Cyber Resilience

CVE-2023-6977

Lfprojects Mlflow 1.0.0 – 2.9.2

Public PoC
Published
20 December 2023
Modified
21 November 2024
Patch / advisory
CVSS Score v3.1 7.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.039 89th percentile
Risk Priority 83 floored blend · peak EPSS

Summary

CVE-2023-6977 is a high-severity Path Traversal: '\..\filename' (CWE-29) vulnerability in Lfprojects Mlflow. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 11% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

Deeper analysis AI-assisted summary

Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.

CVE-2023-6977 is a path traversal vulnerability (CWE-29) affecting the MLflow machine learning platform. It permits unauthorized reading of arbitrary files on the server hosting the application, as reflected in its CVSS 7.5 rating for network-accessible confidentiality impact without authentication.

An unauthenticated attacker with network reachability to an MLflow instance can exploit the flaw to retrieve sensitive server-side files. The attack requires no user interaction and directly compromises data confidentiality while leaving integrity and availability untouched.

Public references point to a fix merged in commit 4bd7f27c810ba7487d53ed5ef1038fca0f8dc28c of the mlflow/mlflow repository, along with associated hunter bounties that document the issue. Applying this patch or an equivalent update closes the traversal vector.

The vulnerability is relevant to AI/ML environments because MLflow is widely used to manage experiments, models, and artifacts. Its EPSS score remains elevated, with a current value of 0.8304 and a recorded peak of 0.8618.

EU & UK References

Vulnerability Data

This vulnerability enables malicious users to read sensitive files on the server.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
T1005 Data from Local System Collection
Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.
T1083 File and Directory Discovery Discovery
Adversaries may enumerate files and directories or may search in specific locations of a host or network share for certain information within a file system.
T1552 Unsecured Credentials Credential Access
Adversaries may search compromised systems to find and obtain insecurely stored credentials.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-2780Same product: Lfprojects Mlflow
CVE-2023-6975Same product: Lfprojects Mlflow
CVE-2023-1177Same product: Lfprojects Mlflow
CVE-2024-8859Same product: Lfprojects Mlflow
CVE-2023-6909Same product: Lfprojects Mlflow
CVE-2025-15036Same product: Lfprojects Mlflow
CVE-2024-3573Same product: Lfprojects Mlflow
CVE-2023-6831Same product: Lfprojects Mlflow
CVE-2024-2928Same product: Lfprojects Mlflow
CVE-2024-3848Same product: Lfprojects Mlflow

Affected Assets

lfprojects
mlflow
1.0.0 — 2.9.2

Mitigating Controls

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly require input validation and path sanitization that block this traversal vector.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

finds

Security testing can discover path-traversal flaws but does not itself prevent them in production code.

prevents

Application security requirements can mandate input validation and path canonicalization to block traversal sequences.

prevents

Secure architecture principles include directory sandboxing and safe file-access design that mitigate path traversal.

prevents

Secure coding standards directly require neutralizing path traversal sequences such as '\..\filename'.

References