CVE-2025-56427
Published: 04 December 2025
Summary
CVE-2025-56427 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Composio Composio. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked in the top 37.7% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
Deeper analysis
ComposioHQ version 0.7.20 is affected by a directory traversal vulnerability in the _download_file_or_dir function. The flaw is tracked as CVE-2025-56427 with a CVSS 3.1 score of 7.5 and is classified under CWE-200, exposing sensitive information to remote actors without authentication.
An unauthenticated attacker can send crafted requests over the network to traverse directories and retrieve arbitrary files from the server, achieving high confidentiality impact while leaving integrity and availability unaffected.
Public references include the vulnerable implementation in composio/server/api.py and a detailed proof-of-concept demonstrating file disclosure. The associated EPSS score has climbed from a low starting value to a recorded peak of 0.0121, indicating growing exploitation interest after public disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-201168
Vulnerability details
Directory Traversal vulnerability in ComposioHQ v.0.7.20 allows a remote attacker to obtain sensitive information via the _download_file_or_dir function.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Directory traversal in _download_file_or_dir enables remote file read outside intended paths, facilitating data collection from local system (T1005) and file/directory discovery (T1083).
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.