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| CVE | CVSS | EPSS | Vendor, product | Description | Modified |
|---|---|---|---|---|---|
| CVE-2025-58367 | 10.0 critical | 1.0% | no CPE yet | DeepDiff is a project focused on Deep Difference and search of any Python data. Versions 5.0.0 through 8.6.0 are vulnerable to class pollution via the Delta class constructor, and when combined with a gadget available in DeltaDiff, it can lead to Denial of Service and Remote Code Execution (via insecure Pickle deserialization) exploitation. The gadget available in DeepDiff allows `deepdiff.serialization.SAFE_TO_IMPORT` to be modified to allow dangerous classes such as posix.system, and then perform insecure Pickle deserialization via the Delta class. This potentially allows any Python code to be executed, given that the input to Delta is user-controlled. Depending on the application where DeepDiff is used, this can also lead to other vulnerabilities. This is fixed in version 8.6.1. | 18 Oct |
| CVE-2026-61539 | 10.0 critical | 1.0% | no CPE yet | Xinference is an inference API for running open-source, speech, and multimodal models. In 2.5.0 and earlier, Xinference passes attacker-influenced Llama3 tool-call output to eval() in xinference/model/llm/tool_parsers/llama3_tool_parser.py and xinference/model/llm/utils.py. Requests to /v1/chat/completions with a tools field flow through xinference/api/restful_api.py, xinference/model/llm/transformers/core.py, handle_chat_result_non_streaming(), and _post_process_completion() before extract_tool_calls() or _eval_llama3_chat_arguments() evaluates the model-generated Python expression. An unauthenticated remote attacker can influence that output through a crafted prompt and execute commands in the Xinference server process context. This issue is fixed in version 2.7.0. | 12 Oct |
| CVE-2026-45568 | 9.9 critical | 1.0% | netfoundry, zrok | zrok is software for sharing web services, files, and network resources. Prior to 2.0.3, zrok's Python SDK ProxyShare Flask proxy route accepts an absolute URL in the request path and passes it to urllib.parse.urljoin, allowing the requested path to replace the configured target host and causing requests.request to return a server-side response from an attacker-chosen URL. This issue is fixed in version 2.0.3. | Sat 24 Oct |
| CVE-2026-9135 | 9.9 critical | 1.0% | langflow | IBM Langflow OSS 1.0.0 through 1.10.0 Langflow versions up to 1.9.2 (commit 94981c443d4918517b9e8163d70fc598dc33a32d) contain a code injection vulnerability in the Policies component's ToolGuard integration that bypasses the allow_custom_components=false security control. The vulnerability exists because the validation mechanism only checks the main component source code in node_template["code"]["value"] but fails to validate dynamic CodeInput fields that store generated ToolGuard Python files. Attackers can embed malicious Python code in these unvalidated dynamic fields, which are persisted in Flow.data and later executed server-side when a guarded tool is invoked through the ToolGuard runtime. This allows authenticated users with flow creation privileges to achieve arbitrary Python code execution on the backend despite custom component restrictions. The vulnerability can be escalated through cross-tenant flow manipulation via the agentic MCP update_flow_component_field tool, which accepts attacker-controlled user_id parameters, enabling attackers to inject malicious code into victim users' flows. When combined with publicly accessible flows and specific misconfigurations (AUTO_LOGIN=true, NEW_USER_IS_ACTIVE=true), the attack can be conducted with reduced authentication requirements. | Sat 24 Oct |
| CVE-2026-8476 | 9.9 critical | 1.0% | langflow | IBM Langflow OSS 1.0.0 through 1.10.0 contain a critical remote code execution vulnerability in the disk-based caching mechanism. The AsyncDiskCache class uses Python's unsafe pickle.loads() function to deserialize cached objects from disk without validation, integrity verification, or authentication, enabling arbitrary code execution when malicious pickle payloads are processed. Attackers who can influence cached data through file system access, malicious workflow inputs, custom components, or API manipulation can achieve complete system compromise with the privileges of the Langflow server process. | Sat 24 Oct |
| CVE-2026-8481 | 9.9 critical | 1.0% | langflow | IBM Langflow OSS 1.0.0 through 1.10.0 contain a critical remote code execution vulnerability in the code validation API endpoint. The POST /api/v1/validate/code endpoint accepts user-supplied Python code and executes it directly using Python's built-in exec() function without sandboxing, input validation, or privilege restrictions, enabling any authenticated user to execute arbitrary system commands with the full privileges of the Langflow server process. | Sat 24 Oct |
