Incident Score: Analysis & Impact (STA1785256137)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Stack Sports'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 Stack Sports 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 Stack Sports breach identified under incident ID STA1785256137.
The analysis begins with a detailed overview of Stack Sports's information like the linkedin page: https://www.linkedin.com/company/stacksports, the number of followers: 0, the industry type: Software Development and the number of employees: 123 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 821 and after the incident was 786 with a difference of -35 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 Stack Sports and their customers.
On 27 July 2026, Stack Sports (SPay Inc.) disclosed Data Breach issues under the banner "Stack Sports Data Breach Exposes Payment Card and Bank Account Details".
Stack Sports, a global sports technology and payments platform operated by SPay Inc., recently disclosed a data breach that compromised sensitive financial information.
The disruption is felt across the environment, and exposing Cardholder names, payment card numbers, expiration dates, CVV codes, and checking account numbers.
In response, and stakeholders are being briefed through Mailed alerts to impacted individuals, filed breach notifications with attorneys general of California and Nebraska.
The case underscores how teams are taking away lessons such as Highlights ongoing vulnerabilities in payment processing systems and the need for heightened security measures, and recommending next steps like Monitor accounts for unauthorized transactions, contact financial institutions if suspicious activity is detected, order free credit reports, place fraud alerts, and set up security freezes, with advisories going out to stakeholders covering Monitor accounts for unauthorized transactions, contact financial institutions if suspicious activity is detected, order free credit reports, place fraud alerts, and set up security freezes.
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 Valid Accounts (T1078) with moderate to high confidence (70%), with evidence including unauthorized access, and payment processing systems vulnerabilities and Exploit Public-Facing Application (T1190) with moderate confidence (60%), supported by evidence indicating ongoing vulnerabilities in payment processing systems. Under the Credential Access tactic, the analysis identified Modify Authentication Process (T1556) with moderate to high confidence (70%), supported by evidence indicating compromised payment card numbers, CVV codes, and bank account numbers and Brute Force (T1110) with moderate confidence (50%), supported by evidence indicating unauthorized access went undetected for a month. Under the Collection tactic, the analysis identified Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating exposed cardholder names, payment card numbers, expiration dates, CVV codes and Data from Removable Media (T1025) with lower confidence (40%), supported by evidence indicating payment processing systems vulnerabilities. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (80%), supported by evidence indicating data breach compromised sensitive financial information and Transfer Data to Cloud Account (T1537) with moderate confidence (50%), supported by evidence indicating global sports technology and payments platform. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (30%), supported by evidence indicating no details on extent of breach and Data Manipulation: Stored Data Manipulation (T1565.001) with moderate confidence (60%), supported by evidence indicating high fraud risks due to compromised payment data. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Stack Sports Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/stacksports/incident/STA1785256137
- Stack Sports CyberSecurity Rating page: https://www.rankiteo.com/company/stacksports
- Stack Sports Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/sta1785256137-stack-sports-breach-may-2026/
- Stack Sports CyberSecurity Score History: https://www.rankiteo.com/company/stacksports/history
- Stack Sports CyberSecurity Incident Source: https://www.claimdepot.com/data-breach/stack-sports-2026
- 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