Step-By-Step Guide to Root Cause Analysis

You’ve probably sat through postmortems that arrive weeks after an incident, skimmed the headlines, and filed a PDF that nobody ever opens again. Traditional security reviews are too slow, shallow, and disconnected from your team’s workflows. What should be a real learning moment is often just a checkbox exercise. 

Fragmented tooling makes it worse. Logs scattered in multiple systems, alerts buried in emails, and security scans hidden in CI jobs all slow you down and cloud your view of what happened. 

By contrast, teams using integrated security platforms detect breaches 74 days faster and contain them 84 days sooner. 

The answer to the postmortem problem is automated root cause analysis that pulls logs, builds timelines, and surfaces fixes inside your CI and delivery workflow. This turns RCA into a simple daily habit that yields actionable results and tangible security improvements. 

What is Root Cause Analysis in Software and Security?

Root Cause Analysis (RCA) is a structured approach to identifying why a security incident or failure occurred. Unlike incident response, which is more about containment and remediation, RCA digs deep and is a continuous practice. It asks questions about systemic weaknesses and how tooling, alerts, developer rules, and runtime environments all contribute to causing the issue under review.

RCA generally involves: 

• Gathering logs from CI pipelines, runtime environments, and security scanners to reconstruct events.

• Establishing a sequence of events to trace when a vulnerability was introduced or missed.

• Connecting alerts from Static Application Security Testing (SAST), container scanners, and CSPM platforms to see overlapping findings or gaps.

• Engaging developers, security engineers, and operations teams to confirm hypotheses and validate that the identified root cause matches real-world behavior.



Why You Need Root Cause Analysis

Root Cause Analysis can feel like extra work, especially when you’re busy with tickets and production incidents, but the benefits justify the effort:

• Prevent recurring security incidents: When you trace a systemic failure behind a misconfigured container image or a poorly written function, you can fix the root problem, not just patch the underlying issue. Over time, you’ll see fewer repeat incidents and your team won’t be stuck fighting the same fires.
• Drive ongoing security improvements: RCA highlights gaps like missing security checks in your CI pipeline, insufficient unit test coverage, or blind spots in log collection. Each investigation becomes a lesson you feed into code reviews, policy updates, and stronger security controls.
• Show auditors that you’re improving: Regulators want proof of continuous monitoring and documented lessons from incidents. Root cause analysis reports are concrete evidence demonstrating your team doesn’t just slap on a quick patch and move on. Instead, it uses root cause analysis to improve.
• Turn postmortems into action: Instead of vague “lessons learned,” RCA yields concrete recommendations like “update the Semgrep policy for Django templates to catch missing escape filters.” These insights become action items that drive real change.



Step-by-Step Guide to Root Cause Analysis

1. Clearly Define the Problem

Before digging into logs or blaming tools, you must pinpoint exactly what went wrong. Spend time gathering the initial alert or report and distill it into a concise statement:

• Describe what happened (for example, “Unauthorized container image pulled into production”)

• When it was detected (specific date and time)

• Which systems or services were affected 

• What were the impacts

This clarity prevents you from chasing irrelevant leads. To capture all these details in one place, use an incident response platform like Cortex XSOAR or a ticketing system like Jira and ServiceNow. Treat this problem statement as a core foundation. If you misunderstand the issue at this stage, the rest of the analysis will be shaky at best. Also, keep in mind, tools like XSOAR, Jira, and ServiceNow are great for incident management but are insufficient for proper RCA  

2. Gather All Relevant Data

Once you know what you’re investigating, collect all the evidence you can. Pull SIEM logs, container runtime logs, logs from Kubernetes security tools, application logs, firewall and network device logs, and any related database or authentication records.

If you suspect a host has been compromised by malware or a rootkit, take a live memory snapshot with a tool like LiME or dump disk images using FTK Imager. Cloud environments also have built-in snapshot features you can use. These features are essential so you won’t lose any in-RAM artifacts (like passwords, decrypted data, running processes, network connections) if the machine is powered off. 



3. Reconstruct The Timeline

With data in hand, your next step is to build a chronological sequence of events to reveal the chain of causation. Ensure all logs are normalized to UTC or synchronized to NTP to avoid misordered events.

Use a timeline creation tool like Plaso or Timeline Explorer to ingest logs from multiple sources and quickly stitch them into a single view. These tools help you filter by IP addresses, user IDs, container SHA values, or Git commit hashes to highlight suspicious events. As you build the timeline, annotate key moments, such as a failed security scan or an unexpected deployment. These notes let you see exactly when the incident diverged from normal operations.

4. Identify Immediate Causes

With the timeline assembled, zero in on the first anomalies that directly triggered the incident. These might be missing security settings, unreviewed code commits, or failed automated checks. Speak with the developers or security engineers responsible for SAST tools like Semgrep or Trivy to confirm that the alert wasn’t a false positive or misinterpretation. And if you rely on CI/CD agents like GitLab Runner, verify that each security step was executed as expected.

It’s important to understand that immediate causes differ from root causes. They’re often symptoms: the visible tip of a deeper, systemic issue. Patching a missing configuration might stop the bleeding, but it won’t prevent a similar mistake from happening again.

Resist the urge to stop here and jump into remediation that may only address symptoms. Instead of stopping at the quick fix, treat these immediate causes as clues and use them as a guide for deeper probing. 

5. Ask “Why” Multiple Times (5 Whys Method)

Each immediate cause has deeper roots, and the 5 Whys method is your path to them. Take one proximate cause – for example, a missing policy check – and ask, “Why did that happen?” Record the answer, then ask “Why?” again, continuing until you uncover a policy gap, a process failure, or a cultural oversight that, once addressed, will prevent recurrence.

