Incident Score: Analysis & Impact (R.I1781144635)
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 R.I.C. Publications's Breach 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 R.I.C. Publications 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 R.I.C. Publications breach identified under incident ID R.I1781144635.
The analysis begins with a detailed overview of R.I.C. Publications's information like the linkedin page: https://www.linkedin.com/company/r.i.c.-publications, the number of followers: 574, the industry type: Book and Periodical Publishing and the number of employees: 34 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 752 and after the incident was 662 with a difference of -90 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 R.I.C. Publications and their customers.
On 04 June 2026, R.I.C Publications disclosed Data Breach issues under the banner "Cybersecurity Breach: Hacker Leaks Data of 116,000 R.I.C Publications Customers".
A Western Australian educational publisher, R.I.C Publications, is investigating a data breach after a threat actor known as '2019' published what they claim is the purchasing data of over 116,000 customers.
The disruption is felt across the environment, and exposing Full names, email addresses, phone numbers, street and IP addresses, order details, school names, with nearly 116,000 records at risk.
In response, teams activated the incident response plan, and began remediation that includes Reviewing security measures, and stakeholders are being briefed through Advising stakeholders to watch for phishing attempts or scam calls.
The case underscores how Active, with advisories going out to stakeholders covering Advising stakeholders to watch for phishing attempts or scam calls.
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 (50%), supported by evidence indicating attack vector such as Unknown, but data leak suggests system compromise and Trusted Relationship (T1199) with lower confidence (40%), supported by evidence indicating threat actor 2019 has targeted multiple Australian entities. Under the Credential Access tactic, the analysis identified Credentials from Password Stores (T1555) with moderate confidence (60%), supported by evidence indicating customer data (names, emails, phone numbers) exfiltrated and Unsecured Credentials: Credentials In Files (T1552.001) with moderate confidence (50%), supported by evidence indicating order details and school names compromised. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating full names, email addresses, phone numbers, order details leaked and Data from Information Repositories (T1213) with moderate to high confidence (70%), supported by evidence indicating purchasing data of 116,000 customers published. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating dataset shared on hacking forum by threat actor 2019 and Exfiltration Over Web Service (T1567) with moderate confidence (60%), supported by evidence indicating data published online for forum members. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (30%), supported by evidence indicating no evidence of further system compromise, but data leaked and Data Manipulation: Stored Data Manipulation (T1565.001) with lower confidence (40%), supported by evidence indicating unauthorized emails sent to customers on May 30, 2026. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- R.I.C. Publications Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/r.i.c.-publications/incident/R.I1781144635
- R.I.C. Publications CyberSecurity Rating page: https://www.rankiteo.com/company/r.i.c.-publications
- R.I.C. Publications Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/r-i1781144635-ric-publications-breach-june-2026/
- R.I.C. Publications CyberSecurity Score History: https://www.rankiteo.com/company/r.i.c.-publications/history
- R.I.C. Publications CyberSecurity Incident Source: https://www.cyberdaily.au/security/13728-exclusive-aussie-educational-publisher-r-i-c-publications-investigating-breach-after-customer-data-published-online
- 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