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02/08/2026 12:07 pm
TL;DR: Manual MDR workflows still leave a response gap between detection and containment, extending MTTR and giving attackers more time to escalate, move laterally, or exfiltrate data, according to Torq. Automation matters because the control problem is no longer visibility alone, but how quickly an alert becomes a governed action.
NHIMG editorial — based on content published by torq: MDR solutions and AI SOC automation for faster response
By the numbers:
- 80% of security teams still depend on fragmented point solutions rather than a unified platform.
- 85% of security leaders say AI has reduced analyst stress and burnout.
- 72% of SOC teams are already comfortable with fully autonomous AI handling medium-severity incidents and below.
Questions worth separating out
Q: How should security teams automate MDR response without losing control?
A: Start by mapping specific detections to specific containment actions, then decide which steps can execute automatically and which require approval.
Q: When does MDR automation create more value than manual analyst response?
A: Automation creates the most value when the response is repetitive, policy-based, and time-sensitive.
Q: What breaks when MDR tools cannot trigger response actions directly?
A: The response chain breaks at the handoff between detection and containment.
Practitioner guidance
- Implement response playbooks for identity-state changes Map MDR detections to concrete identity actions such as session termination, password reset, token revocation, and privileged account suspension.
- Prioritise open API and event-driven integrations Require MDR providers to support bidirectional APIs, real-time event delivery, and clear severity metadata so automated workflows can act without batch delays.
- Automate audit trails for containment actions Log the triggering detection, executed response, actor or workflow identifier, and final outcome for every automated action.
What's in the full article
Torq's full article covers the operational detail this post intentionally leaves for the source:
- How the AI SOC Platform is wired into MDR workflows through integration and orchestration logic
- Examples of containment actions such as endpoint isolation, IP blocking, and account suspension in live workflows
- How the Case Management capability captures response actions and audit trails across the incident lifecycle
- The Deepwatch case study and the MDR integration pattern Torq uses to illustrate scalable automation
👉 Read Torq's analysis of MDR automation and AI SOC response →
Mdr response latency: what it means for SOC teams now?
Explore further
02/08/2026 1:12 pm
Response latency is now a governance failure, not just an operational inconvenience. When MDR detects threats but cannot execute containment quickly, the control gap is not visibility, it is actionability. Security leaders should treat the time between detection and response as a measurable exposure window, because that is where privilege escalation and lateral movement happen.
A question worth separating out:
Q: What should teams do first when an MDR workflow touches accounts or sessions?
A: Define the access events that justify immediate action, then require approval logic for everything else. The first priority is to control the blast radius of compromised access by suspending risky sessions, revoking exposed credentials, and preserving evidence. If those steps are not pre-approved, automation will stall when it matters most.
👉 Read our full editorial: Mdr response latency is the gap automation closes for SOC teams
