|
| 1 | +--- |
| 2 | +sidebar_position: 11 |
| 3 | +--- |
| 4 | + |
| 5 | +:::info |
| 6 | +**Document Creation:** 23 September 2025. **Last Edited:** 23 September 2025. **Authors:** Syed Mahmood Aleem Huzaifa. |
| 7 | +**Effective Date:** 23 September 2025. **Expiry Date:** 23 September 2026. |
| 8 | +::: |
| 9 | + |
| 10 | +### Overview |
| 11 | +This project aimed to design and validate a Security Orchestration, Automation, and Response (SOAR) pipeline entirely on community editions of open-source tools. The intent was to replicate the core capabilities of a modern SOC (Security Operations Center) — detection, enrichment, case management, and automation — without relying on enterprise licenses. |
| 12 | + |
| 13 | +The chosen stack included: |
| 14 | + |
| 15 | +1. **Wazuh** – SIEM and endpoint monitoring platform. |
| 16 | + |
| 17 | +2. **Suricata** – Network Intrusion Detection System (NIDS). |
| 18 | + |
| 19 | +3. **MISP** – Threat intelligence sharing and enrichment platform. |
| 20 | + |
| 21 | +4. **TheHive** – Security Incident Response Platform (SIRP). |
| 22 | + |
| 23 | +5. **Cortex** – Analyzer engine for automated enrichment. |
| 24 | + |
| 25 | +The project was divided into nine sequential phases (Phases 1–9), each delivering one layer of capability. This page consolidates these phases and validates the pipeline by tracing the journey of a malicious IOC through every stage - from initial detection in Wazuh/Suricata through MISP enrichment, TheHive escalation, Cortex automation, and finally analyst case closure. |
| 26 | + |
| 27 | +### Phase-by-Phase Explanations |
| 28 | + |
| 29 | +### Phase 1 – Wazuh Core Setup |
| 30 | +Link to [Phase 1](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%201%20-%20Core%20Setup%20and%20Wazuh%20Deployment). |
| 31 | + |
| 32 | +**Why this phase matters**: |
| 33 | +No SOAR pipeline can function without a central log ingestion and correlation layer. Wazuh was chosen because it combines SIEM capabilities (log analysis, rule correlation, dashboards) with endpoint monitoring (File Integrity Monitoring, rootkit detection). |
| 34 | + |
| 35 | +**What was done**: |
| 36 | + |
| 37 | +1. Installed Wazuh Manager on Ubuntu 22.04. |
| 38 | + |
| 39 | +2. Deployed Wazuh Agents on Debian endpoints to forward system logs. |
| 40 | + |
| 41 | +3. Configured secure manager-agent communication using TLS certificates. |
| 42 | + |
| 43 | +4. Verified integration using the Wazuh Dashboard (Kibana plugin or web UI). |
| 44 | + |
| 45 | +**Validation**: |
| 46 | +Triggered simple test events (e.g., failed SSH logins) and confirmed alerts appeared in the Wazuh Dashboard. Agents were listed as active, and rule-based alerts (from Wazuh’s built-in rule set) were generated. |
| 47 | + |
| 48 | +**Link to next phase**: |
| 49 | +This established the detection backbone. Suricata logs and threat intelligence feeds would later enrich the data flowing through Wazuh. |
| 50 | + |
| 51 | +### Phase 2 – Suricata + Wazuh (Network Threat Detection) |
| 52 | +Link to [Phase 2](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%202%20-Network%20Threat%20Detection%20Integration%20%E2%80%93%20Suricata%20+%20Wazuh). |
| 53 | + |
| 54 | +**Why this phase matters**: |
| 55 | +While Wazuh can monitor endpoints, modern threats often exploit network-based vulnerabilities. By integrating Suricata with Wazuh, the project gained visibility into live network traffic. |
| 56 | + |
| 57 | +**What was done**: |
| 58 | + |
| 59 | +Installed Suricata 6.0.8 on Ubuntu. |
| 60 | + |
| 61 | +Configured it to run in AF-PACKET mode to capture live traffic. |
| 62 | + |
| 63 | +Enabled EVE JSON output, directing logs to /var/log/suricata/eve.json. |
| 64 | + |
| 65 | +Configured Wazuh to parse Suricata alerts by editing ossec.conf. |