| CVE-2026-73263 | 9.9 critical | 1.0% | no CPE yet | Prowler is a cloud security platform. Prior to 5.36.0, the Kubernetes provider connection test accepted kubeconfig_content containing a legacy gcp auth-provider with config.cmd-path and config.cmd-args because kubeconfig_contains_exec_auth in api/src/backend/api/v1/serializers.py checked only exec blocks, and POST /api/v1/providers/{id}/connection loaded it through config.load_kube_config_from_dict in prowler/providers/kubernetes/kubernetes_provider.py, causing kubernetes-python CommandTokenSource.token to run the attacker-supplied command through subprocess.Popen on the shared worker. This issue is fixed in version 5.36.0. | Sat 24 Oct |
| CVE-2026-96639 | 9.8 critical | 1.0% | python, pillow | Pillow is a Python imaging library. From 11.0.0 until 13.0.0, multi-frame loaders can retain an ImagingCore allocation created for a narrow frame mode while a later frame of the same dimensions changes the logical mode and decoder tiles to wider RGB or CMYK data. ImageFile.load_prepare() reuses the stale native storage because _im is non-null without verifying that its mode and size still match. Crafted PSD, MPO, DCX, or MIC frame transitions can then write wider pixels into the narrow allocation, causing native out-of-bounds writes and crashes. The MPO path can also cause a native over-read and, in demonstrated runtime-specific profiles, command execution. This issue is fixed in version 13.0.0. | Tue 27 Oct |
| CVE-2026-40288 | 9.8 critical | 1.0% | praison, praisonai, praisonaiagents | PraisonAI is a multi-agent teams system. In versions below 4.5.139 of PraisonAI and 1.5.140 of praisonaiagents, the workflow engine is vulnerable to arbitrary command and code execution through untrusted YAML files. When praisonai workflow run <file.yaml> loads a YAML file with type: job, the JobWorkflowExecutor in job_workflow.py processes steps that support run: (shell commands via subprocess.run()), script: (inline Python via exec()), and python: (arbitrary Python script execution)—all without any validation, sandboxing, or user confirmation. The affected code paths include action_run() in workflow.py and _exec_shell(), _exec_inline_python(), and _exec_python_script() in job_workflow.py. An attacker who can supply or influence a workflow YAML file (particularly in CI pipelines, shared repositories, or multi-tenant deployment environments) can achieve full arbitrary command execution on the host system, compromising the machine and any accessible data or credentials. This issue has been fixed in versions 4.5.139 of PraisonAI and 1.5.140 of praisonaiagents. | Mon 26 Oct |
| CVE-2026-41497 | 9.8 critical | 1.0% | praison, praisonai | PraisonAI is a multi-agent teams system. Prior to version 4.6.9, the fix for PraisonAI's MCP command handling does not add a command allowlist or argument validation to parse_mcp_command(), allowing arbitrary executables like bash, python, or /bin/sh with inline code execution flags to pass through to subprocess execution. This issue has been patched in version 4.6.9. | Mon 26 Oct |
| CVE-2026-44887 | 9.8 critical | 1.0% | no CPE yet | Pi.Alert is a WIFI / LAN intruder detector with web service monitoring. Prior to 2026-05-07, Pi.Alert's web-based configuration editor allows arbitrary Python code to be injected into pialert.conf. Since the background scan daemon loads this file via Python's exec(), injected code executes as the daemon process. With web protection disabled (the default configuration), no authentication is required, making this an unauthenticated Remote Code Execution vulnerability. This vulnerability is fixed in 2026-05-07. | Sun 25 Oct |
| CVE-2026-47391 | 9.8 critical | 1.0% | no CPE yet | PraisonAI is a multi-agent teams system. Prior to version 4.6.40, PraisonAI's first-party A2A server example exposes an unauthenticated A2A JSON-RPC endpoint and registers a `calculate(expression)` tool implemented with Python `eval()`. The example also binds to `0.0.0.0`. A remote unauthenticated attacker can send `message/send` to `/a2a`; the request reaches `agent.chat()`, and a real LLM can invoke the registered `calculate` tool. In testing with `gemini/gemini-2.5-flash-lite`, this resulted in arbitrary Python execution in the server process, confirmed by creation of a marker file from an unauthenticated HTTP request. The issue affects deployments following the official A2A example or similar unauthenticated public A2A deployments with unsafe tools. The default unauthenticated A2A surface also exposes task history and task cancellation APIs, increasing confidentiality and integrity impact. Version 4.6.40 patches the issue. | Sat 24 Oct |
