As MSSPs, we serve our customers using Torq, and I work as a consultant in an MSSP that uses Torq as our main SOAR platform for our SOC.
Our usual use cases for Torq involve a variable amount of scenarios. We use it for fast automation building, as the automation building capability in Torq is low-code and quick with less scripting involved. This enables faster Tier 1 SOC automation, so all Level 1 analyst work is eliminated with Torq.
Our other use case centers on its cloud-native architecture. Torq makes use of API-first integrations and event-driven workflows with AI-assisted triage and response capabilities. It can be integrated with different multi-cloud vendors as well as other SaaS stacks, other MDR, and MSSP operations. Integration with cloud technologies is very straightforward.
Regarding Torq's automation of triage, investigation, and remediation actions across multiple attack surfaces, the data ingestion pipeline and workflow are excellent. Torq ingests alerts from a SIEM, EDR, CSPM, IAM, email, ASM, and other sources. It then performs normalization and enrichment. The third phase involves correlation across services, correlating data between different platforms when alerts arrive from endpoints, identity, cloud, network, or other sources. After correlation, the AI rule-based triage determines whether an alert is a false positive, a real attack, or its priority level. This is managed by the AI Agentic software within Torq. The automated response playbook then comes into play for remediation. If a playbook has been configured, it may disable a user, isolate a host, revoke a token, or patch a cloud issue based on what the AI detected. The final stage involves ticketing and validation. Torq audits everything, generates a ticket regarding whether the task has been completed, and includes a validation point that ensures all completed work has been confirmed or validated for completeness.