Microsoft Security Breach Incident Score: Analysis & Impact (MIC1769023724)

In this Rankiteo incident briefing, we review the Microsoft Security breach identified under incident ID MIC1769023724.

The analysis begins with a detailed overview of Microsoft Security's information like the linkedin page: https://www.linkedin.com/company/microsoft-security, the number of followers: 515370, the industry type: IT Services and IT Consulting and the number of employees: None 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 777 and after the incident was 773 with a difference of -4 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 Microsoft Security and their customers.

On 23 November 2025, Chainlit disclosed Data Breach, Privilege Escalation and Lateral Movement issues under the banner "Critical Vulnerabilities in Chainlit AI Framework Expose Sensitive Data and Enable Lateral Movement".

Security researchers at Zafran Security uncovered two high-severity vulnerabilities (CVE-2026-22218 and CVE-2026-22219) in Chainlit, an open-source AI framework for building conversational chatbots.

The disruption is felt across the environment, affecting Chainlit AI Framework and AWS EC2 instances with IMDSv1, and exposing API keys, Credentials and Internal file paths.

In response, moved swiftly to contain the threat with measures like Patch released (Chainlit v2.9.4), and began remediation that includes Upgrade to Chainlit v2.9.4, Enable IMDSv2 for AWS EC2 and Block private IP access, and stakeholders are being briefed through Responsible disclosure by Zafran Security.

The case underscores how Resolved (patches released), teams are taking away lessons such as Traditional vulnerabilities (SSRF, arbitrary file reads) are being embedded into AI infrastructure, creating new attack surfaces. Rapid adoption of AI frameworks requires heightened security scrutiny, and recommending next steps like Upgrade Chainlit to v2.9.4 or later, Migrate AWS EC2 instances from IMDSv1 to IMDSv2 and Implement allowlists for URI requests in MCP servers.

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 (80%), with evidence including critical Vulnerabilities in Chainlit AI Framework, and cVE-2026-22218 and CVE-2026-22219 and Valid Accounts (T1078) with high confidence (90%), with evidence including authenticated attackers to steal sensitive data, and authenticated Access attack vector. Under the Execution tactic, the analysis identified Exploitation for Client Execution (T1203) with moderate to high confidence (70%), supported by evidence indicating cVE-2026-22218 (Arbitrary File Read) enables attackers to read files. Under the Privilege Escalation tactic, the analysis identified Exploitation for Privilege Escalation (T1068) with moderate to high confidence (80%), with evidence including escalate privileges via SSRF (CVE-2026-22219), and privilege Escalation incident type and Abuse Elevation Control Mechanism (T1548) with moderate to high confidence (70%), supported by evidence indicating retrieving IAM role credentials via SSRF on AWS EC2 IMDSv1. Under the Credential Access tactic, the analysis identified Unsecured Credentials (T1552) with high confidence (90%), supported by evidence indicating aPI keys, credentials, and internal file paths exposed via file read, Cloud Instance Metadata API (T1552.005) with high confidence (90%), supported by evidence indicating aWS IAM role credentials theft via SSRF on IMDSv1 (169.254.169.254), and OS Credential Dumping (T1003) with moderate to high confidence (70%), supported by evidence indicating environment variables (/proc/self/environ) containing credentials. Under the Discovery tactic, the analysis identified File and Directory Discovery (T1083) with moderate to high confidence (80%), supported by evidence indicating arbitrary File Read (CVE-2026-22218) enables reading any file and Network Service Discovery (T1046) with moderate to high confidence (80%), supported by evidence indicating sSRF (CVE-2026-22219) allows probing internal network services. Under the Lateral Movement tactic, the analysis identified Exploitation of Remote Services (T1210) with moderate to high confidence (80%), supported by evidence indicating move laterally within compromised systems via SSRF and credentials and Use Alternate Authentication Material: Pass the Hash (T1550.002) with moderate confidence (60%), supported by evidence indicating iAM role credentials theft enables cloud lateral movement. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating database files (SQLite) and environment variables exfiltrated and Data from Information Repositories (T1213) with moderate to high confidence (80%), supported by evidence indicating sQLAlchemy with SQLite database files accessible via file read. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with moderate to high confidence (70%), supported by evidence indicating data exfiltration possible via SSRF and arbitrary file read and Transfer Data to Cloud Account (T1537) with moderate confidence (60%), supported by evidence indicating aWS IAM credentials enable data transfer to attacker-controlled cloud. Under the Defense Evasion tactic, the analysis identified Subvert Trust Controls: SIP and Trust Provider Hijacking (T1553.003) with moderate confidence (50%), supported by evidence indicating aI framework vulnerabilities embedded into trusted infrastructure. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.