| CVE-2026-31228 | 9.8 critical | 1.0% | no CPE yet | The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains a remote code execution vulnerability in its Kubeflow component. The robustness evaluation function for PyTorch models uses the unsafe eval() function to dynamically evaluate user-supplied strings for the LossFn and Optimizer parameters without any sanitization or security restrictions. An attacker can exploit this by providing a specially crafted string that contains arbitrary Python code, which will be executed when eval() is called, leading to complete compromise of the system running the ART evaluation. | 19 Oct |
| CVE-2026-31229 | 9.8 critical | 1.0% | no CPE yet | The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains an insecure deserialization vulnerability (CWE-502) in its Kubeflow component's model loading functionality. When loading model weights from a file (e.g., model.pt) during robustness evaluation, the code uses torch.load() without the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the Pickle module. An attacker can exploit this by uploading a maliciously crafted model file to an object storage location referenced by the pipeline, or by controlling the model_id parameter to point to such a file. When the pipeline loads the model, the malicious payload is executed, leading to remote code execution. | 19 Oct |
| CVE-2026-31230 | 9.8 critical | 1.0% | no CPE yet | The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains a command-line argument injection vulnerability in its Kubeflow component (robustness_evaluation_fgsm_pytorch.py). The script uses the unsafe eval() function to parse string values provided via the --clip_values and --input_shape command-line arguments. This allows an attacker to inject arbitrary Python code into these arguments, which will be executed when eval() is called. The vulnerability can be exploited remotely if an attacker can control these arguments (e.g., through pipeline configuration or automated scripts), leading to arbitrary code execution on the system running the ART evaluation. | 19 Oct |
| CVE-2026-31231 | 9.8 critical | 1.0% | no CPE yet | Cognee thru v0.4.0 contains a critical remote code execution vulnerability in its notebook cell execution API endpoint. The endpoint is designed to execute arbitrary Python code provided by the user, but it does so using the unsafe exec() function without any sandboxing, validation, or security controls. An attacker can exploit this by sending a specially crafted POST request containing malicious Python code to the execution endpoint. This leads to arbitrary code execution on the Cognee server with the privileges of the server process, allowing complete compromise of the system. | 19 Oct |
| CVE-2026-31237 | 9.8 critical | 1.0% | no CPE yet | The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) through its predict() method. When a user provides a dataset file path to the predict() method, the framework automatically determines the file format. If the file is a pickle (.pkl) file, it is loaded using pandas.read_pickle() without any validation or security restrictions. This allows the deserialization of arbitrary Python objects via the unsafe pickle module. A remote attacker can exploit this by providing a maliciously crafted pickle file, leading to arbitrary code execution on the system running the Ludwig prediction. | 19 Oct |
| CVE-2026-7304 | 9.8 critical | 1.0% | lmsys, sglang | SGLangs multimodal generation runtime is vulnerable to unauthenticated remote code execution when the --enable-custom-logit-processor option is enabled, as Python objects loaded via dill.loads() will be deserialized without validation. | 14 Oct |
| CVE-2025-65213 | 9.8 critical | 1.0% | mthreads, torch_musa | MooreThreads torch_musa through all versions contains an unsafe deserialization vulnerability in torch_musa.utils.compare_tool. The compare_for_single_op() and nan_inf_track_for_single_op() functions use pickle.load() on user-controlled file paths without validation, allowing arbitrary code execution. An attacker can craft a malicious pickle file that executes arbitrary Python code when loaded, enabling remote code execution with the privileges of the victim process. | 14 Oct |
