Lfprojects vulnerabilities1 known to be exploited.

Vendor1 known exploited
The short answer

Lfprojects has 62 published vulnerabilities across 12 products in our catalogue. 1 of them is on the list of flaws known to be exploited, so criminals are using them now. The most affected product is Mlflow, with 53. If you run Lfprojects software, patch the exploited flaws first.

See the exploited flaws

The most recent Lfprojects flaw added to the known-exploited list is CVE-2026-64849, on 19 August 2026. We keep watching the known-exploited list.

Products

Which Lfprojects products have the most vulnerabilities?

Mlflow leads with 53 published vulnerabilities. Open a product to see its versions and which of its flaws criminals are already using.

Known exploited

Which Lfprojects vulnerabilities are being exploited?

1 flaw is on the government list of vulnerabilities known to be exploited. These are the ones criminals are using now, so they go first, whatever their severity score says.

  1. 9.3
    CVE-2026-64849CriticalKnown exploited
    MLflow Server-Side Request Forgery Vulnerability

    MLflow contains a server-side request forgery vulnerability that can allow attackers to reach internal or cloud metadata services and receive response_status and response_body.

    Chance of use9.8%Known exploited since19 Aug 2026
Exploit likelihood

Which Lfprojects flaws are most likely to be used?

Ranked by the latest exploit-likelihood forecast: the chance each flaw is used in an attack in the next 30 days. A high severity score on its own doesn't tell you that. Flaws shared by many other makers' products are left out.

50% or more10% to 49%Under 10%
  1. 90%

    Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.

    CVSS7.5Published18 Dec 2023
  2. 82%

    Redis is an open source, in-memory database that persists on disk.

    CVSS9.9Published3 Oct 2025
  3. 70%

    Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.2.1.

    CVSS9.8Published24 Mar 2023
  4. 68%

    Absolute Path Traversal in GitHub repository mlflow/mlflow prior to 2.5.0.

    CVSS10.0Published19 Jul 2023
  5. 48%

    An attacker can overwrite any file on the server hosting MLflow without any authentication.

    CVSS9.8Published16 Nov 2023
  6. 43%

    A path traversal vulnerability exists in mlflow/mlflow version 2.11.0, identified as a bypass for the previously addressed CVE-2023-6909.

    CVSS7.5Published16 May 2024
  7. 37%

    An issue in MLFlow versions 2.8.1 and before allows a remote attacker to obtain sensitive information via a crafted request to REST API.

    CVSS7.5Published5 Dec 2023
  8. 26%

    MLflow Tracking Server Model Creation Directory Traversal Remote Code Execution Vulnerability.

    CVSS9.8Published29 Oct 2025
  9. 22%

    A Local File Inclusion (LFI) vulnerability was identified in mlflow/mlflow, specifically in version 2.9.2, which was fixed in version 2.11.3.

    CVSS7.5Published6 Jun 2024
  10. 11%

    In mlflow/mlflow version 2.17.2, the `/graphql` endpoint is vulnerable to a denial of service attack.

    CVSS7.5Published20 Mar 2025
Precursor Intelligence

Running Lfprojects? We'll keep checking.

Looking flaws up one at a time doesn't scale. Tell us what you run once, and we tell you which flaws matter to you, in what order, and keep watching for new ones.

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  2. We match it to every flawOver 400,000 published flaws, checked against your list.
  3. Ranked by real-world riskA 0 to 100 score, led by evidence criminals are using it.
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Our catalogue lists 62 published vulnerabilities across 12 products and 773 versions from Lfprojects. The most recent Lfprojects flaw added to the known-exploited list is CVE-2026-64849, on 19 August 2026.

1 Lfprojects vulnerability is on the list of flaws known to be exploited. The most recently added is CVE-2026-64849. The full list is on this page.

Mlflow, with 53 published vulnerabilities. Its own page lists the ones known to be exploited.

Create a Precursor Intelligence account and track the Lfprojects products you run. We match them against every published flaw, give each one a risk score from 0 to 100 and tell you as soon as we spot one that affects you, by email, in the app or by webhook.