Automated Incident Response: Streamlining Your SecOps

Security operations centers can no longer rely on purely human‑powered processes. As SaaS adoption and cloud footprints explode, teams face relentless waves of telemetry and alerts that are too many to triage by hand without burning out analysts or missing real threats.

Automated incident response using incident response automation tools are the only scalable solutions. By codifying detection rules, enrichment workflows and containment playbooks into scripts and APIs, you move from alert overload to rapid, reliable threat resolution with minimal manual steps.

This post shows you how to:

• Define and deploy an automated incident response workflow
• Automate detection tuning and alert enrichment today
• Build secure, high‑confidence remediation playbooks
• Lay the groundwork for future machine learning and LLM‑powered improvements

Whether your team writes custom scripts or leverages SOAR integrations, these high‑level strategies will help you reduce mean time to respond, cut incident backlog and keep your analysts focused on the threats that matter most.

What is Automated Incident Response?

Plainly, incident response automation involves going from threat or cyber attack identification to eradication and remediation with as few humans in the loop as possible. This fits into three (3) primary buckets of activity:

1. Incident Detection - How do you identify when an activity is suspicious enough to warrant further inspection?
2. Investigation - How do you take an initial lead (alert) and identify whether it’s benign or malicious behavior?
3. Remediation - How do you contain the threat and “stop the bleeding” in your environment?

Automating Detection

Generally there are two types of activities that teams want to automate:

1. Generate detection content
2. Tune existing detections

In recent years, generated detection content has been surprisingly less of an ask from security teams. Generally, native security tools come with their own rules that are out of the box and cover a broader set of use cases that are typically MITRE ATT&CK focused. While having reasonable coverage of MITRE ATT&CK tactics is a great place to start, if you’re looking for additional rule coverage, LLMs are quite good at building rule content given a guided prompt, which we discussed in a previous blog.

Tuning is generally the greater challenge. So many out-of-the-box rules from different security products create too much of a signal for security teams to handle. We’ve discussed how to build a strong process to addfress tuning, and with some clever scripting and periodic automation, there’s no reason you can’t automate this process.

Automating Investigation

This may be the hardest of the bunch to automate successfully. There’s no shortage of workflow, Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) tools you may have in your tool belt to help with this problem, but there are some challenges.

• SOAR tools require a good amount of heavy lifting from your team to get started. Whether that’s dragging and dropping workflows into place or writing some code to transform data into an investigative format that makes sense.
• There is so much variation when it comes to investigation that building static workflows for most alert types might leave you with an enriched alert, but without definitive answers.
• SIEMs lack deep contextual awareness, limiting their ability to fully automate accurate investigations.

We believe building investigations and dynamic plans is one of the areas that LLMs will help with most in the future, but today, focus on enriching your alert with as much threat intelligence and contextual data as possible to minimize false positives and reduce the cycles it takes for your team to interpret what’s happening.

• Enrich IPs with infrastructure metadata including reputation scores, or if they are a known TOR node, proxy, or hosting provider. 
• For alerts relating to identities, try to pull in some historical context programmatically (how often do they login from this location? Is there an endpoint detection and response agent that exists on this IP address?) so that users can differentiate between legitimate standard activity and what may be happening in the investigation.

Ultimately, you won’t be hands-off with an off-the-shelf approach to investigation, but you may significantly reduce the effort of manual data collection for incident responders and, hence, improve your response capabilities.

Automating Remediation

Seconds matter when it comes to active threat activity, like active malware or security breaches, and real-time mitigation is essential. This means that building incident response playbooks that enable auto-remediation, like automatically contain assets, block process execution or IP traffic, and ban malicious binaries identified across the environment are solid wins.

1. Revoke sessions for a specific user identity
2. Disable a user identity
3. Contain an endpoint
4. Kill a process
5. Ban a binary by hash
6. Block an IP

For extremely high-confidence detections, you may want to automate a subset of these response actions on detection triggers to create an automated response strategy.

Closing Thoughts

Unfortunately, teams are saddled with the responsibility of building automation prior to threat identification to manage inbound alert notification queues and respond fast enough to contain modern cyber threats. Using native API integrations with your existing security tools and a good bit of elbow grease, you can reduce the amount of energy needed to manage detections, enrich alerts, and respond effectively to known threats. Ultimately, this will reduce response times and accelerate threat remediation.

The challenge is that incident response automation requires its own development cycle, with each alert requiring its own type of planning, integrations, and automation that puts a different strain on your team. Creating an automated incident response plan is no mean feat.

At Prophet Security, we’re building a different security future for teams with our AI-powered, out-of-the-box automation for alert triage and investigation for any security alert (including custom detections). Request a demo of Prophet AI today to see our agentic AI SOC Analyst in action.

Frequently Asked Questions

What is automated incident response?
Automated incident response uses scripts, playbooks and APIs to detect, investigate and contain threats with minimal human intervention, speeding up resolution and reducing risk.

How does incident response automation work?
Incident response automation triggers on alerts, enriches them with context, applies decision logic and executes predefined playbook actions—like isolating endpoints or blocking IPs—to accelerate response.

What are the top automated incident response tools?
The leading tools integrate via APIs into SIEM, SOAR and endpoint platforms to orchestrate detection, investigation and containment tasks—enabling end‑to‑end automated incident response.

How do you create an automated incident response playbook?
Start by mapping high‑confidence detection triggers, define containment steps (e.g. disable accounts, kill processes), codify them in a playbook and test in observe mode before full automation.

What makes an automated incident response solution or system effective?
An effective solution combines reliable detection, contextual alert enrichment, dynamic decision logic and safe playbooks—backed by clear guardrails and human‑in‑the‑loop checks for low‑confidence cases.

How do you launch an incident response automation project?
Kick off with a pilot: select a use case, integrate core tools, build simple workflows, gather feedback, refine your automated incident response workflow and expand to additional alerts.

How can AI enhance automated incident response?
‍Prophet Security’s AI SOC Analyst leverages machine learning and large language models to enrich alerts with context, prioritize true threats, and suggest (or feed into) automated playbooks—speeding up response and reducing manual effort.

Further Reading

• SOC metrics that matter
• What is MFA fatigue attack?
• Investigating geo-impossible travel alert
• Top 3 scenarios for auto remediation
• Key SOC tools every security operations needs
• Demystifying SOC automation
• Alert triage and investigation in cybersecurity: best practices
• SOC challenges for analysts and managers
• Alert tuning best practices: keys to reducing false positives
• How to investigate Okta alerts
• AI SOC: Key to solving persistent challenges
• AI SOC Analyst: A comprehensive guide
• Will AI replace cybersecurity jobs?