| CVE-2025-66455 | 9.8 critical | 1.0% | no CPE yet | LMDeploy is a toolkit for compressing, deploying, and serving large language models. Starting in version 0.9.2 and prior to version 0.16.0, LMDeploy's PyTorch DistServe/PD-disaggregation control plane used `recv_pyobj()` to deserialize messages received through a ZeroMQ PULL socket. PyZMQ implements `recv_pyobj()` using Python pickle deserialization, which can execute arbitrary code while reconstructing an object. The peer address used by the receiver was supplied through the `POST /distserve/p2p_connect` HTTP endpoint. An attacker who could reach an affected DistServe API server could cause the server to connect to an attacker-controlled ZeroMQ endpoint and deserialize a crafted pickle payload. API-key authentication is not enabled unless the operator explicitly configures it. As a result, affected DistServe deployments without API keys allowed unauthenticated remote code execution with the privileges of the LMDeploy serving process. This issue affects the PyTorch backend when PD-disaggregation/DistServe is enabled. Ordinary deployments that do not use the affected disaggregated-serving path do not expose this data flow. The fix was released in LMDeploy 0.16.0. Users who cannot upgrade immediately should prevent untrusted clients from reaching `/distserve/*` endpoints, restrict the DistServe HTTP and ZeroMQ control planes to trusted cluster networks, configure API-key authentication, and block arbitrary outbound ZeroMQ connections from serving nodes. These measures reduce exposure but do not make pickle deserialization safe. | 14 Oct |
| CVE-2025-62373 | 9.8 critical | 1.0% | pipecat | Pipecat is an open-source Python framework for building real-time voice and multimodal conversational agents. Versions 0.0.41 through 0.0.93 have a vulnerability in `LivekitFrameSerializer` – an optional, non-default, undocumented frame serializer class (now deprecated) intended for LiveKit integration. The class's `deserialize()` method uses Python's `pickle.loads()` on data received from WebSocket clients without any validation or sanitization. This means that a malicious WebSocket client can send a crafted pickle payload to execute arbitrary code on the Pipecat server. The vulnerable code resides in `src/pipecat/serializers/livekit.py` (around line 73), where untrusted WebSocket message data is passed directly into `pickle.loads()` for deserialization. If a Pipecat server is configured to use LivekitFrameSerializer and is listening on an external interface (e.g. 0.0.0.0), an attacker on the network (or the internet, if the service is exposed) could achieve remote code execution (RCE) on the server by sending a malicious pickle payload. Version 0.0.94 contains a fix. Users of Pipecat should avoid or replace unsafe deserialization and improve network security configuration. The best mitigation is to stop using the vulnerable LivekitFrameSerializer altogether. Those who require LiveKit functionality should upgrade to the latest Pipecat version and switch to the recommended `LiveKitTransport` or another secure method provided by the framework. Additionally, always follow secure coding practices: never trust client-supplied data, and avoid Python pickle (or similar unsafe deserialization) in network-facing components. | 12 Oct |
| CVE-2026-70470 | 9.5 critical | 1.0% | flowiseai, flowise | Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, Flowise validatePythonCodeForDataFrame in packages/components/src/pythonCodeValidator.ts can be bypassed with Unicode homoglyph identifiers, allowing arbitrary Python execution inside Pyodide and full OS command execution on the Flowise host via Pyodide js module interop. The validator gates pyodide.runPythonAsync in packages/components/nodes/agents/CSVAgent/CSVAgent.ts and packages/components/nodes/agents/AirtableAgent/AirtableAgent.ts with an ASCII word-boundary blacklist. JavaScript regex word boundaries are ASCII-only, while Python 3 NFKC-normalizes identifiers at parse time, so homoglyph forms such as __cl𝐚ss__, __subcl𝐚sses__, __b𝐚se__, and __b𝐮iltins__ bypass the blacklist and are parsed as their ASCII equivalents. This issue is fixed in version 3.1.3. | Sat 24 Oct |
| CVE-2026-70477 | 9.5 critical | 1.0% | flowiseai, flowise | Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, a prompt injection sent to a chatflow using a CSV Agent node can cause the LLM to respond with a malicious Python script that bypasses the blocklist validator and executes in an unsandboxed Pyodide environment. The specific flaw exists within the run method of the CSV_Agents class, where untrusted data is used to construct an LLM prompt and the resulting pythonCode is validated by validatePythonCodeForDataFrame before execution. An attacker can leverage this to execute arbitrary code in the context of the service account. This issue is fixed in 3.1.3. | Sat 24 Oct |
| CVE-2026-115557 | 9.4 critical | 1.0% | no CPE yet | Python has added a denylist for known compromised certificates to the "ssl" module to ensure user safety even without certificate revocation configured. Known compromised certificates will automatically be rejected regardless of the SSLContext policy configuration. | Tue 27 Oct |
