How Rapid7's Remediation Hub Reduces MTTR in Exposure Command

Rapid7’s newly launched Remediation Hub, part of its Exposure Command platform, aims to transform how security teams address vulnerabilities by shifting focus from detection to resolution. The tool integrates automated prioritization, step-by-step remediation guidance, and AI-driven scoring to reduce mean time to remediate (MTTR) by up to 60% according to customer case studies¹. This comes as organizations face increasing pressure to close security gaps faster amid rising ransomware attacks and regulatory requirements.

TL;DR: Key Capabilities

Automated risk scoring combining exploitability, asset value, and blast radius
Native workflows for bulk remediation (e.g., fixing 50+ CVEs via single library update)
AI-generated CVSS scoring (87% accuracy) compensating for NVD delays²
Integration with AWS Macie, GCP DLP, and Azure Defender
Alignment with Gartner’s CTEM framework stages³

Technical Implementation Details

The Remediation Hub operates within Rapid7’s Exposure Command platform, which unifies vulnerability management, cloud security, and threat intelligence feeds. Its prioritization engine uses three weighted factors: exploitability (40% weight), asset criticality (35%), and blast radius (25%). These metrics are calculated in real-time using both static asset inventories and dynamic network topology mapping⁴.

For cloud environments, the tool automatically correlates IAM misconfigurations with exposed services. A proof-of-concept integration with Azure DevOps shows how it can block vulnerable infrastructure-as-code deployments by scanning Terraform templates during CI/CD pipelines⁵. The system maintains an internal vulnerability database updated hourly, cross-referencing Rapid7’s threat intelligence on active exploitation.

Remediation Hub Scoring Criteria
Factor	Data Sources	Update Frequency
Exploitability	Metasploit modules, AttackerKB, in-the-wild reports	Real-time
Asset Criticality	CMDB tags, business unit mapping, data classification	Daily
Blast Radius	Network segmentation maps, service dependencies	Hourly

Operational Impact

Financial institutions using the platform reported reducing their MTTR from 45 days to 18 days on average⁶. The system’s bulk remediation feature proved particularly effective for addressing dependency chain vulnerabilities – one bank patched 62 Java library vulnerabilities across 3,000 servers by updating a single shared component.

For threat hunting teams, the integration with Vector Command allows simulated attacks against unpatched systems to validate exposure. Security operations centers can create automated playbooks that trigger when critical vulnerabilities are detected, such as immediately isolating assets with unpatched VMware ESXi systems during the CVE-2024-37085 outbreak⁷.

“Remediation Hub finally gives us a way to measure and improve our remediation velocity, not just our detection rates.” – SOC Manager, Fortune 500 Healthcare Company⁸

Future Developments

Rapid7’s roadmap includes zero-day response workflows in Q3 2025, which will automatically generate mitigation rules for emerging threats before official patches are available. The company is also expanding MDR coverage for third-party EDR tools like CrowdStrike and SentinelOne⁹. AI enhancements will introduce predictive exposure scoring based on attacker TTP patterns from Rapid7’s incident response caseload.

For organizations evaluating the platform, Rapid7 provides a risk reduction calculator that estimates time savings based on asset inventory size and current remediation rates. The tool is available through both SaaS and on-prem deployments, with API support for integrating with existing ticketing systems like ServiceNow and Jira.