聚合 NVD、CVE 及多源情报，深度解析 RCE 等高危风险。系统集成 CVSS 与 EPSS 模型，动态追踪 Exploit 资源与 PoC 公开状态，研判可利用性。结合官方补丁与修复方案，优化漏洞管理优先级，缩短响应周期，保障资产安全。
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| CVE | 描述 | 最高 CVSS | EPSS % | 公开时间 | 更新时间 |
|---|---|---|---|---|---|
| CVE-2026-12243 | NLTK version 3.9.4 is vulnerable to a path traversal attack due to an incomplete fix for GitHub Issue #3504. The `_UNSAFE_NO_PROTOCOL_RE` regex in `nltk/data.py` checks for literal `../` sequences but fails to account for percent-encoded traversal sequences such as `..%2f`. The `url2pathname()` function decodes these sequences after the validation step, allowing an attacker to bypass the protection. This vulnerability enables an attacker to read arbitrary files accessible to the Python process b | 7.5 | 0.49% | 2026-06-29 | 2026-06-30 |
| CVE-2026-6657 | A vulnerability in jupyter-server versions 1.12.0 through 2.17.0 allows an attacker to bypass CORS origin validation when the `allow_origin_pat` configuration is used. The issue arises from the use of `re.match()` for validating the `Origin` header, which only anchors at the start of the string. This allows attacker-controlled domains such as `trusted.example.com.evil.com` to pass validation against patterns intended to match `trusted.example.com`. The vulnerability affects multiple locations in | 8.8 | 0.13% | 2026-06-03 | 2026-06-30 |
| CVE-2026-5497 | vLLM versions 0.8.0 and later are vulnerable to an Out-of-Memory (OOM) Denial of Service (DoS) attack due to unbounded frame count processing in the `VideoMediaIO.load_base64()` method. When processing `video/jpeg` data URLs, the method splits the base64 data string on commas to extract individual JPEG frames without enforcing a frame count limit. An attacker can exploit this by crafting a single API request containing thousands of comma-separated base64-encoded JPEG frames in a data URL, causin | 7.5 | 0.54% | 2026-06-11 | 2026-06-29 |
| CVE-2026-5241 | A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `Lig | 9.6 | 0.49% | 2026-06-03 | 2026-06-29 |
| CVE-2026-4035 | A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environment credentials to an attacker-controlled endpoint. This issue arises because the `api_key` field in gateway secrets can accept `$ENV_VAR` references, which are resolved against the MLflow server's environment during runtime. The resolved secrets are then sent in provider authentication headers to th | 7.7 | 0.38% | 2026-06-03 | 2026-06-29 |
| CVE-2026-2614 | A vulnerability in the `_create_model_version()` handler of `mlflow/server/handlers.py` in mlflow/mlflow versions 3.9.0 and earlier allows an unauthenticated remote attacker to read arbitrary files from the server's filesystem. The issue arises when a `CreateModelVersion` request includes the tag `mlflow.prompt.is_prompt`, which bypasses source path validation. This enables an attacker to store an arbitrary local filesystem path as the model version source. The `get_model_version_artifact_handle | 7.5 | 0.74% | 2026-05-11 | 2026-06-29 |
| CVE-2026-1462 | A vulnerability in the `TFSMLayer` class of the `keras` package, version 3.13.0, allows attacker-controlled TensorFlow SavedModels to be loaded during deserialization of `.keras` models, even when `safe_mode=True`. This bypasses the security guarantees of `safe_mode` and enables arbitrary attacker-controlled code execution during model inference under the victim's privileges. The issue arises due to the unconditional loading of external SavedModels, serialization of attacker-controlled file path | 7.8 | 0.33% | 2026-04-13 | 2026-06-29 |
| CVE-2026-11816 | Keras versions prior to 3.14.0 are vulnerable to a path traversal issue in the archive extraction utilities located in `keras/src/utils/file_utils.py`. The functions `filter_safe_tarinfos()` and `filter_safe_zipinfos()` validate archive member paths against the process current working directory (CWD) instead of the actual extraction destination. When the process runs with CWD set to `/`, which is common in Docker containers, CI/CD runners, and Jupyter environments, the validation boundary become | 8.1 | 0.45% | 2026-06-11 | 2026-06-29 |
| CVE-2026-0847 | A vulnerability in NLTK versions up to and including 3.9.2 allows arbitrary file read via path traversal in multiple CorpusReader classes, including WordListCorpusReader, TaggedCorpusReader, and BracketParseCorpusReader. These classes fail to properly sanitize or validate file paths, enabling attackers to traverse directories and access sensitive files on the server. This issue is particularly critical in scenarios where user-controlled file inputs are processed, such as in machine learning APIs | 7.5 | 0.92% | 2026-03-04 | 2026-06-29 |
| CVE-2026-0846 | A vulnerability in the `filestring()` function of the `nltk.util` module in nltk version 3.9.2 allows arbitrary file read due to improper validation of input paths. The function directly opens files specified by user input without sanitization, enabling attackers to access sensitive system files by providing absolute paths or traversal paths. This vulnerability can be exploited locally or remotely, particularly in scenarios where the function is used in web APIs or other interfaces that accept u | 7.5 | 0.36% | 2026-03-09 | 2026-06-29 |
