While technology plays a crucial role, we firmly believe that successful cybersecurity requires a comprehensive approach. We offer our clients more than just data engineering expertise:
Security process optimization: We don’t simply implement technology; we assess and optimize existing security processes. This involves identifying and eliminating redundancies, streamlining workflows, and ensuring alignment with data-driven insights for improved efficiency.
Empowering through training: We invest in user education and awareness programs to create a human firewall. By equipping employees with the knowledge and skills to identify and report suspicious activity, we bolster the overall security posture.
Staying ahead of threats: We provide access to real-time threat intelligence feeds, keeping organizations informed about the latest threats, vulnerabilities, and attacker tactics. This enables proactive security measures and informed decision-making.
We recognize that cybersecurity solutions can be costly, and organizations are increasingly focused on maximizing the return on their security investments. HOOP Cyber prioritizes cost optimization alongside security effectiveness by:
Standardization and automation: We advocate for the standardization of security architectures and the automation of repetitive tasks. This streamlines operations, reduces manual effort, and ultimately translates to cost savings.
Cloud-based security solutions: We leverage the inherent scalability and cost benefits of cloud-based security solutions. This reduces upfront capital expenditures and allows organizations to pay only for the resources they use.
Open-source integration: Where applicable, we integrate open-source security tools alongside commercial solutions. This provides organizations with comparable functionality at a lower cost, allowing them to stretch their security budget further.
SIEM (Security Information and Event Management) deployment is a critical component in modern cybersecurity strategies, enabling organizations to detect, analyze, and respond to security threats in real time. The deployment process begins with thorough planning and preparation, which involves defining the specific security objectives and requirements, assessing the current IT infrastructure, and selecting the appropriate SIEM solution that aligns with the organization’s needs. This stage also includes configuring data sources such as network devices, servers, applications, and security tools to ensure they generate relevant logs and event data that the SIEM system can collect and analyze. Properly setting up these data inputs is crucial for the SIEM to provide comprehensive visibility into the organization’s security posture.
Once the SIEM solution is selected and data sources are configured, the actual deployment involves integrating the SIEM system into the existing IT environment. This includes installing the SIEM software, configuring network settings, and setting up user roles and permissions. After the installation, the SIEM system undergoes a tuning process to filter out false positives and refine alert thresholds to ensure the alerts generated are relevant and actionable. Continuous monitoring and regular updates are essential to maintain the effectiveness of the SIEM deployment. Additionally, staff training is vital to ensure that security personnel can effectively utilize the SIEM tools to investigate incidents and respond to threats. By successfully deploying a SIEM system, organizations can significantly enhance their ability to monitor, detect, and respond to security incidents, thereby improving their overall security posture.
SIEM (Security Information and Event Management) optimization is a continuous process aimed at enhancing the performance, accuracy, and efficiency of SIEM systems to ensure they provide actionable insights and timely threat detection. This process begins with refining data collection to ensure that only relevant and high-quality logs are ingested, reducing noise and the likelihood of false positives. It involves regular tuning of correlation rules and use cases to reflect the latest threat intelligence and organizational changes. By updating these rules, the SIEM system can more accurately detect potential threats and reduce the burden of analyzing false alarms. Additionally, optimizing the parsing and normalization of log data ensures that the SIEM system can efficiently process and correlate information from diverse sources.
Beyond technical adjustments, SIEM optimization also focuses on improving the workflows and response strategies of the security operations center (SOC). This includes integrating automated response capabilities to streamline incident handling and reduce response times. Regularly reviewing and updating incident response plans based on insights gained from previous incidents helps in refining the overall security posture. Enhancing the skills and knowledge of SOC analysts through continuous training and simulation exercises ensures that they can effectively interpret SIEM alerts and take appropriate actions. By combining technical enhancements with procedural improvements, SIEM optimization enables organizations to maximize the value of their SIEM investments, ensuring robust, proactive security monitoring and swift incident response.
Data source mapping is a crucial process in the implementation and optimization of security systems, including SIEM (Security Information and Event Management) solutions. This process involves identifying, categorizing, and documenting all the data sources within an organization that generate logs and security-relevant information. These data sources can include network devices, servers, applications, databases, and endpoint devices. Effective data source mapping ensures that all relevant data is captured and fed into the SIEM system, providing a comprehensive view of the organization’s security landscape. By systematically mapping data sources, organizations can ensure that their SIEM systems receive the necessary input to detect and correlate security events accurately.
The benefits of thorough data source mapping extend beyond initial setup to ongoing security operations. Accurate mapping helps in the identification of gaps in log collection, ensuring that critical data is not overlooked. It also aids in the efficient tuning and filtering of data, which is essential for minimizing false positives and enhancing the relevance of alerts generated by the SIEM system. Furthermore, well-documented data source mappings facilitate easier maintenance and updates, as security teams can quickly reference and modify data source configurations as the IT environment evolves. Ultimately, data source mapping is foundational to building a resilient and effective security monitoring infrastructure, enabling better threat detection, faster incident response, and improved overall security posture.
SecOps architecture modernization is essential in today’s cyber security landscape, where traditional approaches are no longer sufficient to handle the complexity of modern IT environments. As organisations move towards cloud-native infrastructure, the need for scalable and dynamic security measures has increased. A key aspect of modernisation involves shifting from perimeter-based defenses to a Zero Trust architecture, which assumes that no user or device should be trusted by default, even within the internal network. Cloud-native tools such as Cloud Security Posture Management (CSPM) and Cloud Workload Protection Platforms (CWPP) are used to secure resources in distributed environments, ensuring that applications, data, and workloads are continuously monitored for vulnerabilities.