| CVE-2026-69256 | 9.4 critical | 1.0% | flowiseai, flowise | Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the CSVAgent node allowed users to provide Python code that is executed through pyodide; although a denylist blocked dangerous Python constructs, pandas.read_pickle() could deserialize a pickled payload and achieve code execution without matching the denied words. The affected file is flowise-components/nodes/agents/CSVAgent/CSVAgent.ts, where user-supplied customReadCSVFunc is evaluated as pd.${customReadCSVFunc}. An authenticated user who can create or modify a chatflow can add a CSV Agent, place a malicious read_pickle payload in the Additional Parameters, save the chatflow, and trigger /api/v1/prediction/<UUID> to execute commands. This issue is fixed in version 3.1.3. | Sat 24 Oct |
| CVE-2026-69264 | 9.4 critical | 1.0% | flowiseai, flowise | Prior to 3.1.3, Flowise CSVAgent interpolates an attacker-controlled segment of the csvFile data URI directly into a Python source-code template that is then executed by Pyodide. Because Pyodide is loaded with the default js bridge to globalThis, which on Node.js exposes eval and dynamic import, the attacker can break out of the Python string literal, hand a JavaScript string to js.eval, dynamically import Node built-in modules such as fs and child_process, and execute arbitrary file I/O or OS commands as the Flowise process. The two validator paths around this code, validatePythonCodeForDataFrame and validateCustomReadCSVFunction, are never applied to the bootstrap template. A workspace user with chatflows:create or agentflows/chatflows update permission can plant a CSV Agent node with a crafted csvFile; once the chatflow is exposed via POST /api/v1/prediction/:id, any unauthenticated request triggers host remote code execution. This issue is fixed in version 3.1.3. | Sat 24 Oct |
| CVE-2026-112408 | 9.4 critical | 1.0% | no CPE yet | Missing verification of source of a communication channel in the default_bucket() function in Amazon SageMaker Python SDK V3 before 3.10.0 and V2 before 2.257.3 might allow remote actors to achieve code execution in the target SageMaker execution environment and obtain IAM credentials via pre-creation of a predictably named S3 bucket that the SDK uses without ownership validation. To remediate this issue, users should upgrade to Amazon SageMaker Python SDK 3.10.0 (V3) or 2.257.3 (V2). | 22 Oct |
| CVE-2026-78683 | 9.4 critical | 1.0% | nltk | NLTK before 3.10.0 (affected versions <=3.9.4) contains an unsafe pickle deserialization vulnerability in the TransitionParser.parse() method (nltk/parse/transitionparser.py). The method calls pickle_load() with the default restricted=False, routing deserialization through WarningUnpickler, which does not override find_class() and therefore permits arbitrary class resolution. When an application loads an attacker-crafted model file, embedded pickle gadget chains execute arbitrary Python code with the privileges of the user running the application. NLTK provides a RestrictedUnpickler for safe deserialization, but it is not used by production code paths. Fixed in 3.10.0. | 12 Oct |
| CVE-2026-68770 | 9.3 critical | 1.0% | no CPE yet | sentence-transformers contains a security control bypass vulnerability that allows attackers to achieve arbitrary code execution by exploiting a logic flaw in the import_module_class helper within sentence_transformers/util/misc.py, where the guard condition includes an 'or os.path.exists(model_name_or_path)' clause that satisfies the trust gate whenever the supplied path exists on the local filesystem, regardless of the trust_remote_code=False argument. Attackers who can control or influence the contents of a model directory on disk can place malicious Python files such as modeling_*.py referenced via modules.json, causing the code to execute at import time when an application loads the model with SentenceTransformer(path, trust_remote_code=False), bypassing the documented security contract and achieving code execution within the loading process. | Fri 23 Oct |
| CVE-2026-77936 | 9.3 critical | 1.0% | no CPE yet | Letta through 0.16.8 ships a compose.yaml that does not enable LETTA_SERVER_SECURE, so the password middleware is never added and all API routes are unauthenticated, and it exposes a superuser PostgreSQL port with default credentials. Remote attackers can execute arbitrary Python via POST /v1/tools/run, manage /v1/admin users, or run OS commands via COPY PROGRAM. | 20 Oct |
| CVE-2026-77932 | 9.3 critical | 1.0% | no CPE yet | DB-GPT through 0.8.2 contains an unauthenticated remote code execution vulnerability because the /api/v1/chat/react-agent endpoint relies on a mock get_user_from_headers function that grants every caller the admin role. Unauthenticated attackers can send prompts that make the ReAct agent's unsandboxed code_interpreter and shell_interpreter tools run arbitrary Python or bash as root in the webserver container, including reaching the bundled database with default credentials. | 20 Oct |
