| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| AzuraCast through 0.23.x contains a command injection vulnerability in the Liquidsoap config generation for live recording that fails to quote the streamer username in process.run calls. Authenticated station users with Streamers and Profile permissions can set a username containing shell metacharacters and trigger command execution as the Liquidsoap process user when recording closes. |
| AzuraCast before 0.23.8 contains a broken access control vulnerability in the GET /api/station/{id}/vue/profile endpoint that allows authenticated users with only View Station Page permission to read Icecast/Shoutcast admin, source, and relay passwords. Attackers with View-only access can call this endpoint and receive plaintext frontend credentials in the JSON response, then use the admin password to authenticate to the Icecast admin interface without Broadcasting permission. |
| AzuraCast before 0.23.8 contains a server-side request forgery and local file read vulnerability in the AutoDJ remote playlist fetch (backend/src/Radio/AutoDJ/QueueBuilder.php, getMediaFromRemoteUrl()). A user with the station Media permission can create or update a playlist with source=remote_url and remote_type=playlist whose remote_url points at a file:// path or an internal/loopback/link-local HTTP endpoint. When AutoDJ builds the queue, the backend passes the user-supplied URL directly to file_get_contents() with no scheme allowlist and no private/loopback/metadata IP policy (PHP allow_url_fopen is enabled by default, including in the Docker image). Lines from the fetched resource are parsed as M3U/PLS entries, stored in StationQueue.autodj_custom_uri, and returned by GET /api/station/{station_id}/queue to any user with the Broadcasting permission, disclosing host files readable by the web container (for example /etc/passwd or the application .env) and the bodies of non-blind internal HTTP requests. No patched version was available at the time of publication. |
| AzuraCast is a self-hosted web radio management suite. In AzuraCast before 0.23.8, the station webhook URL validation in AbstractConnector::getValidUrl() (backend/src/Webhook/Connector/AbstractConnector.php), used by the Generic and Discord webhook connectors, rejects only URLs whose host is a literal link-local IP address (169.254.0.0/16 or fe80::/10). Loopback addresses and RFC1918 private ranges are not rejected, and any non-literal-IP hostname causes the IP parsing call to throw, which skips the check entirely. A user holding only the station-scoped WebHooks permission can therefore configure a webhook pointing at an internal, loopback, or private-network target and cause the server to issue an outbound HTTP POST containing the station's Now Playing data, resulting in server-side request forgery. The PUT /station/{id}/webhook/{id}/test endpoint allows the same low-privileged user to trigger the request on demand. At the time of the advisory no patched version was available. |
| AzuraCast (Composer package azuracast/azuracast) before 0.23.8 validates a station's "Remote Relay" URL only for URL syntax and an http/https scheme (Utilities\Urls::parseUserUrl, used by StationRemote::getUrlAsUri) and performs no host or IP address restriction. A user holding only the station-scoped RemoteRelays permission can therefore set a Remote Relay URL pointing at loopback, private-network, or cloud-metadata addresses (e.g. http://127.0.0.1:<port>/ or http://169.254.169.254/latest/meta-data/), and AzuraCast's periodic background Now Playing sync (AbstractRemote::getNowPlayingAsync) will automatically and repeatedly issue HTTP requests to that address, resulting in server-side request forgery against internal resources. This affects the main branch as of commit bcf8754eef3a268ad82c3db4d81f7920c3c28b56 (2026-07-31); no patched version is available at the time of the advisory. |
| AzuraCast before 0.23.8 contains a DQL injection vulnerability in the sortOrder API parameter of AbstractSearchableListAction.php. Attackers can inject arbitrary DQL expressions through the sortOrder parameter to extract sensitive database information including user credentials and station settings. |
| MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algo_from_pickle 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 algo_from_pickle on an attacker-supplied pickle file, an object defining __reduce__ is executed during deserialization, resulting in arbitrary code execution in the context of the application. |
| MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allow_pickle=True when loading .npy and .npz files. Attackers can craft malicious .npy files with pickle payloads that execute arbitrary code when loaded through MONAI's standard data pipeline. |
| MONAI before 1.6.0 is vulnerable to OS command injection in the nnUNetV2Runner component (monai.apps.nnunet.nnunetv2_runner). User-controlled values taken from the YAML configuration file (notably dataset_name_or_id) and from CLI/kwargs arguments are concatenated into a command string without quoting or validation and then passed to subprocess with shell=True, so shell metacharacters (e.g., ';' on Linux, '&' on Windows) are interpreted. If a victim loads and processes a crafted configuration file — for example by instantiating nnUNetV2Runner with the malicious YAML and invoking a training/validation job such as train_single_model() — arbitrary commands are executed with the privileges of the user running the job. |
| MONAI versions before 1.6.0 contain a remote code execution vulnerability in the algo_from_pickle() function due to unsafe pickle.loads() deserialization in monai/auto3dseg/utils.py. Attackers can craft malicious pickle files that execute arbitrary system commands when deserialized by the vulnerable function. |
| MONAI through 1.6.0 contains an eval injection vulnerability in _get_fake_spatial_shape() in monai/bundle/scripts.py. The function validates shape expressions with a helper that walks the AST and only collects ast.Name nodes, rejecting any name other than 'p' or 'n', before passing the string to eval(). Expressions built solely from constants and attribute, subscript, or call nodes (for example "(1).__class__.__bases__[0].__subclasses__()" or "int.__class__.__init__.__globals__") contain no ast.Name nodes and therefore bypass the allowlist. Because the shape value originates from bundle metadata consumed by _get_real_input_data and verify_net_in_out (reachable through the bundle 'verify_net_in_out' CLI flow), an attacker who can influence a bundle's metadata can escape the eval sandbox via object introspection chains and achieve code execution in this non-default flow. |
