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Analyze » Lovable » LOV1776731185

Incident Score: Analysis & Impact (LOV1776731185)

The details regarding individual company incidents & reports gives you full view from every side.

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-2
Company Score Before Incident766 / 1000
Company Score After Incident764 / 1000
INCIDENT NUMBERLOV1776731185
Type of Cyber IncidentVulnerability
ATTACK VECTORMisconfiguration
DATA EXPOSEDChat histories, emails, names, dates...
INCIDENT DATE24/05/2025
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of Lovable'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 Lovable 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 Lovable breach identified under incident ID LOV1776731185.

The analysis begins with a detailed overview of Lovable's information like the linkedin page: https://www.linkedin.com/company/lovable-dev, the number of followers: 427012, the industry type: Software Development and the number of employees: 957 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 766 and after the incident was 764 with a difference of -2 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 Lovable and their customers.

Lovable recently reported "Lovable Denies Data Breach After User Exposes Chat History Vulnerability", a noteworthy cybersecurity incident.

Swedish no-code startup Lovable has refuted claims of a mass data breach after an anonymous user alleged that sensitive user information including chat histories, emails, names, and dates of birth was accessible through a security flaw.

The disruption is felt across the environment, and exposing Chat histories, emails, names, dates of birth, source code, personal details.

In response, moved swiftly to contain the threat with measures like Disabled chat message accessibility for enterprise customers, and stakeholders are being briefed through Public response on X (Twitter) acknowledging poor communication.

Overall, the incident is a reminder of why proactive monitoring and strong governance matter.

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 moderate confidence (60%), supported by evidence indicating vulnerability exploited via security flaw in public projects and Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating user accessed data after creating a free account. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Credentials In Files (T1552.006) with moderate confidence (50%), supported by evidence indicating source code and personal details exposed via misconfiguration. Under the Discovery tactic, the analysis identified Account Discovery (T1087) with moderate to high confidence (70%), supported by evidence indicating user could view other customers project data after account creation and Password Policy Discovery (T1201) with lower confidence (40%), supported by evidence indicating poor data visibility settings implied weak access controls. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating chat histories, emails, names, dates of birth compromised and Data from Information Repositories (T1213) with moderate to high confidence (80%), supported by evidence indicating user downloaded other customers project data including chat logs. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate confidence (60%), supported by evidence indicating user claimed to download other customers data and Exfiltration Over Web Service (T1567) with moderate confidence (50%), supported by evidence indicating data exposure via public-facing no-code platform. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (30%), supported by evidence indicating potential unauthorized modification of exposed data and Disk Wipe (T1561) with lower confidence (10%), supported by evidence indicating no evidence of disk wiping, but included for completeness. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Exploit Public-Facing Application (60%)
Valid Accounts (80%)
Credential Access
Unsecured Credentials: Credentials In Files (50%)
Discovery
Account Discovery (70%)
Password Policy Discovery (40%)
Collection
Data from Local System (90%)
Data from Information Repositories (80%)
Exfiltration
Exfiltration Over C2 Channel (60%)
Exfiltration Over Web Service (50%)
Impact
Data Destruction (30%)
Disk Wipe (10%)

Sources & References