CVE-2023-6568 is a medium-severity (CVSS 6.5) Cross-site Scripting (XSS) vulnerability in mlflow. 1 public exploit reference exists, so weaponization risk is real. A fix is available for mlflow — see the affected versions and patch details below.
Reflected XSS via Content-Type Header in mlflow/mlflow
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
How urgent is this, really
CVE-2023-6568 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 377,166 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
mlflowReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
A reflected Cross-Site Scripting (XSS) vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the Content-Type header in POST requests. An attacker can inject malicious JavaScript code into the Content-Type header, which is then improperly reflected back to the user without adequate sanitization or escaping, leading to arbitrary JavaScript execution in the context of the victim's browser. The vulnerability is present in the mlflow/server/auth/init.py file, where the user-supplied Content-Type header is directly injected into a Python formatted string and returned to the user, facilitating the XSS attack.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | mlflow | all versions | 2.9.0pip install --upgrade 'mlflow==2.9.0' |
Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for mlflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update mlflow to 2.9.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2023-6568 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like CVE-2023-6568 can be triaged on real exposure rather than presence alone.
Tailored to CVE-2023-6568. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
How to detect CVE-2023-6568
A community-maintained Nuclei template exists for this CVE. You can scan for it directly:
nuclei -id cve-2023-6568 -u https://target- Template
- Mlflow - Cross-Site Scripting
- Severity
- medium
- Impact
- Allows attackers to execute malicious scripts in the context of a user's session
- Remediation
- Sanitize and validate user input to prevent XSS attacks
Template by ProjectDiscovery nuclei-templates (ritikchaddha), MIT licensed. View the full template. Scan only systems you are authorised to test.
Frequently Asked Questions
Is CVE-2023-6568 in your dependencies?
O3 Security finds CVE-2023-6568 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.