OSSIM leverages the power of the AlienVault Open Threat Exchange by allowing users to both contribute and receive real-time information about malicious hosts. AlienVault OSSIM is an open source Security Information and Event Management (SIEM) product. It is a unified platform providing: Asset discovery Vulnerability assessment Intrusion detection Behavioral monitoring SIEM OSSIM provides the basis for AlienVault's proprietary Unified Security…
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Logstash
Score 8.0 out of 10
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Pricing
AlienVault OSSIM
Logstash
Editions & Modules
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AlienVault OSSIM
Logstash
Free Trial
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No
Free/Freemium Version
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No
Premium Consulting/Integration Services
No
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Entry-level Setup Fee
No setup fee
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Community Pulse
AlienVault OSSIM
Logstash
Features
AlienVault OSSIM
Logstash
Security Information and Event Management (SIEM)
Comparison of Security Information and Event Management (SIEM) features of Product A and Product B
AlienVault OSSIM
7.5
10 Ratings
4% below category average
Logstash
-
Ratings
Centralized event and log data collection
9.49 Ratings
00 Ratings
Correlation
6.910 Ratings
00 Ratings
Event and log normalization/management
8.110 Ratings
00 Ratings
Deployment flexibility
8.210 Ratings
00 Ratings
Integration with Identity and Access Management Tools
If this is your first experience with a SIEM, this one can get you started. Take the time to learn the ins and outs of the product and you'll most likely be satisfied with it if your company is an SMB. If you need compliance reports, OSSIM is too small for you, you'll need to go with USM or USM Anywhere.
Perfect for projects where Elasticsearch makes sense: if you decide to employ ES in a project, then you will almost inevitably use LogStash, and you should anyways. Such projects would include: 1. Data Science (reading, recording or measure web-based Analytics, Metrics) 2. Web Scraping (which was one of our earlier projects involving LogStash) 3. Syslog-ng Management: While I did point out that it can be a bit of an electric boo-ga-loo in finding an errant configuration item, it is still worth it to implement Syslog-ng management via LogStash: being able to fine-tune your log messages and then pipe them to other sources, depending on the data being read in, is incredibly powerful, and I would say is exemplar of what modern Computer Science looks like: Less Specialization in mathematics, and more specialization in storing and recording data (i.e. Less Engineering, and more Design).
Asset discovery. Once installed in a centric, network-accessible server, OSSIM can poll all your endpoints with common protocols (SSH, SNMP, WMI) to detect and discover site-wide assets to monitor. You only need to group them by your own criteria once added to the product.
SIEM Event Correlation. You can define quite complex correlation rules to detect possible suspicious or malicious actions or attempts in your network, in order to categorize them as real threats or as false positives, thus streamlining your risk assessment and management.
Ease of installation. The entire AlienVault OSSIM is self-contained in an ISO file, which can be burned into a DVD or just mounted in your server of choice (physical or virtual) for deployment. The installation process is automated and quote verbosed, with options for static IP, email messaging and others.
Ease of access. Being AlienVault OSSIM a self-contained appliance, it can be accessed via web by any device that supports a web browser, being that desktops, workstation, mobile devices, etc. The OSSIM dashboard and other features are automatically rearranged to adapt to the particular device being in use.
Logstash design is definitely perfect for the use case of ELK. Logstash has "drivers" using which it can inject from virtually any source. This takes the headache from source to implement those "drivers" to store data to ES.
Logstash is fast, very fast. As per my observance, you don't need more than 1 or 2 servers for even big size projects.
Data in different shape, size, and formats? No worries, Logstash can handle it. It lets you write simple rules to programmatically take decisions real-time on data.
You can change your data on the fly! This is the CORE power of Logstash. The concept is similar to Kafka streams, the difference being the source and destination are application and ES respectively.
Since it's a Java product, JVM tuning must be done for handling high-load.
The persistent queue feature is nice, but I feel like most companies would want to use Kafka as a general storage location for persistent messages for all consumers to use. Using some pipeline of "Kafka input -> filter plugins -> Kafka output" seems like a good solution for data enrichment without needing to maintain a custom Kafka consumer to accomplish a similar feature.
I would like to see more documentation around creating a distributed Logstash cluster because I imagine for high ingestion use cases, that would be necessary.
AlienVault OSSIM is far easy to use and manage - provided you know what you're doing. As any SIEM application, there is some background knowledge required in order to take advantage of the product's functionalities, such as the log correlation and analysis. Other than that, the application is quite usable and robust.
Everything is done through MSSP and installation pro services. Once those hours are burned up, then you're on your own without a lot of help. Typically the pro services hours aren't enough to get past 60 days and MSSP are hit and miss. We had a miss for installation helpers.
Originally my organization leveraged alien value due to the lower cost of entry and ability to manage it as a service provider. Unfortunately, after several years of working with this tool, it became unwieldy to use as it felt that almost every useful report had to be created by hand. As other tools have come out with the ability to do automated responses such as Stellar Data processor, we have begun to evaluate alternatives.
MongoDB and Azure SQL Database are just that: Databases, and they allow you to pipe data into a database, which means that alot of the log filtering becomes a simple exercise of querying information from a DBMS. However, LogStash was chosen for it's ease of integration into our choice of using ELK Elasticsearch is an obvious inclusion: Using Logstash with it's native DevOps stack its really rational
Positive: Learning curve was relatively easy for our team. We were up and running within a sprint.
Positive: Managing Logstash has generally been easy. We configure it, and usually, don't have to worry about misbehavior.
Negative: Updating/Rehydrating Logstash servers have been little challenging. We sometimes even loose data while Logstash is down. It requires more in-depth research and experiments to figure the fine-grained details.
Negative: This is now one more application/skill/server to manage. Like any other servers, it requires proper grooming or else you will get in trouble. This is also a single point of failure which can have the ability to make other servers useless if it is not running.