Results for “ics-scada”

Detect sophisticated cyber-physical attacks that modify PLC logic while spoofing sensor readings, covering PLC integrity monitoring, process anomaly detection, and multi-stage attack chain detection.

Detect command injection attacks against Modbus TCP/RTU protocol in ICS environments by monitoring for unauthorized write operations, anomalous function codes, malformed frames, and deviations from established communication baselines.

Detect network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning activity.

Runs KICS to scan infrastructure-as-code files for security vulnerabilities and compliance issues.

Integrates SAST, DAST, and SCA security scanning into CI/CD pipelines using open-source tools like Semgrep, Trivy, OWASP ZAP, and Gitleaks.

Chief Security Officer mode. (gstack)

Chief Security Officer mode. (gstack)

Deploys and configures Suricata IDS/IPS with Emerging Threats rulesets, EVE JSON logging, and custom rules for real-time network traffic inspection, threat detection, and integration with SIEM platforms.

Develop and implement OT-specific incident response playbooks aligned with SANS PICERL framework, IEC 62443, and NIST SP 800-82 that address unique ICS challenges including safety-critical systems, limited downtime tolerance, and coordination between IT SOC, OT engineering, and plant operations teams.

Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline.

Detect anomalies in DNP3 protocol communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.

Analyze PLC firmware for security vulnerabilities including hardcoded credentials, insecure updates, backdoors, memory corruption, and undocumented debug interfaces using static and dynamic analysis techniques.

Deploys anomaly detection for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications.

Design and implement network segmentation for industrial control systems using the Purdue Enterprise Reference Architecture model, separating OT and IT networks into hierarchical security zones with strict traffic control.