| 66 | + |
| 67 | +Loaded the Emerging Threats Open ruleset, which includes detection for botnets, C2 servers, and common exploit attempts. |
| 68 | + |
| 69 | +**Validation**: |
| 70 | +Simulated malicious network traffic (e.g., connecting to a known blacklisted IP). Suricata generated an alert in eve.json. Wazuh ingested the alert and triggered rule correlation, displaying it in the dashboard. |
| 71 | + |
| 72 | +**Link to next phase**: |
| 73 | +This phase provided network-layer detection, which when combined with IOC enrichment from MISP, would allow alerts to be contextualized. |
| 74 | + |
| 75 | +### Phase 3 – MISP Deployment |
| 76 | +Link to [Phase 3](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%203%20-%20MISP%20Threat%20Intelligence%20Platform%20Deployment). |
| 77 | + |
| 78 | +**Why this phase matters**: |
| 79 | +Detection without context leads to alert fatigue. Analysts need to know if an IP/domain is just unusual or actively associated with malware or attacks. MISP solves this by storing and sharing structured IOCs. |
| 80 | + |
| 81 | +**What was done**: |
| 82 | + |
| 83 | +1. Deployed MISP on Kali Linux. |
| 84 | + |
| 85 | +2. Configured MySQL, PHP, and Apache services for the web interface. |
| 86 | + |
| 87 | +3. Created an admin user and organization. |
| 88 | + |
| 89 | +4. Added test IOCs: IP (1.2.3.4), domain (malicious.test), and a file hash. |
| 90 | + |
| 91 | +5. Published these as events, making them available to API queries. |
| 92 | + |
| 93 | +**Validation**: |
| 94 | +Queried the MISP API directly to confirm that IOCs were retrievable. Ensured that Cortex’s MISP Analyzer could also pull events from MISP. |
| 95 | + |
| 96 | +**Link to next phase**: |
| 97 | +With MISP in place, Wazuh could now enrich alerts by checking observables against known IOCs. |
| 98 | + |
| 99 | +### Phase 4 – Wazuh–MISP Enrichment Automation |
| 100 | +Link to [Phase 4](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%204%20-%20Wazuh%E2%80%93MISP%20Automation%20and%20Alert%20Enrichment). |
| 101 | + |
| 102 | +**Why this phase matters**: |
| 103 | +Without automation, analysts would need to manually query threat intelligence for each alert - a time-consuming process. Integration ensures enrichment happens at detection time. |
| 104 | + |
| 105 | +**What was done**: |
| 106 | + |
| 107 | +1. Installed the custom-misp Python script. |
| 108 | + |
| 109 | +2. Modified local_rules.xml in Wazuh to run this script on matching alerts (e.g., suspicious IPs, hashes). |
| 110 | + |
| 111 | +3. Configured the script to query the MISP API and return enrichment tags. |
| 112 | + |
| 113 | +4. Verified enriched alerts were displayed in Wazuh Dashboard with additional context. |
| 114 | + |
| 115 | +**Validation**: |
| 116 | +Generated an alert using a known malicious IP (1.2.3.4). Wazuh triggered the enrichment script, queried MISP, and tagged the alert with IOC context (e.g., “Threat Level: High, Category: C2”). |
| 117 | + |
| 118 | +**Link to next phase**: |
| 119 | +Enriched alerts would later be forwarded to TheHive, ensuring that analysts saw intelligence-backed alerts, not raw data. |
| 120 | + |
| 121 | +### Phase 5 – TheHive + Cortex Deployment |
| 122 | +Link to [Phase 5](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%205%20-%20SOAR%20Deployment-The%20Hive%20and%20Cortex). |
| 123 | + |
| 124 | +**Why this phase matters**: |
| 125 | +SIEMs detect and enrich alerts, but analysts need a platform to manage investigations, assign tasks, and escalate cases. TheHive provides this functionality, while Cortex powers observable enrichment. |
| 126 | + |
| 127 | +**What was done**: |
| 128 | + |
| 129 | +1. Deployed TheHive 5.2.4 and Cortex 3.1.6 via Docker Compose. |
