http. Some of these ideas and techniques can later be applied to monitor different protocols in a similar way. The http.
Here are the first few columns of http. The UID can be used to identify all logged activity possibly across multiple log files associated with a given connection 4-tuple over its lifetime. For example, the columns on the line below shortened for brevity show a request to the root of Zeek website:.
Network administrators and security engineers, for instance, can use the information in this log to understand the HTTP activity on the network and troubleshoot network problems or search for anomalous activities.
We must stress that there is no single right way to perform an analysis. It will depend on the expertise of the person performing the analysis and the specific details of the task.
Working with Bro Logs: Queries By Example
For more information about how to handle the HTTP protocol in Zeek, including a complete list of the fields available in http. A proxy server is a device on your network configured to request a service on behalf of a third system; one of the most common examples is a Web proxy server.
A client without Internet access connects to the proxy and requests a web page, the proxy sends the request to the web server, which receives the response, and passes it to the original client.
Proxies were conceived to help manage a network and provide better encapsulation. So we can use this to identify a proxy server. In reality, the HTTP protocol defines several success status codes other thanso we will extend our basic script to also consider the additional codes. Finally, our goal should be to generate an alert when a proxy has been detected instead of printing a message on the console output.
Once a notification has been fired, we will further suppress it for one day. Below is the complete script.Download Cloud Signup. Humio is an excellent tool for analyzing Zeek data. This document describes how to get Zeek data into Humio.
That will make it easier to send them to Humio. By default each JSON log file is rotated every 15 minutes, and four versions of the file are kept. These files will be monitored by Filebeat and data send to Humio as is described below in the section Configure Filebeat.
You can follow the above or add the Zeek script in a way matching your installation. We assume you already have a local Humio running or is using Humio as a Service. Head over to the installation docs for instructions on how to install Humio. We will use Filebeat to ship Zeek logs to Humio. Filebeat is a light weight, open source agent that can monitor log files and send data to servers like Humio.
Filebeat must be installed on the server having the Zeek logs. Follow the instructions here to download and install Filebeat. Then return here to configure Filebeat. You can replace the parameters in the file or set them as ENV parameters when starting Filebeat.
You can create an ingest token following the instructions here. Note that in the filebeat configuration we specify that Humio should use the built-in parser bro-json to parse the data with:. Experiment with increasing this if filebeat cannot keep up with sending data.
Run Filebeat as described here. An example of running Filebeat with the above parameters as environment variables:. Logging is verbose Logging is set to debug in the above Filebeat configuration. It can be a good idea to set it to info when things are running well. Filebeat log files are by default rotated and only 7 files of 10 megabytes each are kept, so it should not fill up the disk.
Examining aspects of encrypted traffic through Zeek logs
For these examples, a combination of file globbing, regular expressions, counting, sorting, basic arithmetic, and pattern matching will be used to examine log data. Logs that have been rotated are in folders named with the date and are compressed in the gzip format.
You will need to either decompress the logs first or use tools that do on the fly decompression e. Bro logs begin with a 8 line header that describes the log format.
For parsing fields we should be concerned with line 7. Each field is described in the Bro documentation [ 2 ][ 3 ]. Below is a sample of conn.
Notice how the field names listed in the header correspond to the values listed in the log data. Now look at the responder field which is field 6, it contains an IP address too. Familiarize yourself with some of the common fields: ts, id. To avoid printing the header each time the first 8 lines can be skipped. I show three ways of doing this below. This is specified in the log format header block as a hex value. Continuing with the Notice message example, without specifying the tab separator you would only print the first word in the message rather than the entire message.
Bro-cut is a C program which allows one to avoid counting fields and instead print fields by their name. It can perform timestamp conversion from unix epoch time to the human readable local time format. Bro-cut also strips off the header by default. It should be noted, as we shall see later, that bro-cut needs to see the log header to operate on the log data.
Note: Bro-cut used to be a shell script wrapper for a large gawk program and as a consequence was very slow. In the following examples we will print the id. Notice how awk prints the 6th field from the header too; it reads line by line. Because bro-cut strips off the header, the output with and without, will differ by a few lines depending on which field is printed with awk.
Printing the id. Also, note that field counting becomes more inconvenient as the field number moves farther from 1. Thus, the use of bro-cut. Passing the -c option to bro-cut will cause it to print, rather than omit, the format header block. Print and convert the timestamp field to local time from the first and last connection in the connection log file. This gives us the date and time range for the log as all other entries occur between these two points.
