(writeup ongoing) ARP Flood Detection and Prevention Lab
In this lab, I simulated an ARP flooding attack using Scapy and analysed traffic behaviour with Wireshark to understand Layer 2 attack patterns. Detection and mitigation were implemented using Snort with custom rules to identify and reduce malicious ARP activity.
Threat Intelligence Platform Deployment & Vulnerability Intelligence Integration
As part of my personal cybersecurity lab, I designed and deployed a self-hosted instance of OpenCTI to simulate how a security team operationalises external threat intelligence within an internal environment. The objective was not merely to install a tool, but to build a working intelligence capability that mirrors real-world SOC and vulnerability management workflows.
Architecture & Secure Deployment
I deployed OpenCTI using a containerised architecture (Docker Compose), replicating a production-style stack consisting of:
OpenCTI backend and frontend services
Elasticsearch for indexed intelligence search
RabbitMQ for task distribution
Redis for caching
MinIO for object storage
Dedicated workers for asynchronous processing
During deployment, I:
Configured secure environment variables and unique service credentials
Generated and managed API tokens for connector authentication
Tuned Linux kernel parameters required by Elasticsearch
Diagnosed and resolved container health and dependency issues
Validated inter-service communication within an isolated Docker network
This ensured a stable, resilient intelligence platform rather than a basic lab install.
Integration of NVD Vulnerability Intelligence
To operationalise vulnerability intelligence, I integrated the National Vulnerability Database feed from the National Institute of Standards and Technology using the official CVE external import connector.
Key implementation steps included:
Obtaining and configuring an NVD API key to handle rate limits efficiently
Generating a dedicated OpenCTI platform token for secure API authentication
Deploying the connector as a separate container within the platform network
Monitoring ingestion logs to validate synchronisation and error handling
Verifying structured CVE objects within the OpenCTI knowledge graph
The connector continuously imports CVEs as structured Vulnerability entities, enabling correlation with intrusion sets, malware families, techniques, and reports.
Analyst-Oriented Application
From a security analyst’s perspective, this environment enables me to prioritise vulnerabilities based not only on severity scores, but also on exploitation likelihood and contextual threat relevance. By integrating CVE data into OpenCTI, I am able to correlate vulnerabilities with known adversary tradecraft, linking specific CVEs to intrusion sets, malware families, and attack techniques. This supports contextual analysis rather than treating vulnerabilities as isolated technical identifiers.
The platform also allows me to produce structured intelligence reports that connect vulnerabilities to threat actors and ongoing campaigns, mirroring how intelligence is communicated within a SOC or vulnerability management team. Through this setup, I can simulate intelligence-driven patch prioritisation by assessing which vulnerabilities pose realistic risk to an organisation based on threat activity and exposure. Instead of viewing CVEs as static references, I analyse them within a broader threat landscape, supporting risk-informed security decision-making.
Competencies Demonstrated
This project demonstrates my ability to deploy and operationalise a practical threat intelligence platform within a secure, containerised environment. I implemented secure API integration and connector configuration to ingest external intelligence feeds, ensuring reliable authentication and service communication. I managed structured data ingestion and validation, confirming that vulnerability records were correctly integrated into the platform’s knowledge graph.
In addition, I applied intelligence correlation techniques to connect vulnerabilities with adversary behaviours and threat entities, leveraging the platform’s graph-based architecture. Throughout the process, I troubleshot distributed service dependencies and container health issues, reinforcing my understanding of service orchestration and system reliability. Most importantly, I translated vulnerability intelligence into operational insight, demonstrating the ability to support evidence-based security decisions rather than simply collecting threat data.