| In MONAI 1.6.0, PersistentDataset (monai/data/dataset.py) explicitly rejects the combination track_meta=True with weights_only=True, forcing users who cache MetaTensors (the default tensor type in MONAI >= 1.0) to run torch.load(hashfile, weights_only=False). Related cache helpers in monai/data/utils.py also call pickle.loads on cached content and derive cache keys with hashlib.md5. As a result, a local user with write access to a shared or world-writable cache_dir (e.g. /tmp/monai_cache, HPC scratch, ~/.cache/monai) can place a malicious pickle file that is deserialized the next time another user's MONAI pipeline reads the cache, resulting in arbitrary code execution in that user's context. All released versions of the monai pip package are affected; no patched version is available as of the advisory. |
| MONAI through 1.6.0 contains a remote code execution vulnerability in the bundle configuration engine that resolves _target_ values to arbitrary importable callables without an allow list and passes $ expressions to Python eval(). Attackers can publish a malicious bundle with crafted configuration containing arbitrary code that executes when a victim loads the bundle using monai.bundle.load() or monai.bundle.run(). |
| 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 Linux kernel, whose AML interpreter executes them. An attacker controlling the host — an assumed adversary in Contrast's threat model — can craft a table with malicious, Turing-complete AML bytecode that the guest kernel interprets with access to the full guest memory, including private pages, resulting in arbitrary code execution and disclosure or modification of confidential guest data. The issue affects the AMD SEV-SNP platforms Metal-QEMU-SNP and Metal-QEMU-SNP-GPU; Metal-QEMU-TDX is not affected because ACPI table contents are measured into RTMR 0 by OVMF on Intel TDX. Version v1.18.0 mitigates the attack by sandboxing the kernel AML interpreter so that it cannot read or write private memory pages. This weakness is not specific to Contrast but is generic to Confidential Computing setups that expose the ACPI interface to the host. |
| Contrast is a confidential-computing runtime for Kubernetes. In versions before 1.19.1, the Kata agent policies generated by the Contrast CLI contained a flaw in the CopyFile verification that allowed arbitrary writes to the guest root filesystem. A malicious process on the untrusted host able to connect to the Kata agent VSOCK could issue a series of CopyFile requests to overwrite security-critical files in the guest or trick the workload into disclosing sensitive data, effectively amounting to a full guest takeover. Users unable to upgrade can apply an equivalent rego policy fix passed to 'contrast generate --policy'. |
| Contrast before 1.16.0 is susceptible to remote attestation relay attacks. Contrast accepted any TEE attestation report that verified correctly and contained the expected firmware patch levels and software measurements, regardless of which machine produced it, so attestation was not bound to specific, physically trusted hardware. An attacker who can both intercept network traffic between the CLI and the Coordinator (or between the Coordinator and an attested component) and forge reports or extract secrets from any single TEE machine under their physical control can relay such a report to impersonate a Contrast Coordinator or a Contrast workload, defeating identity verification in Contrast's attested TLS (aTLS). |
| Contrast (edgelesssys/contrast) versions 1.14.0 before 1.23.1 generate runtime policies that fail to detect all container image substitutions. A bad rebase during a Kata Containers update accidentally introduced an `allow_storage` rule that accepts storage entries using the `image_guest_pull` driver without verifying the image digest. An attacker with access to the Kata agent API — for example, a Kubernetes cluster administrator in Contrast's threat model — can therefore substitute a container image with an exploit payload, provided the substituted image satisfies the remaining policy rules, undermining the confidential container's integrity guarantees. |
| Contrast is a confidential-computing runtime for Kubernetes. In versions before 1.4.1, a recovering Coordinator does not verify the seed supplied by the recovering party. An attacker can therefore stand up a rogue Coordinator whose manifest passes validation but whose secret seed is attacker-controlled. If network traffic is redirected from the legitimate Coordinator to the attacker's Coordinator, a workload owner can be impersonated when they either set a new manifest without comparing the returned root CA certificate against the existing one (the default behavior of the contrast CLI) or verify the Coordinator without comparing the root CA certificate against a trusted reference. Under these conditions the attacker can issue certificates that chain back to the rogue Coordinator's root CA and recover arbitrary workload secrets of workloads deployed after the attack. Secrets of the legitimate Coordinator (seed, workload secrets, CA), workload integrity, and certificates chaining to the mesh CA are not affected. |
| Contrast (Edgeless Systems) before 1.8.1 logs the workload secret to stderr, and thus to Kubernetes logs, when the Contrast initializer is configured with CONTRAST_LOG_LEVEL set to info or debug. Because info is the default, all installations that do not customize the initializer log level are affected. This exposes workload secrets — normally accessible only to the Contrast Coordinator, the initializer, the seedshare owner, and the workload owner — to Kubernetes users with get or list permission on pods/logs and to anyone with read access to the Kubernetes log storage, such as the cloud provider. Deployments that do not use workload secrets are unaffected. |
| Contrast, Edgeless Systems' runtime for confidential containers on Kubernetes, is affected in versions up to and including 1.9.0. The VOLUME directive in a Dockerfile (config.volumes in the OCI image configuration) is only a hint and is not handled specially by Kubernetes, but containerd adds a mount point for it when Kubernetes sets none, requiring the runtime to be able to push arbitrary data to the Kata agent. As a result, on bare-metal Contrast deployments (AKS deployments are not affected) that run an image declaring at least one VOLUME for which no Kubernetes mount exists at that path, the untrusted host can write arbitrary file trees below that mount point inside the confidential container, compromising the integrity of a directory that is typically important to the application's core functionality. Version 1.9.1 fixes the issue by disallowing this configuration in `contrast generate`. |
