249725 matches found
Arbitrary Code Injection
Overview Affected versions of this package are vulnerable to Arbitrary Code Injection via the ConfigWriter::cleanUpString process. An attacker can execute arbitrary shell commands by injecting specially crafted Liquidsoap string interpolation sequences into playlist URLs or station metadata field...
Arbitrary Code Injection
Overview Affected versions of this package are vulnerable to Arbitrary Code Injection via the remote relay password field due to incomplete migration from the cleanUpString method to toRawString. An attacker can execute arbitrary code in the Liquidsoap process, disclose internal API keys, or...
CVE-2026-100864
heym before 0.0.91 contains a sandbox escape vulnerability in the expression engine's DotList map/filter and fallback resolver that allows authenticated users to execute arbitrary Python code. Attackers can craft workflow expressions using dunder attribute access through item expressions or the...
CVE-2026-100865
Heym before 0.0.53 evaluates workflow condition expressions using Python's eval with insufficient sandboxing in the workflow executor service. Authenticated users can edit workflow condition nodes or import malicious templates to execute arbitrary Python and OS commands as the backend process use...
PYSEC-2026-4020
MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allowpickle=True when loading .npy and .npz files. Attackers can craft malicious .npy files with pickle payloads that execute arbitrary code when loaded through...
CVE-2026-100845
MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allowpickle=True when loading .npy and .npz files. Attackers can craft malicious .npy files with pickle payloads that execute arbitrary code when loaded through...
PYSEC-2026-4021
MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algofrompickle function in monai/auto3dseg/utils.py. The function reads a .pkl file and passes its contents to pickle.loads without validating the data source or content. If an application invokes algofrompickle ...
CVE-2026-100846
MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algofrompickle function in monai/auto3dseg/utils.py. The function reads a .pkl file and passes its contents to pickle.loads without validating the data source or content. If an application invokes algofrompickle ...
PYSEC-2026-4021
MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algofrompickle function in monai/auto3dseg/utils.py. The function reads a .pkl file and passes its contents to pickle.loads without validating the data source or content. If an application invokes algofrompickle ...
PYSEC-2026-4020
MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allowpickle=True when loading .npy and .npz files. Attackers can craft malicious .npy files with pickle payloads that execute arbitrary code when loaded through...
PYSEC-2026-4016
In MONAI 1.6.0, PersistentDataset monai/data/dataset.py explicitly rejects the combination trackmeta=True with weightsonly=True, forcing users who cache MetaTensors the default tensor type in MONAI = 1.0 to run torch.loadhashfile, weightsonly=False. Related cache helpers in monai/data/utils.py al...
CVE-2026-100841
In MONAI 1.6.0, PersistentDataset monai/data/dataset.py explicitly rejects the combination trackmeta=True with weightsonly=True, forcing users who cache MetaTensors the default tensor type in MONAI = 1.0 to run torch.loadhashfile, weightsonly=False. Related cache helpers in monai/data/utils.py al...
CVE-2026-100839
Contrast is a confidential-computing runtime for Kubernetes. In versions before 1.18.0, the guest kernel's ACPI/AML handling is vulnerable to an AML injection attack "BadAML". ACPI tables containing AML bytecode are passed from the untrusted host QEMU to the guest firmware OVMF and on to the Linu...
PYSEC-2026-4016
In MONAI 1.6.0, PersistentDataset monai/data/dataset.py explicitly rejects the combination trackmeta=True with weightsonly=True, forcing users who cache MetaTensors the default tensor type in MONAI = 1.0 to run torch.loadhashfile, weightsonly=False. Related cache helpers in monai/data/utils.py al...
CVE-2026-100721
vm2 before 3.12.2 contains an authorization bypass in the NodeVM external-module resolver. When an embedder configures require.external with a custom resolver and context: 'host', LegacyResolver.customResolve in lib/resolver-compat.js records the resolved module directory in this.externals as new...
EUVD-2026-87821
AzuraCast before 0.23.6 contains a code injection vulnerability in the remote relay password field due to incomplete migration from the vulnerable cleanUpString method to toRawString. Attackers with RemoteRelays station permission can inject nested Liquidsoap interpolation syntax to execute...
EUVD-2026-87842
MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algofrompickle function in monai/auto3dseg/utils.py. The function reads a .pkl file and passes its contents to pickle.loads without validating the data source or content. If an application invokes algofrompickle ...
EUVD-2026-87843
MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allowpickle=True when loading .npy and .npz files. Attackers can craft malicious .npy files with pickle payloads that execute arbitrary code when loaded through...
CVE-2026-100845
MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allowpickle=True when loading .npy and .npz files. Attackers can craft malicious .npy files with pickle payloads that execute arbitrary code when loaded through...
EUVD-2026-87847
In MONAI 1.6.0, PersistentDataset monai/data/dataset.py explicitly rejects the combination trackmeta=True with weightsonly=True, forcing users who cache MetaTensors the default tensor type in MONAI = 1.0 to run torch.loadhashfile, weightsonly=False. Related cache helpers in monai/data/utils.py al...