| CVE-2026-0545 | In mlflow/mlflow, the FastAPI job endpoints under `/ajax-api/3.0/jobs/*` are not protected by authentication or authorization when the `basic-auth` app is enabled. This vulnerability affects the latest version of the repository. If job execution is enabled (`MLFLOW_SERVER_ENABLE_JOB_EXECUTION=true`) and any job function is allowlisted, any network client can submit, read, search, and cancel jobs without credentials, bypassing basic-auth entirely. This can lead to unauthenticated remote code exec | 9.8 | 4.39% | 2026-04-03 | 2026-06-29 |
| CVE-2025-15381 | In the latest version of mlflow/mlflow, when the `basic-auth` app is enabled, tracing and assessment endpoints are not protected by permission validators. This allows any authenticated user, including those with `NO_PERMISSIONS` on the experiment, to read trace information and create assessments for traces they should not have access to. This vulnerability impacts confidentiality by exposing trace metadata and integrity by allowing unauthorized creation of assessments. Deployments using `mlflow | 7.1 | 0.32% | 2026-03-27 | 2026-06-29 |
| CVE-2025-15379 | A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deplo | 9.8 | 1.99% | 2026-03-30 | 2026-06-29 |
| CVE-2025-15036 | A path traversal vulnerability exists in the `extract_archive_to_dir` function within the `mlflow/pyfunc/dbconnect_artifact_cache.py` file of the mlflow/mlflow repository. This vulnerability, present in versions before v3.7.0, arises due to the lack of validation of tar member paths during extraction. An attacker with control over the tar.gz file can exploit this issue to overwrite arbitrary files or gain elevated privileges, potentially escaping the sandbox directory in multi-tenant or shared c | 10.0 | 0.59% | 2026-03-29 | 2026-06-29 |
| CVE-2025-15031 | A vulnerability in MLflow's pyfunc extraction process allows for arbitrary file writes due to improper handling of tar archive entries. Specifically, the use of `tarfile.extractall` without path validation enables crafted tar.gz files containing `..` or absolute paths to escape the intended extraction directory. This issue affects the latest version of MLflow and poses a high/critical risk in scenarios involving multi-tenant environments or ingestion of untrusted artifacts, as it can lead to arb | 9.1 | 0.85% | 2026-03-18 | 2026-06-29 |
| CVE-2025-14287 | A command injection vulnerability exists in mlflow/mlflow versions before v3.7.0, specifically in the `mlflow/sagemaker/__init__.py` file at lines 161-167. The vulnerability arises from the direct interpolation of user-supplied container image names into shell commands without proper sanitization, which are then executed using `os.system()`. This allows attackers to execute arbitrary commands by supplying malicious input through the `--container` parameter of the CLI. The issue affects environme | 8.8 | 1.46% | 2026-03-16 | 2026-06-29 |
| CVE-2025-14009 | A critical vulnerability exists in the NLTK downloader component of nltk/nltk, affecting all versions. The _unzip_iter function in nltk/downloader.py uses zipfile.extractall() without performing path validation or security checks. This allows attackers to craft malicious zip packages that, when downloaded and extracted by NLTK, can execute arbitrary code. The vulnerability arises because NLTK assumes all downloaded packages are trusted and extracts them without validation. If a malicious package | 8.8 | 0.79% | 2026-02-18 | 2026-06-29 |
| CVE-2025-11157 | A high-severity remote code execution vulnerability exists in feast-dev/feast version 0.53.0, specifically in the Kubernetes materializer job located at `feast/sdk/python/feast/infra/compute_engines/kubernetes/main.py`. The vulnerability arises from the use of `yaml.load(..., Loader=yaml.Loader)` to deserialize `/var/feast/feature_store.yaml` and `/var/feast/materialization_config.yaml`. This method allows for the instantiation of arbitrary Python objects, enabling an attacker with the ability t | 7.8 | 0.32% | 2026-01-01 | 2026-06-29 |
| CVE-2026-2651 | A vulnerability in MLflow versions <=3.10.1.dev0 allows unauthorized access to multipart upload (MPU) endpoints when the `--serve-artifacts` mode is enabled. The authorization logic does not enforce resource-level permission checks for `/mlflow-artifacts/mpu/*` endpoints, enabling attackers to overwrite artifacts belonging to other users. This can lead to unauthorized cross-user writes, model supply chain poisoning, and arbitrary code execution when compromised models are loaded. The issue is re | 9.0 | 0.34% | 2026-05-25 | 2026-06-27 |
| CVE-2026-2611 | In MLflow version 3.9.0, the MLflow Assistant feature introduced improper origin validation in its /ajax-api endpoints. This vulnerability allows a remote attacker to exploit cross-origin requests from a malicious webpage to interact with the MLflow Assistant running on a victim's local machine. By bypassing the loopback-only restriction, the attacker can modify the Assistant's configuration to enable full access, which in turn allows the execution of arbitrary commands via the Claude Code sub-a | 9.6 | 0.37% | 2026-05-19 | 2026-06-27 |