Automation is a cornerstone of modern SecOps architecture. Security Orchestration, Automation, and Response (SOAR) platforms allow organizations to streamline their security operations by automating repetitive tasks such as threat detection, incident response, and log analysis. The integration of AI and machine learning in SecOps enables faster threat identification and more precise responses to cyber incidents. This approach reduces the workload on security teams and ensures that even large volumes of data and alerts are processed efficiently. Automation enhances agility and allows organizations to keep up with the rapidly evolving threat landscape.
Another critical element in SecOps modernization is the incorporation of DevSecOps, which integrates security into the software development lifecycle. By embedding security practices early in the development process, vulnerabilities can be identified and mitigated before code reaches production. Shift-left security ensures that application security testing, compliance checks, and code reviews happen continuously within the CI/CD pipeline. This proactive approach reduces the risk of introducing security flaws during deployment, resulting in more secure software and infrastructure.
Modern SecOps architectures emphasize enhanced threat intelligence and observability. Advanced analytics tools and platforms like Extended Detection and Response (XDR) consolidate data from across the enterprise, offering comprehensive insights into potential threats and anomalies. This heightened visibility is crucial for identifying malicious activities across various layers, including endpoints, networks, and cloud environments. As a result, organizations can move from a reactive to a proactive security posture, improving their ability to detect, investigate, and mitigate sophisticated cyberattacks in real-time.
Introducing HOOP-Jam for Security Lake switch-on, the first step of your security lake journey.
In this Workshop HOOP experts will help set-up and advise on key data sources to your Security Lake (Both Native AWS and OCSF). They will provide guidance on how to integrate to your current SEC-OPS environment and Subscriber Services.
What can I expect?
Through this workshop you will be able to increase your security data coverage with AWS Security Lake with our FastStart HOOP-Jam.
Our expert engineers and architects will help you onboard your AWS data sources into AWS Security Lake.
Security Lake helps you take control of your security data, so you can get a more complete understanding of your security posture across the entire organisation.
With Security Lake, you can:
Improve the protection of your workloads, applications, and data.
Take advantage of Open Cyber Security Schema Format (OCSF) by normalising your security data sources.
This FastStart includes:
A data source assessment.
Prioritisation.
Onboarding of data sources.
Customer data querying with existing tools and integrations offered through AWS Security Lake.
Key Benefits
Data Source Assessment
Understand the monitoring needs of the customer and prioritise the right data sources to be onboarded in Security Lake.
Data Source Onboarding
Expert engineers will guide customers through the onboarding process and explain how to query and options of accessing the data through external integrations.
Experienced Deployment Specialists
By teaming with us on a project, the customer taps into a deep and wide-ranging skills network to help align business goals to realised cloud initiative.
Expert Led Onboarding of Security Lake
Advice covering all data sources and Subscriber requirements.
At HOOP Cyber we believe that Cyber Security is fundamentally a Data Problem. The HOOP Lake approach Is set to change the way Security teams identify and combat emerging threats, enabling the broader retention of data for longer – optimised for search and addresses the challenge of how to detect threats across all your data in whatever format of wherever it may be stored.
HOOP Lake is a modern SOC/SIEM approach that empowers Security teams to accelerate adoption of Amazon Security Lake – there are 5 key building blocks that form the approach:
HOOP Orchestrate
Orchestrate your data flows – our orchestrator allows you to order and manipulate your ingest data sources based on your unique data set requirements. For example, your search actions may require additional fields to be captured, and our orchestrator will automatically add this to the streaming function, or you may want data enriched to a new regulatory standard, so we simply add additional components to the stream. Alternatively, you may want to enrich data prior to normalisation, or normalise before archiving. The HOOP Orchestrator uses modular blocks which allows streams to be manipulated without the need to re-write your streaming code.
HOOP Stream
Simply bring your own data – our data processor logic automatically receives log information from your data sources, and transforms this data into your target format, optimised and enriched for store, search and compliance. We focus on the OCSF and OSSEM standards, but also support others such as CIM. The purpose of our streamer is that it provides extremely high throughput and manipulation of data, based on how that log source needs to be treated. For example, we can enrich the stream with regulatory or threat intelligence data, we can truncate keywords and we can consolidate duplicate records with unique timestamps.
HOOP Store
Efficient store for your data – your normalised and enriched data is stored in a compressed and optimised format, allowing for common access and efficient search and the information is stored in a high performance DB with automatic compress/uncompress. We leverage Parquet tables to provide a high level of compression and high performance indexing, whilst our stream pre-event has already normalised the data for it to be stored in the most efficient manner.
HOOP Search
Natural language search for your data – our federated search capability allows you to optimally search centrally stored or distributed data, using natural language. Our search capability
automatically builds this requirement into a native and optimised query language. Whether you want to search your data in DQL, KQL or other formats, our query capability allows natural language search to be automatically converted into a highly optimised search string, which ensures that the search is as advantageous as possible, making it more likely that you will remain in your free search tier.
HOOP Comply
Compliance metrics at your fingertips – your data is automatically enriched at point of ingestion, making on the fly dashboard reporting and visualisation simple. Whether you want to report in NIST or MITRE frameworks, our streaming process automatically categorises data based on your needs, making observability built in as standard. As we have a highly scalable stream and store process, our compliance dashboards are created in real time, using live data which provides the most accurate view of your estate.