| CVE-2026-107779 | 9.3 critical | 1.0% | no CPE yet | Dromara Skyeye through commit 003549ae5615bd114ba5bb8ddf6a8e8ead97c321 contains a missing authentication vulnerability in bundled xxl-job-admin JobInfoController endpoints annotated with @PermissionLimit(limit = false). Unauthenticated attackers can POST GLUE_SHELL, GLUE_PYTHON, or GLUE_POWERSHELL jobs with attacker-supplied glueSource to /jobinfo/addAndStart, executing commands on the executor host or stopping and deleting jobs. | 14 Oct |
| CVE-2026-107204 | 9.3 critical | 1.0% | no CPE yet | LMCache through 0.5.5 contains an unauthenticated remote code execution vulnerability that allows remote attackers to execute Python code by posting scripts to the /run_script endpoint. Attackers can recover real builtins through the injected FastAPI app object, bypassing the guarded __import__, to import os and run operating system commands as the LMCache process. | 8 Oct |
| CVE-2026-35002 | 9.3 critical | 1.0% | agno | Agno versions prior to 2.3.24 contain an arbitrary code execution vulnerability in the model execution component that allows attackers to execute arbitrary Python code by manipulating the field_type parameter passed to eval(). Attackers can influence the field_type value in a FunctionCall to achieve remote code execution. | 8 Oct |
| CVE-2026-41265 | 9.2 critical | 1.0% | flowiseai, flowise | Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, the specific flaw exists within the run method of the Airtable_Agents class. The issue results from the lack of proper sandboxing when evaluating an LLM generated python script. Using prompt injection techniques, an unauthenticated attacker with the ability to send prompts to a chatflow using the Airtable Agent node may convince an LLM to respond with a malicious python script that executes attacker controlled commands on the flowise server. This vulnerability is fixed in 3.1.0. | Mon 26 Oct |
| CVE-2026-112393 | 9.2 critical | 1.0% | python, pillow | Pillow is a Python imaging library. From 2.0.0 until 13.0.0, Pillow has a heap buffer overflow and stale-heap disclosure in _tiffWriteProc when saving compressed TIFF data through libtiff to a target without a usable fileno(), such as BytesIO. The callback sizes its allocation from the prior buffer size instead of the current write position, allowing an attacker-controlled out-of-line TIFF tag or retained ICC profile to be copied beyond the allocation after libtiff seeks forward. This overflow can crash the process and may allow code execution. Independently, unwritten alignment gaps in compressed TIFF output larger than 64 KiB can disclose stale heap bytes without a crafted tag. File paths and targets with real file descriptors are unaffected. This issue is fixed in version 13.0.0. | Mon 26 Oct |
| CVE-2026-13014 | 9.2 critical | 1.0% | no CPE yet | A vulnerability in Thales CERT "Suspicious" application =< 1.3.4 allows a remote and unauthenticated attacker to execute arbitrary code and arbitrarily overwrite writable application files—including Python modules, configuration files, cron inputs, and runtime artifacts—leading to a persistent denial of service, the potential compromise of application secrets or integrations, and root-level execution inside the Django application container. This vulnerability has been names "Matryoshka Mail". Thales PSIRT acknowledges and thanks Lucien Doustaly (aka wlayzz) for discovering and reporting this issue. | Sat 24 Oct |
| CVE-2026-69255 | 9.2 critical | 1.0% | flowiseai, flowise | Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.3, the CSVAgent in packages/components/nodes/agents/CSVAgent/CSVAgent.ts extracted attacker-controlled CSV data with file.split(',').pop() and interpolated it directly into executable Python as base64_string = "${base64String}" before calling Pyodide. The validatePythonCodeForDataFrame() denylist only checked later LLM-generated code and did not validate this initial code block. An authenticated attacker could inject a closing quote followed by Python code, use Pyodide's js bridge to load Node.js child_process, and execute arbitrary operating system commands as root in the Flowise container. This issue is fixed in version 3.1.3. | Sat 24 Oct |
| CVE-2026-115727 | 9.2 critical | 1.0% | no CPE yet | AgenticSeek before commit 409840c contains a remote code execution vulnerability because llm_server/app.py hardcodes Flask debug mode while binding to all interfaces. Attackers who reach the server port and obtain the derivable Werkzeug debugger PIN can execute Python code and operating system commands with llm_server privileges. | Fri 23 Oct |
