OpenSOAR vs Torq Hyperautomation

OpenSOAR is an open-source platform for automating security alert handling with Python playbooks. It accepts alerts through webhooks, Elasticsearch polling, and syslog, then can normalize their data, extract indicators of compromise, and remove duplicates. Playbooks are asynchronous Python functions that teams can test, version, and run with standard Python packages. The execution engine supports parallel actions, timeouts, retries, and exponential backoff. For incident work, OpenSOAR can create and link cases, assign them, add comments and observables to timelines, and surface correlation suggestions. Listed integrations include Elastic Security, VirusTotal, AbuseIPDB, Slack, and Email; a Python SDK can be extended. AI options include Claude, OpenAI, and Ollama for tasks such as summarization, triage recommendations, playbook generation, and correlation. The maker says local Ollama can keep AI triage data within the network. OpenSOAR is self-hosted, with Docker Compose deployment documented, and is available on the web and through an API. The free plan is free, with no feature gates or per-action billing. The homepage labels the product beta.

Torq Hyperautomation is a cloud security-automation platform for enterprise security teams and SOC operations. It automates security tasks and workflows at scale as the foundation of the Torq AI SOC Platform. Users can create agentic or deterministic workflows, including repeatable common tasks, by describing a workflow, use case, or desired outcome in natural language; Torq then creates and validates production-ready workflows. Security uses include threat triage, containment, remediation, phishing response, vulnerability management, and cloud security posture remediation. Torq lists more than 400 out-of-the-box integrations, supports custom integrations, and connects through APIs, SSH, PowerShell, SQL, Python, Bash, Kubernetes, and CLI tools for AWS, GCP, and Azure. It offers playbook automation, alert enrichment, threat-intelligence actions, and case management. Deployment is cloud, with API, self-hosted, and web platforms listed. Pricing is paid and available on request. Monthly AI-credit allocations range from 500 to 20,000 by tier, reset without rollover, and each AI Agent execution allows up to 25 tool calls.