You don’t need exactly five layers every time. You can stop once you hit a concrete, fixable root. Here’s an example:

• Why did the container fail the Trivy scan? Because it included a vulnerable version of the openssl_client module.
• Why was OpenSSL outdated? Because the base image reference was not updated.
• Why was the base image not updated? Because the automated Dependabot check was disabled.
• Why was Dependabot disabled? Because the team had a sprint deadline, it turned off non-critical checks.
• Why did the sprint deadline override security checks? Because there’s no policy enforcing mandatory security gates in the pipeline.



In this case, a fixable root cause isn’t five layers deep; it’s the lack of enforced policy. But understanding how one decision cascades into systemic exposure helps teams address both the tactical issue and the underlying process gap.

And these aren’t abstract risks. From 2012 to 2014, many systems ran OpenSSL versions 1.0.1 through 1.0.1f - releases that contained the now-infamous Heartbleed vulnerability. Due to a missing bounds check in the TLS heartbeat extension, a malicious actor could craft a request that tricked the server into leaking up to 64 KB of memory. That memory could include private keys, credentials, or session data. It exemplifies how one outdated dependency, left unpatched in base images, can silently expose everything.

6. Use Dedicated RCA Tools 

Visual tools help teams see how multiple factors converge to cause an incident. A Fishbone (Ishikawa) diagram or Fault Tree Analysis lists categories like People, Process, Tools, and Environment, which helps you avoid missing hidden contributors.

Here’s how you can create a fishbone diagram:

• Draw a horizontal “spine” with the problem statement at the head.

• Branch out major categories: People (lacking security training), Process (missing CI policies), Tools (outdated scanners), Environment (misconfigured cloud settings).

• Under each branch, list specific factors. For example: Dependabot disabled, Semgrep rules outdated, or AWS IAM role mispermissions.

And how to develop a Fault Tree Analysis:

• Start with a top-level incident (Production breach due to a vulnerable container).

• Break it into AND/OR gates, showing how multiple failures combine, such as an outdated library, AND no security gate, AND a failed log alert.



Then, share that diagram and your “Why” chains with developers, operations, security, and compliance teams. Their feedback may reveal overlooked steps or additional context. The idea is to achieve consensus to ensure that your identified root cause and contributing factors are accurate and supported.

7. Document Findings and Assign Corrective Actions

Now it’s time to write a concise RCA report that ensures that future teams can learn from this incident without interviewing every person involved. Similar to a report for external penetration testing, this document should include sections for:

• Problem Statement: The precise issue you defined in Step 1.

• Timeline: Bullet-pointed or table-formatted sequence of events.

• Immediate Causes: List of triggers and errors.

• Root Cause: The underlying process or policy failure (with “Why” analysis and any diagrams)

• Contributing Factors: Anything else that made the failure more likely (such as missing documentation or lack of training).

• Corrective Actions

Under the Corrective Actions section, list specific tasks, such as updating deployment scripts, enforcing missing checks in your pipeline, or formalizing review processes. Assign each task to an owner with a clear deadline. If resources are limited, prioritize the corrective actions to address the most important steps first. And whenever possible, automate these fixes through your CI/CD pipelines or policy-as-code tools so nobody can bypass them.

Best Practices for Root Cause Analysis in DevOps Workflows

If RCA feels like trudging through mud, your team will likely skip it or rush the process. Instead, you want to automate and embed the process into your everyday workflows: 

Automate Evidence Gathering and Correlation

Use tools that automatically ingest pipeline logs, scan results, and runtime events into a unified view. Jit’s AI agents (SERA and COTA) can correlate Semgrep, Trivy, and Prowler findings, group related alerts, assess exploitability against your internal application security policies and business context, and then flag the highest-risk issues. 

Those insights are then turned into action with automatically created and enriched tickets (with code snippets and fix recommendations) routed to the right team. When you can skip data wrangling and ask “why,” investigations become faster and more accurate.



Conduct RCA for Repeat Failures

You don’t have to wait for a full-blown incident to run a root cause investigation. Any repeat failure can point to deeper process gaps. When you give minor incidents the same scrutiny as major ones, you can surface patterns early and stop minor annoyances from snowballing.

Make RCA a Regular Sprint Ritual

RCA loses momentum when it lives outside your regular practices. It’s better to carve out time in each sprint retrospective or hold quick, “blameless” review sessions right after incidents. Frame these conversations around “what can we learn?” rather than “who slipped up?” to build trust within your team. 

Stop Reacting and Start Preventing With Jit

Root cause analysis isn’t just about fixing what’s broken. It’s also about understanding why it broke and ensuring it doesn’t happen again. It identifies the deeper process failures, gaps in coverage, or missing guardrails that allowed the issue through. When treated as a proactive discipline, RCA becomes a lever for improving both security posture and development velocity. But to do that effectively, you need context and speed. 

Jit helps you bring that context together in real time. Instead of handing off raw scan results or scattered alerts, Jit correlates findings across your entire toolchain,  from code analysis to infrastructure and CI/CD, and maps them directly to the underlying root causes. Whether a misconfigured resource was pushed via Terraform, a static check was skipped, or a policy failed silently, Jit connects the dots and surfaces the “why” behind the “what.”

This context is delivered into the developer’s workflow so teams can investigate issues while the context is fresh and fix the underlying problem, not just the symptom. That’s how RCA becomes a habit, not a post-incident scramble.

Check out Jit and start turning every incident into an opportunity for prevention.