| CVE-2026-96620 | 9.2 critical | 1.0% | no CPE yet | Claude Agent SDK is a Python SDK for Claude Code. Prior to 0.2.121, the resume option is passed to the Claude CLI as a separate token without validation, so a dash-leading value is parsed as an independent CLI flag. An attacker can inject the --mcp-config flag to define a stdio MCP server, causing arbitrary command execution at CLI startup outside the SDK permission controls. The issue is exploitable when an application passes untrusted input as the session ID to resume. This issue is fixed in version 0.2.121. | 21 Oct |
| CVE-2026-113613 | 9.2 critical | 1.0% | no CPE yet | FlexGet before 3.20.7 contains a path traversal vulnerability in the decompress plugin that allows remote attackers to write arbitrary files by supplying malicious archive member paths. Attackers can deliver zip or rar archives with ../ sequences or absolute paths through a feed, writing Python files into the plugins directory for code execution. | 21 Oct |
| CVE-2026-47731 | 9.1 critical | 1.0% | no CPE yet | The AMMOS Instrument Toolkit (Formerly the Bespoke Links to Instruments for Surface and Space (BLISS)) is a Python-based software suite developed to handle Ground Data System (GDS), Electronic Ground Support Equipment (EGSE), commanding, telemetry uplink/downlink, and sequencing for instrument and CubeSat Missions. In versions prior to 2.6.1 and in version 3.1.0, the Binary Stream Capture (BSC) component exposes an unauthenticated HTTP API for dynamically creating packet capture "handlers." Because the code blindly trusts path‑related form fields, a remote client can bypass the configured log root and direct BSC to log to arbitrary filesystem paths (path traversal / directory escape), and append attacker‑controlled data to those files, using the privileges of the`ait-bsc` process. There are two ways for a remote attacker to trigger this. First, if the attacker has access to the network where `ait-bsc` is deployed (a reason for that could be that the ports are publicly accessible), the payloads can be directly sent to the server to trigger the arbitrary file append. This type of attack is demonstrated in `python_poc.py`. Second, even if the attacker does not have direct access to the network because the software is running in a local network, it is possible to exploit this if a bad actor in that network opens an attacker-controlled website (which might be a website created by an attacker, or a third-party website compromised by the attacker). The browser javascript can automatically send the requests necessary to exploit this into the local network. This is even possible if the server is only accessible on `localhost`. This type of attack is demonstrated by `attacker_tcp.py` and `test1.html` (first launch the attacker TCP server, then start a webserver to host `test1.html`, for example using `python3 -m http.server 7000`, and open `test1.html`).This issue affects BSC (Binary Stream Capture) and usage of the ait-bsc server. This impacts AIT-Core versions before 3.1.1, from 2.x before 2.6.1. Users are recommended to upgrade to version 3.1.1 or 2.6.1. | Sat 24 Oct |
| CVE-2026-73485 | 9.0 critical | 1.0% | flowiseai, flowise | Flowise before 3.1.3 contains a code injection vulnerability in the Airtable Agent node that allows unauthenticated attackers to execute arbitrary Python code by bypassing the pythonCodeValidator blocklist through obfuscation techniques. Attackers can send crafted prompts to a chatflow using the Airtable Agent node to inject malicious Python code that executes in an unsandboxed pyodide environment with full access to the host operating system. | Sat 24 Oct |
| CVE-2026-73486 | 9.0 critical | 1.0% | flowiseai, flowise | Flowise before 3.1.3 contains a code injection vulnerability in the CSV Agent node's customReadCSV parameter that allows authenticated attackers to execute arbitrary Python code. The validator uses a static regex blocklist that can be bypassed through obfuscation techniques, enabling attackers to execute code in the unsandboxed pyodide environment with full system access. | Sat 24 Oct |
| CVE-2026-73487 | 9.0 critical | 1.0% | flowiseai, flowise | Flowise before 3.1.3 contains a regex-based Python code validator bypass in CSV and Airtable Agent nodes that allows unauthenticated attackers to inject malicious code via prompt injection. Attackers can exploit unblocked pandas functions like pd.read_json() to exfiltrate datasets, perform SSRF against internal services, or achieve code execution through the unauthenticated prediction API. | Sat 24 Oct |
