ruby Breach Incident Score: Analysis & Impact (RUB4722547110925)

In this Rankiteo incident briefing, we review the ruby breach identified under incident ID RUB4722547110925.

The analysis begins with a detailed overview of ruby's information like the linkedin page: https://www.linkedin.com/company/ruby-life-inc, the number of followers: 30865, the industry type: Software Development and the number of employees: 262 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 754 and after the incident was 692 with a difference of -62 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 ruby and their customers.

A newly reported cybersecurity incident, "General Data Breach and Dark Web Data Trade Analysis", has drawn attention.

Data breaches often result from targeted cyberattacks or exploitation of security flaws, leading to the theft of sensitive information such as email addresses, passwords, Social Security numbers, credit card details, medical records, or corporate documents.

The disruption is felt across the environment, and exposing Email Addresses, Passwords and Social Security Numbers, plus an estimated financial loss of Potential (varies based on stolen data type, e.g., fraudulent purchases from payment cards, identity theft).

In response, moved swiftly to contain the threat with measures like Freezing Credit Reports, Locking Payment Cards and Resetting Compromised Passwords, and began remediation that includes Using Password Managers, Enabling Multi-Factor Authentication (MFA) and Removing Personal Data from Public Profiles, while recovery efforts such as Monitoring Dark Web for Leaked Data, Employing VPNs for Traffic Encryption and Using Burner Emails/One-Time Payment Methods continue, and stakeholders are being briefed through Public Advisories for Affected Users, Transparency Reports (for corporations) and Customer Notifications.

The case underscores how Ongoing (general analysis of dark web data trade practices), teams are taking away lessons such as Data breaches are often targeted and exploit overlooked security flaws, emphasizing the need for proactive cybersecurity measures, Stolen data is commodified and traded rapidly on underground markets, highlighting the importance of monitoring and quick response and Individuals and organizations must adopt layered defenses (e.g., password managers, VPNs, MFA) to mitigate risks, and recommending next steps like Use password managers and enable multi-factor authentication (MFA) for all accounts, Employ VPNs to encrypt internet traffic and prevent profiling by ISPs or advertisers and Adjust privacy settings on social media to restrict access to personal information, with advisories going out to stakeholders covering Individuals: Monitor accounts, use protective tools (VPNs, password managers), and limit exposure of personal data, Corporations: Strengthen cybersecurity posture, disclose breaches transparently, and assist affected customers and Regulators: Enforce compliance with data protection laws and penalize negligent organizations.

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.

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 (95%), with evidence including exploited security vulnerabilities to exfiltrate **36 million user records**, and exploitation of Security Flaws in attack_vector, Valid Accounts: Cloud Accounts (T1078.004) with moderate to high confidence (85%), supported by evidence indicating weak encryption and lax access controls implied compromised credentials, and Phishing: Spearphishing Link (T1566.002) with moderate to high confidence (70%), with evidence including phishing listed in attack_vector, and social Engineering listed in attack_vector. Under the Credential Access tactic, the analysis identified Credentials from Password Stores: Credentials from Web Browsers (T1555.003) with high confidence (90%), with evidence including 36 million user records included Passwords (from personally_identifiable_information), and site Credentials in type_of_data_compromised and OS Credential Dumping: Security Account Manager (T1003.002) with moderate to high confidence (75%), supported by evidence indicating weak encryption and lax access controls suggests credential harvesting. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (95%), supported by evidence indicating exfiltrate **36 million user records**, including real names, email addresses, physical addresses, credit card transaction details and Automated Collection (T1119) with moderate to high confidence (80%), supported by evidence indicating scale of breach (36M records) implies automated scraping/exfiltration. Under the Exfiltration tactic, the analysis identified Exfiltration Over Alternative Protocol: Exfiltration Over Unencrypted/Obfuscated Non-C2 Protocol (T1048.003) with high confidence (90%), with evidence including publicly dumped the data online implies unencrypted transfer, and data is extracted and sold/traded (from data_exfiltration) and Automated Exfiltration: Traffic Duplication (T1020.001) with moderate to high confidence (75%), supported by evidence indicating large-scale exfiltration (36M records) suggests automated processes. Under the Impact tactic, the analysis identified Data Destruction (T1485) with moderate to high confidence (85%), with evidence including publicly dumped the data online as a moral protest (destructive disclosure), and irreversible reputational damage and Data Encrypted for Impact (T1486) with lower confidence (30%), supported by evidence indicating weak encryption (implied, but no direct evidence of post-breach encryption). Under the Defense Evasion tactic, the analysis identified Indicator Removal: File Deletion (T1070.004) with moderate to high confidence (70%), supported by evidence indicating poor security measures, such as weak encryption and lax access controls (suggests log tampering/evidence removal) and Impair Defenses: Disable or Modify Tools (T1562.001) with moderate confidence (65%), supported by evidence indicating insufficient monitoring or detection of anomalous activity (from root_causes). Under the Persistence tactic, the analysis identified Account Manipulation: Additional Cloud Credentials (T1098.003) with moderate to high confidence (80%), supported by evidence indicating backdoors established (from initial_access_broker) for persistent access. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.