Incident Score: Analysis & Impact (FEDLOVBASNETREP1778156932)
The details regarding individual company incidents & reports gives you full view from every side.
Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Replit's Vulnerability and lateral movement inside company's environment.
- Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
- How Rankiteo’s incident engine converts technical details into a normalized incident score.
- How this cyber incident impacts Replit Rankiteo cyber scoring and cyber rating.
- Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.
Full Incident Analysis Transcript
In this Rankiteo incident briefing, we review the Replit breach identified under incident ID FEDLOVBASNETREP1778156932.
The analysis begins with a detailed overview of Replit's information like the linkedin page: https://www.linkedin.com/company/replit, the number of followers: 0, the industry type: IT Services and IT Consulting and the number of employees: 2 employees
After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 786 and after the incident was 785 with a difference of -1 which is could be a good indicator of the severity and impact of the incident.
In the next step of the video, we will analyze in more details the incident and the impact it had on Replit and their customers.
Lovable recently reported "AI Coding Tools Expose Sensitive Data in Massive Security Oversight", a noteworthy cybersecurity incident.
Israeli cybersecurity firm RedAccess uncovered over 380,000 publicly accessible applications built using low-code and AI-powered tools from Lovable, Base44, Replit, and Netlify, including roughly 5,000 containing sensitive corporate and personal data.
The disruption is felt across the environment, affecting 380,000+ applications built using Lovable, Base44, Replit, and Netlify, and exposing Sensitive corporate and personal data, with nearly Roughly 5,000 applications with sensitive data records at risk.
In response, moved swiftly to contain the threat with measures like Some exposed apps were taken down after companies were notified.
The case underscores how Ongoing, teams are taking away lessons such as The incident underscores how AI-driven 'vibe coding' tools designed for non-technical users are enabling rapid, large-scale data exposure due to lack of built-in safeguards.
Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.
The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.
MITRE ATT&CK® Correlation Analysis
Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Exploit Public-Facing Application (T1190) with high confidence (90%), supported by evidence indicating 380,000 publicly accessible applications built using low-code/AI tools and Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating employees without cybersecurity training...exposing confidential information. Under the Persistence tactic, the analysis identified Account Manipulation (T1098) with moderate to high confidence (70%), supported by evidence indicating apps were set to public by default, requiring manual adjustments. Under the Privilege Escalation tactic, the analysis identified Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating employees...inadvertently exposing confidential information through misconfigurations. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with moderate to high confidence (70%), supported by evidence indicating lack of built-in safeguards in AI-driven tools and Disabling Security Tools (T1089) with moderate confidence (60%), supported by evidence indicating misconfigured privacy settings in low-code/AI tools. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.001) with moderate to high confidence (80%), supported by evidence indicating internal bank records, customer service logs, medical records exposed. Under the Discovery tactic, the analysis identified Cloud Service Discovery (T1526) with high confidence (90%), supported by evidence indicating 380,000 publicly accessible applications indexed by Google and File and Directory Discovery (T1083) with moderate to high confidence (80%), supported by evidence indicating exposed apps contained medical records, financial data, corporate intelligence. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with high confidence (90%), supported by evidence indicating 5,000 applications containing sensitive corporate and personal data and Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating hospital app with unredacted patient complaints and staff schedules. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (80%), supported by evidence indicating publicly accessible applications indexed by Google and Exfiltration Over C2 Channel (T1041) with moderate confidence (60%), supported by evidence indicating sensitive data exposed via misconfigured privacy settings. Under the Impact tactic, the analysis identified Endpoint Denial of Service: Application or System Exploitation (T1499.004) with moderate confidence (50%), supported by evidence indicating potential brand reputation damage for affected entities and Data Manipulation: Stored Data Manipulation (T1565.001) with moderate to high confidence (70%), supported by evidence indicating phishing sites impersonating Bank of America, FedEx, McDonald’s. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Replit Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/replit/incident/FEDLOVBASNETREP1778156932
- Replit CyberSecurity Rating page: https://www.rankiteo.com/company/replit
- Replit Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/fedlovbasnetrep1778156932-lovable-base44-replit-netlify-fedex-vulnerability-may-2026/
- Replit CyberSecurity Score History: https://www.rankiteo.com/company/replit/history
- Replit CyberSecurity Incident Source: https://www.axios.com/2026/05/07/loveable-replit-vibe-coding-privacy
- Rankiteo A.I CyberSecurity Rating methodology: https://www.rankiteo.com/Images/rankiteo_algo.pdf
- Rankiteo TPRM Scoring methodology: https://static.rankiteo.com/model/rankiteo_tprm_methodology.pdf