# CVE-2023-1177: mlflow — Fixed in 2.2.1 🐍 🐍 PyPI Not in CISA KEV CRITICAL severity # CVE-2023-1177 — mlflow CRITICAL [Fix: mlflow/mlflow#7891](https://github.com/mlflow/mlflow/pull/7891/commits/7162a50c654792c21f3e4a160eb1a0e6a34f6e6e) CVE-2023-1177 is a critical-severity (CVSS 9.3) CWE-29 vulnerability in mlflow. 1 public exploit or proof-of-concept reference is indexed, so weaponization risk is real. A fix is available for mlflow — see the affected versions and patch details below. Path Traversal: '\\..\\filename' in mlflow/mlflow Also known asBIT-mlflow-2023-1177[GHSA-xg73-94fp-g449](/vulnerability/GHSA-xg73-94fp-g449)PYSEC-2023-29 Published Mar 24, 2023 Updated Oct 28, 2026 Affected 1 pkg Patched 1 / 1 Exploits 1 known Exploitation data as of Nov 5, 2026 · OSV.dev, NVD, FIRST.org (EPSS) ## Exploitation Status ### Proof-of-concept exploit code exists - CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation. - CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks. Exploitation and automatability from CISA’s SSVC triage for CVE-2023-1177. ## EPSS Exploitation Probability [via FIRST.org ↗](https://www.first.org/epss/) 69.7%probability of exploitation in next 30 days High Risk0.00% Lower risk than most CVEs99th percentile — riskier than 99% of all scored CVEsHighest risk 62.3%74.9%87.4%100.0%93.3%69.7%May 26Aug 26Nov 26 Probability of exploitation in the next 30 days, from [FIRST.org EPSS](https://www.first.org/epss/). ## How urgent is this, really ## Where this sits among everything scored ## Real-World Exposure 1 pkg affected 🐍`mlflow` Real-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 #### Impact Users of the MLflow Open Source Project who are hosting the MLflow Model Registry using the `mlflow server` or `mlflow ui` commands using an MLflow version older than MLflow 2.2.1 may be vulnerable to a remote file access exploit if they are not limiting who can query their server (for example, by using a cloud VPC, an IP allowlist for inbound requests, or authentication / authorization middleware). This issue only affects users and integrations that run the `mlflow server` and `mlflow ui` commands. Integrations that do not make use of `mlflow server` or `mlflow ui` are unaffected; for example, the Databricks Managed MLflow product and MLflow on Azure Machine Learning do not make use of these commands and are not impacted by these vulnerabilities in any way. The vulnerability detailed in [https://nvd.nist.gov/vuln/detail/CVE-2023-1177](https://nvd.nist.gov/vuln/detail/CVE-2023-1177) enables an actor to download arbitrary files unrelated to MLflow from the host server, including any files stored in remote locations to which the host server has access. #### Patches This vulnerability has been patched in MLflow 2.2.1, which was released to PyPI on March 2nd, 2023. If you are using `mlflow server` or `mlflow ui` with the MLflow Model Registry, we recommend upgrading to MLflow 2.2.1 as soon as possible. #### Workarounds If you are using the MLflow open source `mlflow server` or `mlflow ui` commands, we strongly recommend limiting who can access your MLflow Model Registry and MLflow Tracking servers using a cloud VPC, an IP allowlist for inbound requests, authentication / authorization middleware, or another access restriction mechanism of your choosing. If you are using the MLflow open source `mlflow server` or `mlflow ui` commands, we also strongly recommend limiting the remote files to which your MLflow Model Registry and MLflow Tracking servers have access. For example, if your MLflow Model Registry or MLflow Tracking server uses cloud-hosted blob storage for MLflow artifacts, make sure to restrict the scope of your server's cloud credentials such that it can only access files and directories related to MLflow. #### References More information about the vulnerability is available at [https://nvd.nist.gov/vuln/detail/CVE-2023-1177](https://nvd.nist.gov/vuln/detail/CVE-2023-1177). ## Affected Packages 1 total 1 fixed Ecosystem Package Vulnerable range Fix 🐍PyPI `mlflow` all versions 2.2.1`pip install --upgrade 'mlflow==2.2.1'` ## Affected Products 1 product · 1 configurations Application `mlflow`lfprojects < 2.2.1 range Exploits & PoCs 1 Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization. [ Path Traversal: '\\..\\filename' in GitHub repository mlflow/mlflow prior … huntr.devNVDMar 2023 ](https://huntr.dev/bounties/1fe8f21a-c438-4cba-9add-e8a5dab94e28) ## Detection & mitigation playbook Open-source dependency 1. ### Detect 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. 2. ### Fix Update mlflow to 2.2.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2023-1177 is resolved across your whole dependency graph. 3. ### Workarounds Resolve every user-supplied path to its canonical form and reject anything that escapes the intended directory, and run the component under an account that has no read or write access outside the directory it legitimately serves. ## How to detect CVE-2023-1177 A community-maintained Nuclei template exists for this CVE. You can scan for it directly: `nuclei -id cve-2023-1177 -u https://target` Template Mlflow <2.2.1 - Local File Inclusion Severity critical Impact Successful exploitation could allow an attacker to read sensitive files on the server. Remediation Upgrade Mlflow to version 2.2.1 or later to mitigate the vulnerability. Template by [ProjectDiscovery nuclei-templates](https://github.com/projectdiscovery/nuclei-templates) (iamnoooob, pdresearch), MIT licensed. [View the full template](https://github.com/projectdiscovery/nuclei-templates/blob/main/http/cves/2023/CVE-2023-1177.yaml). Scan only systems you are authorised to test. ## Frequently Asked Questions \### Impact Users of the MLflow Open Source Project who are hosting the MLflow Model Registry using the \`mlflow server\` or \`mlflow ui\` commands using an MLflow version older than MLflow 2.2.1 may be vulnerable to a remote file access exploit if they are not limiting who can query their server (for example, by using a cloud VPC, an IP allowlist for inbound requests, or authentication / authorization middleware). This issue only affects users and integrations that run the \`mlflow server\` and \`mlflow ui\` commands. Integrations that do not make use of \`mlflow server\` or \`mlflow ui\` are unaffected O3 Security · Impact-Aware SCA ### Is CVE-2023-1177 in your dependencies? Find it across PyPI, including transitive dependencies. [Scan my dependencies](/book-demo) [How O3 SCA works](/impact-aware-sca)