| 130 | + |
| 131 | +2. Connected TheHive to Elasticsearch (for indexing) and Cassandra (for storage). |
| 132 | + |
| 133 | +3. Installed Cortex analyzers: AbuseIPDB, VirusTotal, MISP Analyzer. |
| 134 | + |
| 135 | +4. Configured TheHive to connect to Cortex using API keys. |
| 136 | + |
| 137 | +**Validation**: |
| 138 | +Created a test case in TheHive with an IP observable. Ran the AbuseIPDB analyzer through Cortex. The report (abuse confidence score, categories) was attached back to the observable. |
| 139 | + |
| 140 | +**Link to next phase**: |
| 141 | +With TheHive + Cortex live, Wazuh alerts could now be escalated into TheHive for case management and automated analysis. |
| 142 | + |
| 143 | +### Phase 6 – Behavioural Detection and Testing |
| 144 | +Link to [Phase 6](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%206%20-%20Behavioural%20Rules%20and%20Testing). |
| 145 | + |
| 146 | +**Why this phase matters**: |
| 147 | +IOC-based detection is useful but incomplete. Behavioural detection identifies patterns of malicious activity even when no IOC match exists. |
| 148 | + |
| 149 | +**What was done**: |
| 150 | + |
| 151 | +1. Configured Wazuh rules for SSH brute-force (multiple failed logins in short time). |
| 152 | + |
| 153 | +2. Monitored suspicious PowerShell commands on endpoints. |
| 154 | + |
| 155 | +3. Added rules for Suricata to flag malicious IP communication. |
| 156 | + |
| 157 | +4. Tested each by simulating attacks (e.g., brute-force SSH, scripted PowerShell). |
| 158 | + |
| 159 | +**Validation**: |
| 160 | +Alerts fired as expected and appeared in TheHive after Wazuh–TheHive integration. Enrichment confirmed whether behaviours were linked to known IOCs. |
| 161 | + |
| 162 | +**Link to next phase**: |
| 163 | +Behavioural rules combined with IOC intelligence provided comprehensive coverage for both known and unknown threats. |
| 164 | + |
| 165 | +### Phase 7 – Wazuh–TheHive Integration |
| 166 | +Link to [Phase 7](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%207%20-%20Wazuh%20&%20The%20Hive%20Integration). |
| 167 | + |
| 168 | +**Why this phase matters**: |
| 169 | +Analysts shouldn’t have to monitor both Wazuh and TheHive. Centralizing alerts in TheHive streamlines workflows. |
| 170 | + |
| 171 | +**What was done**: |
| 172 | + |
| 173 | +1. Configured Wazuh to forward alerts via TheHive API. |
| 174 | + |
| 175 | +2. Mapped Wazuh fields to TheHive alert schema (title, description, severity, source, observables). |
| 176 | + |
| 177 | +3. Verified alerts enriched in Wazuh (from MISP) were fully visible in TheHive. |
| 178 | + |
| 179 | +**Validation**: |
| 180 | +Triggered alerts appeared in TheHive’s Alerts section with metadata intact. Analysts could promote alerts directly to cases. |
| 181 | + |
| 182 | +**Link to next phase**: |
| 183 | +Now that alerts were centralized, Cortex analyzers could be run directly from TheHive. |
| 184 | + |
| 185 | +### Phase 8 – Cortex Observables |
| 186 | +Link to [Phase 8](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%208%20-%20Cortex%20Observables). |
| 187 | + |
| 188 | +**Why this phase matters**: |
| 189 | +Analysts often need to validate observables (IP, hash, domain) in external sources. Cortex enables automated checks without leaving TheHive. |
| 190 | + |
| 191 | +**What was done**: |
| 192 | + |
| 193 | +1. Configured Cortex analyzers (AbuseIPDB, MISP Analyzer, VirusTotal). |
| 194 | + |
| 195 | +2. Attached observables to cases in TheHive. |
| 196 | + |
| 197 | +3. Ran analyzers and confirmed reports were attached back to the case. |
| 198 | + |
| 199 | +**Validation**: |
| 200 | +When running AbuseIPDB on a malicious IP, the report showed abuse categories (e.g., SSH brute-force) and confidence score. |