A few examples of matching a single IP address will follow using the id. We also escape the period with backslashes so they loose there special regular expression meaning by default, they match any single character. Using GNU zgrep, like you would find on Linux, we could use character classes instead to represent any type of whitespace, not just tabs. Print a list of all the unique removal of duplicates services detected by Bro.Once Zeek has been deployed in an environment and monitoring live traffic, it will, in its default configuration, begin to produce human-readable ASCII logs.
As the standard log files are simple ASCII data, working with the data contained in them can be done from a command line terminal once you have been familiarized with the types of data that can be found in each file. In the following, we work through the logs general structure and then examine some standard ways of working with them. However, as each log file flows through the Logging Framework, they share a set of structural similarities.
The author then decides what network activity should generate a single log file entry i. When these behaviors are observed during operation, the data is passed to the Logging Framework which adds the entry to the appropriate log file. As the fields of the log entries can be further customized by the user, the Logging Framework makes use of a header block to ensure that it remains self-describing. As you can see, the header consists of lines prefixed by and includes information such as what separators are being used for various types of data, what an empty field looks like and what an unset field looks like.
The timestamp for when the file was created is included under open. The header then goes on to detail the fields being listed in the file and the data types of those fields, in fields and typesrespectively. These two entries are often the two most significant points of interest as they detail not only the field names but the data types used. When navigating through the different log files with tools like sedawkor grephaving the field definitions readily available saves the user some mental leg work.
The field names are also a key resource for using the zeek-cut utility included with Zeek, see below. Next to the header follows the main content. See Conn::Info for a description of all fields. In addition to conn. As you can see, some log files are specific to a particular protocol, while others aggregate information across different types of activity.
For a complete list of log files and a description of its purpose, see Log Files. The zeek-cut utility can be used in place of other tools to build terminal commands that remain flexible and accurate independent of possible changes to the log file itself.
It accomplishes this by parsing the header in each file and allowing the user to refer to the specific columnar data available in contrast to tools like awk that require the user to refer to fields referenced by their position.
For example, the following command extracts just the given columns from a conn. The corresponding awk command will look like this:. Firstly, the zeek-cut output includes only the log file entries, while the awk solution needs to skip the header manually. Secondly, since zeek-cut uses the field descriptors to identify and extract data, it allows for flexibility independent of the format and contents of the log file.
In this case, the fields in the awk command would have to be altered to compensate for the new position whereas the zeek-cut output would not change. The sequence of field names given to zeek-cut determines the output order, which means you can also use zeek-cut to reorder fields. That can be helpful when piping into, e.Zeek comes with a flexible key-value based logging interface that allows fine-grained control of what gets logged and how it is logged.
This document describes how logging can be customized and extended. All of these approaches are described in this document. Without this attribute, a field will not appear in the log output. This indicates that the field might not be assigned any value before the log record is written.
At this point, the only thing missing is a call to the Log::write function to send data to the logging framework. The actual event handler where this should take place will depend on where your data becomes available. If you run Zeek with this script, a new log file foo. Note that the way that such fields are named in the log output differs slightly from the way we would refer to the same field in a Zeek script each dollar sign is replaced with a period.
When you are developing scripts that add data to the connection record, care must be given to when and how long data is stored. You can add additional fields to a log by extending the record type that defines its content, and setting a value for the new fields before each log record is written.
Now we need to set the field.
Although the details vary depending on which log is being extended, in general it is important to choose a suitable event in which to set the additional fields because we need to make sure that the fields are set before the log record is written. Sometimes the right choice is the same event which writes the log record, but at a higher priority in order to ensure that the event handler that sets the additional fields is executed before the event handler that writes the log record.
Now conn. For extending logs this way, one needs a bit of knowledge about how the script that creates the log stream is organizing its state keeping. Sometimes it is helpful to do additional analysis of the information being logged. For these cases, a stream can specify an event that will be generated every time a log record is written to it.
To do this, we need to modify the example module shown above to look something like this:. You could use that for example for flagging when a connection to a specific destination exceeds a certain duration:. Often, these events can be an alternative to post-processing Zeek logs externally with Perl scripts.
Much of what such an external script would do later offline, one may instead do directly inside of Zeek in real-time. For example, the following example will prevent the conn. Note that this must run after the stream is created, so the priority of this event handler must be lower than the priority of the event handler where the stream was created.