Manufacturing: Cloud Incident Response Transformation
Key outcomes
Mean Time to Detect (Cloud)
Mean Time to Contain
Evidence Collection Success
Incident Response Readiness
The challenge
A global manufacturing company with operations across 15 countries had migrated 70% of their infrastructure to AWS and Azure over 18 months. However, their incident response capabilities hadn't evolved. When a cryptomining attack hit their AWS environment, it took 14 hours to detect and 3 days to fully contain. The IR team struggled with ephemeral cloud resources - logs disappeared before they could be collected, and manual forensics was impossible in auto-scaling environments. They had no cloud-specific playbooks, no automated evidence collection, and investigators were still using legacy on-prem tools. The incident cost them $180,000 in compute overages and exposed serious gaps in their security program.
Our approach
We embedded a 2-engineer FDE pod for an 8-week cloud IR modernization engagement: Weeks 1-3 (Cloud Forensics Foundation): - Implemented automated evidence collection using AWS Systems Manager and Azure Automation - Configured cloud-native logging pipelines to centralized S3/Blob storage with immutability and retention policies - Built forensic snapshots automation for EC2/VM instances triggered by security alerts - Deployed GuardDuty, Security Hub, and Azure Defender with customized alert routing Weeks 4-6 (Incident Response Playbooks): - Created 8 cloud-specific IR playbooks (cryptomining, credential compromise, data exfiltration, ransomware, misconfigured S3 buckets, IAM privilege escalation) - Automated containment actions: isolate instances, revoke IAM credentials, quarantine S3 buckets, block malicious IPs - Built investigation workflows that automatically collect: CloudTrail logs, VPC Flow Logs, EBS snapshots, memory dumps, network traffic captures - Integrated with PagerDuty for on-call escalations and StatusPage for internal communications Weeks 7-8 (Testing & Training): - Ran tabletop exercises for each playbook with the IR team - Executed purple team exercises simulating attacks in non-prod environments - Documented response procedures and decision trees - Trained 12 security engineers on cloud forensics and IR automation
The outcome
The company went from reactive firefighting to proactive readiness: - Mean Time to Detect for cloud incidents dropped from 14 hours to 8 minutes with automated monitoring - Mean Time to Contain decreased from 3 days to 35 minutes with automated containment actions - Forensic evidence collection became 100% automated - no more lost logs from terminated instances - The IR team successfully responded to 4 incidents in the next 3 months with zero data loss - Compute cost anomalies are now detected within 5 minutes, preventing another cryptomining incident that would have cost $220,000 Three months post-engagement, they detected a credential stuffing attack against their Azure environment. The automated playbook isolated the compromised VM, collected forensics, rotated credentials, and alerted the IR team - all within 12 minutes. The CISO commented: 'This would have been a multi-day incident before Covenda. Now it's handled before I finish my coffee.'
The cryptomining incident was our wake-up call. Covenda didn't just patch the problem - they built us a modern cloud IR capability. We went from feeling helpless in the cloud to having faster response times than our on-prem environment.
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