HEAL Security | Cyber Threat, Incidents, Risk & Situational Intelligence for Healthcare. Breach Incident Score: Analysis & Impact (HEA1765325610)

In this Rankiteo incident briefing, we review the HEAL Security | Cyber Threat, Incidents, Risk & Situational Intelligence for Healthcare. breach identified under incident ID HEA1765325610.

The analysis begins with a detailed overview of HEAL Security | Cyber Threat, Incidents, Risk & Situational Intelligence for Healthcare.'s information like the linkedin page: https://www.linkedin.com/company/healsecurity, the number of followers: 7285, the industry type: Computer and Network Security and the number of employees: 15 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 749 and after the incident was 747 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 HEAL Security | Cyber Threat, Incidents, Risk & Situational Intelligence for Healthcare. and their customers.

A newly reported cybersecurity incident, "Healthcare Sector Cybersecurity Threats from Quantum Computing and Generative AI", has drawn attention.

Healthcare data breaches decreased from 37% in 2021 to 12% today due to improved security measures, but emerging threats from quantum computing and generative AI pose new risks.

The disruption is felt across the environment, affecting Cloud data storage, APIs and AI diagnostic systems, and exposing Medical history, insurance details, prescription records.

In response, moved swiftly to contain the threat with measures like Multi-factor authentication (MFA) adoption (57%) and Post-quantum cryptography prototyping (58%), and began remediation that includes GenAI-specific security tools (68%) and DevSecOps secrets management tools (15% effectiveness).

The case underscores how teams are taking away lessons such as Improved security measures like MFA reduce breaches, but emerging threats from quantum computing and AI require proactive preparation. Encryption of sensitive data and API security are critical gaps. Trust in AI systems and regulatory compliance are major concerns, and recommending next steps like Accelerate adoption of post-quantum cryptography, Enhance encryption for sensitive cloud data and Improve API security and secrets management.

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 moderate to high confidence (70%), supported by evidence indicating 32% manage over 500 APIs, each a potential entry point and Valid Accounts (T1078) with moderate to high confidence (80%), supported by evidence indicating only 15% rate DevSecOps secrets management tools as highly effective. Under the Credential Access tactic, the analysis identified Cloud Instance Metadata API (T1552.005) with moderate confidence (60%), supported by evidence indicating 27% lack confidence in tracking their data’s location in cloud and Unsecured Credentials (T1552) with moderate to high confidence (80%), supported by evidence indicating compromised credentials listed as vulnerability exploited. Under the Defense Evasion tactic, the analysis identified Disable or Modify Tools (T1562.001) with moderate confidence (50%), supported by evidence indicating 65% worry about AI model integrity, potentially bypassing security and Encrypted Channel (T1573) with lower confidence (40%), supported by evidence indicating only 4% encrypted at least 80% of sensitive data (lack of encryption). Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (70%), supported by evidence indicating 47% of healthcare cloud data is classified as sensitive and Exfiltration Over Alternative Protocol (T1048) with moderate confidence (60%), supported by evidence indicating aPI vulnerabilities as potential exfiltration channels. Under the Impact tactic, the analysis identified Data Manipulation: Stored Data Manipulation (T1565.001) with moderate to high confidence (70%), supported by evidence indicating 60% question trustworthiness of AI systems in diagnostics and Data Destruction (T1485) with moderate confidence (50%), supported by evidence indicating quantum computing threat to break current encryption standards. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.