Feel locked-in with your SIEM?
How do you integrate your data sources with data destinations such as SIEM platforms, XDRs, and Datalakes?
Whether you are new in security or a lifer, chances are you’ve heard the industry discussions relating to log management strategies, collection, routing, storage and integrating data sources with SIEMs and accompanying costs associated with that effort. It’s fundamental that companies must ensure high data quality as they collect and manage security data. Challenges arise because data comes from potentially hundreds of unique sources with differing formats, structures and of course tremendous volumes of useless logs tangled with relevant data. These attributes require cleansing, complex mapping, normalizing or other processes to ensure accuracy and consistency while making sure all stakeholders are happy with how the data is being handled and how the organization is being protected.
And even if you figure all of that out, you’re left with having to work individually with each of the logging platforms because of their differing architectures, data mapping approaches and analytics.
What’s in the way?
Direct integration of your data sources with SIEMs results in noisy data and a heavy onboarding or migration effort. Problems that arise can include:
- Cloud visibility – Most logging platforms don’t support all the complex cloud sources you need ingestion from, either because of cost or supportability. This leads to blind gaps in data consolidation.
- Paying ingestion costs on data that is not useful.
Not all data from your data sources is useful for threat detection. Some events are internal service updates, some logs have extraneous fields, and some have additional info that is irrelevant. When you don’t have the right method to filter out the unnecessary data, you end up storing it in a high-cost data destination causing both your data volumes and costs to increase.
- Noisy data blinding your SecOps.
State of SecOps and Automation report states that “99% of organizations report high volumes of alerts cause problems for security teams in identifying real threats buried in the noise”. Having noisy data filling your SIEM / datalake platforms isn’t just a cost problem, it's a fundamental security problem. Noise from 90% of irrelevant data takes away focus from the 10% data that matters.
- Compromising on visibility
All data must be accounted for, to have full visibility, right? But when the data is not filtered or normalized before being routed to destinations, what compromises are you making? How do you decide which data sources need to be onboarded, and which ones are of lesser value or can wait until later to avoid blurry data? Having a lot of data but not filtering it correctly can actually impact visibility negatively. If that’s the case, then the organization will be unable to see real threats through all of the noise.
- Vendor Lock-In and SIEM migration complexity
Every SIEM / XDR / datastore platform is different. Each vendor may have its own data structure and querying language. Once you’ve onboarded a data source with a particular SIEM vendor, several factors come into play before you can make a switch to a new one, like integration complexity, data volume that needs to be re-routed, analytic policies migration and the operational burden on the team to make the transition. This creates vendor lock-in for an already saturated security team trying to defend the organization against real threats.
So how do you solve the potential problems that might arise from integrating data directly with your SIEMs and other platforms? What if there was a “helper” or a translation layer in between your data sources and data destinations that can take the heavy lifting of data operations off your internal team’s plate by decoupling the sources from destinations?
Introducing Abstract Security’s Data Pipeline Management
A data pipeline management tool helps decouple the data sources from data destinations and adds the ability to operate on the data before it reaches a destination. This removes individual onboarding dependency, and the prebuilt source and destination integrations make data easily routable to any destination.
Abstract’s pipelines feature goes beyond a generic data pipeline management tool with its data and threat expertise. The main difference lies in Abstract’s strong security focus. There are a lot of DPM tools that can be the “helper” to route your data from one platform to another, however, not all tools are built with security in mind. Abstract Security has the data and threat expertise that enables it to distinguish between legit threat data and noise, to mask sensitive data before routing, to apply threat enrichments with live streaming intelligence, and most importantly to recognize what data should not be dropped (under noise reduction).
With Abstract’s “no-code required” model, you can easily perform all these operations without having to hire a dedicated, certified professional to work with the platform. With Abstract Security’s pipeline features, you get
- Streamlined Quality Data: Abstract collects, reduces, enriches and routes data from various cloud sources such as AWS CloudTrail, Azure Activity Logs, and GCP logs. Abstract’s out-of-the-box rules filter out low-value data (e.g., debugging logs or redundant telemetry) before sending it to high-cost SIEM platforms, improving the quality of data ingested at destinations. In addition, Abstract’s data aggregation features further reduce data sizes by 40-50%.
- Normalization and Enrichment: Cloud logs can be enriched with contextual information (e.g., geolocation, IAM role mappings) before reaching the SIEM, improving the relevance of security alerts for cloud environments. Abstract’s Intel Gallery consists of in-house threat feed (ASTRO feed) that is constantly updated and an option and the ability to bring your own threat intelligence feed into a single platform to apply enrichments.
- Dynamic and Context-Aware Routing: Abstract allows for dynamic routing of logs to multiple destinations, enabling the organization to split the stream based on predefined analytic use cases or specific security scenarios. This approach supports cloud use cases, ensuring holistic visibility. Abstract’s ability to send data to multiple SIEMs and cloud monitoring tools ensures that the right data reaches the right platform, whether for compliance, security operations, or cloud monitoring.
- Simplified SIEM Transitions: Abstract’s architecture decouples data sources from specific SIEM platforms, enabling the organization to seamlessly replace SIEMs without significant re-architecting. By allowing simultaneous data flow to multiple destinations, Abstract can facilitate easy transitions to new SIEMs or cloud monitoring tools during migration periods, reducing integration costs and minimizing operational disruptions.
With Abstract’s pipelines feature, you can remove the complexity from data operations and make the most out of your SIEM investments without getting locked-in.
Leave the data operations to Abstract so your teams can focus on stopping the adversaries who threaten our collective livelihood.