CVE-2024-43610
Published: 09 October 2024
Summary
CVE-2024-43610 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Microsoft Copilot Studio. Its CVSS base score is 7.4 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 10.2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Enterprise AI Assistants; in the Privacy and Disclosure risk domain; MITRE ATLAS techniques in scope: Obtain Capabilities (AML.T0016), Poison Training Data (AML.T0020).
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-40359
Vulnerability details
Exposure of Sensitive Information to an Unauthorized Actor in Copilot Studio allows a unauthenticated attacker to view sensitive information through network attack vector
- CWE(s)
AI Security AnalysisAI
- AI Category
- Enterprise AI Assistants
- Risk Domain
- Privacy and Disclosure
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Copilot Studio is a Microsoft platform for building and deploying custom enterprise AI assistants (copilots) powered by LLMs, making it a clear fit for Enterprise AI Assistants category.
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
The vulnerability enables unauthenticated remote exploitation of a public-facing cloud application (T1190: Exploit Public-Facing Application), resulting in exposure of sensitive information likely including credentials or secrets (T1552: Unsecured Credentials).
MITRE ATLAS TechniquesAI
MITRE ATLAS techniques
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.