| CVE-2025-12060 | 8.9 high | 1.0% | no CPE yet | The keras.utils.get_file API in Keras, when used with the extract=True option for tar archives, is vulnerable to a path traversal attack. The utility uses Python's tarfile.extractall function without the filter="data" feature. A remote attacker can craft a malicious tar archive containing special symlinks, which, when extracted, allows them to write arbitrary files to any location on the filesystem outside of the intended destination folder. This vulnerability is linked to the underlying Python tarfile weakness, identified as CVE-2025-4517. Note that upgrading Python to one of the versions that fix CVE-2025-4517 (e.g. Python 3.13.4) is not enough. One additionally needs to upgrade Keras to a version with the fix (Keras 3.12). | 19 Oct |
| CVE-2026-41138 | 8.8 high | 1.0% | flowiseai, flowise | Flowise is a drag & drop user interface to build a customized large language model flow. Prior to 3.1.0, there is a remote code execution vulnerability in AirtableAgent.ts caused by lack of input verification when using Pandas. The user’s input is directly applied to the question parameter within the prompt template and it is reflected to the Python code without any sanitization. This vulnerability is fixed in 3.1.0. | Mon 26 Oct |
| CVE-2026-44827 | 8.8 high | 1.0% | huggingface, diffusers | Diffusers is the a library for pretrained diffusion models. Prior to 0.38.0, diffusers 0.37.0 allows remote code execution without the trust_remote_code=True safeguard when loading pipelines from Hugging Face Hub repositories. The _resolve_custom_pipeline_and_cls function in pipeline_loading_utils.py performs string interpolation on the custom_pipeline parameter using f"{custom_pipeline}.py". When custom_pipeline is not supplied by the user, it defaults to None, which Python interpolates as the literal string "None.py". If an attacker publishes a Hub repository containing a file named None.py with a class that subclasses DiffusionPipeline, the file is automatically downloaded and executed during a standard DiffusionPipeline.from_pretrained() call with no additional keyword arguments. The trust_remote_code check in DiffusionPipeline.download() is bypassed because it evaluates custom_pipeline is not None as False (since the kwarg was never supplied), while the downstream code path that actually loads the module resolves the None value into a valid filename. An attacker can achieve silent arbitrary code execution by publishing a malicious model repository with a None.py file and a standard-looking model_index.json that references a legitimate pipeline class name, requiring only that a victim calls from_pretrained on the repository. This vulnerability is fixed in 0.38.0. | Mon 26 Oct |
| CVE-2026-13749 | 8.8 high | 1.0% | snowflake, snowflake_cli | Improper neutralization in the Snowpark annotation processor callback template in Snowflake CLI versions prior to 3.19 allowed arbitrary code execution during application bundling or deployment. An attacker could exploit this by supplying crafted project content that is interpolated into generated Python code, causing Snowflake CLI to execute attacker-controlled code in the local context of the user running the CLI. Successful exploitation requires the victim to run the relevant bundling or deployment workflow against attacker-controlled project content, and any resulting code runs with the privileges of that local execution context. The fix is available in Snowflake CLI version 3.19, and users must manually upgrade. | Sun 25 Oct |
| CVE-2026-14534 | 8.8 high | 1.0% | trailofbits, fickling | Trail of Bits fickling versions up to and including 0.1.10 do not include the Python standard library modules _posixsubprocess, site, and atexit in the UNSAFE_IMPORTS denylist (fickle.py). Because these modules are absent from the denylist, fickling's check_safety() function returns LIKELY_SAFE with zero findings for pickle payloads that invoke dangerous functions including _posixsubprocess.fork_exec (C-level process spawner capable of executing arbitrary binaries), site.execsitecustomize (executes arbitrary site customization code), and atexit._run_exitfuncs (triggers all registered exit handler callbacks). The fickling.load() API chains check_safety() into pickle.loads() as an explicit security gate; a LIKELY_SAFE verdict causes the payload to be deserialized and executed. This shares the same root cause as CVE-2026-22607 (cProfile), CVE-2025-67748 (pty), and CVE-2025-67747 (marshal/types). OvertlyBadEvals does not flag these modules because they are standard library imports. UnsafeImports does not flag them because they are not in the denylist. The UnusedVariables heuristic is defeated by the SETITEMS opcode pattern. | Sun 25 Oct |
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EPSS scores: 2026-10-28. NVD cursor: 2026-10-29 00:22. The News page shows only notable CVEs (KEV, your stack, new criticals, EPSS over 50%, or active exploitation per SSVC); this table has all of them.