| 201 | + |
| 202 | +**Link to next phase**: |
| 203 | +While Phase 8 required manual analyzer execution, Phase 9 introduced automation to remove analyst effort. |
| 204 | + |
| 205 | +### Phase 9 – Cortex Automation |
| 206 | +Link to [Phase 9](https://redback-operations.github.io/redback-documentation/docs/cybersecurity/Blue%20Team/Research/Automated%20Threat%20Hunting/Phase%209%20-%20Cortex%20Automation). |
| 207 | + |
| 208 | +**Why this phase matters**: |
| 209 | +Manual enrichment wastes analyst time. Automation ensures observables are enriched immediately upon alert creation. |
| 210 | + |
| 211 | +**What was done**: |
| 212 | + |
| 213 | +1. Configured TheHive notification rules (e.g., trigger on ArtifactCreated). |
| 214 | + |
| 215 | +2. Linked the rule to Cortex analyzers (AbuseIPDB, VirusTotal). |
| 216 | + |
| 217 | +3. Tested by injecting a malicious IP observable from Wazuh. |
| 218 | + |
| 219 | +**Validation**: |
| 220 | +AbuseIPDB ran automatically, returning a report without analyst intervention. The report was attached to the observable in TheHive. |
| 221 | + |
| 222 | +**Link to final validation**: |
| 223 | +This completed the SOAR loop, ensuring that alerts arriving in TheHive were already enriched and ready for analyst action. |
| 224 | + |
| 225 | +### Example of a validation scenario |
| 226 | + |
| 227 | + A malicious IP (1.2.3.4) published in MISP was used to validate the full workflow: |
| 228 | + |
| 229 | +1. *Detection*: Suricata flagged communication → Wazuh alert created. |
| 230 | + |
| 231 | +2. *Enrichment*: Wazuh triggered custom script → MISP tags added. |
| 232 | + |
| 233 | +3. *Escalation*: Alert forwarded into TheHive. |
| 234 | + |
| 235 | +4. *Automation*: Cortex ran AbuseIPDB automatically → report attached. |
| 236 | + |
| 237 | +5. *Case Handling*: Analyst promoted alert to case, added notes, and closed as True Positive. |
| 238 | + |
| 239 | +This confirms the pipeline can detect, enrich, escalate, automate, and resolve incidents in real time. |
| 240 | + |
| 241 | +### Future Scope |
| 242 | +This project demonstrates the feasibility of building a SOAR pipeline entirely with community tools. Each phase contributed incrementally: |
| 243 | + |
| 244 | +*Phases 1–2*: Core detection layer (host + network). |
| 245 | + |
| 246 | +*Phases 3–4*: Intelligence enrichment (MISP). |
| 247 | + |
| 248 | +*Phases 5–7*: Orchestration and centralized case management (TheHive). |
| 249 | + |
| 250 | +*Phases 8–9*: Automated enrichment and analysis (Cortex). |
| 251 | + |
| 252 | +**Strengths**: |
| 253 | + |
| 254 | +1. Real-time enrichment reduced manual triage time. |
| 255 | + |
| 256 | +2. TheHive centralized alert and case management. |
| 257 | + |
| 258 | +3. Cortex automation provided instant IOC validation. |
| 259 | + |
| 260 | +**Limitations**: |
| 261 | + |
| 262 | +1. Community editions lack enterprise scalability. |
| 263 | + |
| 264 | +2. Manual configuration (scripts, custom rules) required maintenance. |
| 265 | + |
| 266 | +3. Advanced case workflows (SLA, dashboards) limited compared to paid SOAR. |
| 267 | + |
| 268 | +### Conclusion |
| 269 | + |
| 270 | +The project successfully validated an end-to-end SOAR workflow across detection, enrichment, orchestration, automation, and response. Despite using only free/community editions, the stack demonstrated the capabilities required for modern SOCs. |
| 271 | + |
| 272 | +This marks the closure of the project - proving that a functioning SOAR pipeline can be achieved with open-source tools, and providing a foundation for future enhancements (e.g., scaling, machine learning-based correlation, or additional analyzers). |
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