Incident Score: Analysis & Impact (CAICOD1770303020)
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 Codeway'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 Codeway 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 Codeway breach identified under incident ID CAICOD1770303020.
The analysis begins with a detailed overview of Codeway's information like the linkedin page: https://www.linkedin.com/company/codeway, the number of followers: 101446, the industry type: Software Development and the number of employees: 500 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 758 and after the incident was 613 with a difference of -145 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 Codeway and their customers.
Chat & Ask AI (Codeway) recently reported "AI Chat App Exposes 300 Million Private Conversations Due to Security Flaw", a noteworthy cybersecurity incident.
A popular mobile app, *Chat & Ask AI*, with over 50 million users across Google Play and Apple’s App Store has exposed hundreds of millions of private chatbot conversations due to a misconfigured backend database.
The disruption is felt across the environment, affecting Backend database (Google Firebase), and exposing 300 million private chatbot conversations, with nearly 300 million messages records at risk.
Formal response steps have not been shared publicly yet.
The case underscores how Unclear (full scope of exposure and malicious access unknown), teams are taking away lessons such as The incident underscores the risks of assuming AI chats remain private and highlights that security practices often lag behind adoption in AI tools.
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 misconfigured backend database allowed unauthenticated access. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Cloud Instance Metadata API (T1552.006) with moderate confidence (50%), supported by evidence indicating misconfigured Google Firebase database exposed data. Under the Collection tactic, the analysis identified Data from Information Repositories (T1213) with high confidence (90%), supported by evidence indicating 300 million private chatbot conversations exposed and Data from Local System (T1005) with moderate to high confidence (80%), supported by evidence indicating full chat histories, timestamps, AI models, custom chatbot names. Under the Exfiltration tactic, the analysis identified Transfer Data to Cloud Account (T1537) with moderate to high confidence (70%), supported by evidence indicating unauthenticated access to backend database (Google Firebase) and Exfiltration Over C2 Channel (T1041) with moderate confidence (50%), supported by evidence indicating malicious actors may have accessed the exposed data. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with lower confidence (40%), supported by evidence indicating misconfigured database suggests lack of security controls. Under the Impact tactic, the analysis identified Data Destruction (T1485) with lower confidence (30%), supported by evidence indicating full scope of exposure including malicious access unclear and Data Manipulation: Stored Data Manipulation (T1565.001) with lower confidence (40%), supported by evidence indicating potential exploitation of exposed sensitive conversations. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Codeway Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/codeway/incident/CAICOD1770303020
- Codeway CyberSecurity Rating page: https://www.rankiteo.com/company/codeway
- Codeway Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/caicod1770303020-codeway-chat-ask-ai-breach-january-2026/
- Codeway CyberSecurity Score History: https://www.rankiteo.com/company/codeway/history
- Codeway CyberSecurity Incident Source: https://www.foxnews.com/tech/millions-ai-chat-messages-exposed-app-data-leak
- 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