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Langflow: IDOR Vulnerability in `/api/v1/responses` Endpoint Allows Authenticated Attackers to Access Another User's Flow

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.1, an Insecure Direct Object Reference (IDOR) vulnerability in /api/v1/responses endpoint allows an authenticated attacker to execute any flow belonging to another user by specifying the victim's flow ID in the request. This vulnerability is fixed in 1.9.1.

• Auf 1.9.1 aktualisieren
• Auf 1.9.2 aktualisieren

Langflow: Logout button does not clear session

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.7.0, the logout button does not clear the session. The previous user stays logged in unless another user explicitly logs in. This vulnerability is fixed in 1.7.0.

• Auf 1.7.0 aktualisieren

Langflow: Unauthenticated DoS through multipart form boundary file upload

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.0.19, an attacker can send a /api/v1/files/upload/ request without any authentication token/cookies and abuse a very long multipart form boundary to make the langflow app unusable for all users for an indefinite amount of time. This vulnerability is fixed in 1.0.19.

• Auf 1.0.19 aktualisieren

Langflow: Unauthenticated RCE in Shareable Playgrounds

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.2, the "Shareable Playground" (or "Public Flows" in code) contains a critical RCE vulnerability. Shareable Playground feature works by enabling the execution of workflows by unauthenticated users, by accessing a link. Specifically, it enables the route /api/v1/build_public_tmp to execute any public flow, given a public flow ID. When the route executes the flow, it allows for providing arbitrary custom Python code as the nodes code, inside the JSON payload. The vulnerable field is data.nodes[X].data.node.template.code.value. This vulnerability is fixed

• Auf 1.9.2 aktualisieren

Langflow: BaseFileComponent-based nodes arbitrary file read with RCE exploit

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.2, by controlling a files that are digested into the RAG, an attacker can direct the node to read any file on the file-system by absolute path. All components based on BaseFileComponent are vulnerable to the vulnerability. This includes Docling (DoclingInlineComponent), Docling Serve, DoclingRemoteComponent), Read File (FileComponent), NVIDIA Retriever Extraction (NvidiaIngestComponent), Video File (VideoFileComponent), and Unstructured API (UnstructuredComponent). This vulnerability is fixed in 1.9.2.

• Auf 1.9.2 aktualisieren

Langflow: Unauthenticated file upload leads to DoS (space exhaustion) and information leak

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.1, unauthenticated users can upload any amount of data to the server without any limitations. No need for any prior knowledge, only network access to Langflow. This can lead to space exhaustion on the server. In addition, in the response, the absolute path of the uploaded file is reported to the attacker, which is an information leak that can assist in chaining other primitives. This vulnerability is fixed in 1.9.1.

• Auf 1.9.1 aktualisieren

yt-dlp: File Downloader cookie leak with curl

yt-dlp is a command-line audio/video downloader. From 2023.09.24 until 2026.06.09, if curl is used as an external downloader for yt-dlp, cookies may be leaked to an unintended host upon HTTP redirect or when the host for download fragments differs from their parent manifest's. At the file download stage, the cookies are passed by yt-dlp to the file downloader via --cookie. However, unless these are loaded from a file, this operation does not activate the cookie engine. As a result, curl will send cookies with requests to domains or paths for which the cookies are not scoped. This vulnerability is fixed in 2026.06.09.

• Auf 2026.06.09-1 aktualisieren
• Auf 2026.6.9 aktualisieren

yt-dlp: Arbitrary code execution via manifest downloads with aria2c

yt-dlp is a command-line audio/video downloader. Prior to 2026.06.09, if aria2c is used as an external downloader for a fragmented manifest format (such as an HLS/DASH stream), yt-dlp passes insufficiently sanitized input to aria2c that allows an attacker to perform an arbitrary file write. On Windows platforms, this can lead to immediate arbitrary code execution. On non-Windows platforms, this can lead to arbitrary code execution upon the next invocation of yt-dlp. This vulnerability is fixed in 2026.06.09.

• Auf 2026.06.09-1 aktualisieren
• Auf 2026.6.9 aktualisieren

yt-dlp: Dangerous file type creation via insufficient filename sanitization (Bypass of CVE-2024-38519)

yt-dlp is a command-line audio/video downloader. Prior to 2026.06.09, a vulnerability exists in yt-dlp that allows a remote attacker to write arbitrary OS-shortcut files (such as .desktop, .url, .webloc) to the user's filesystem, bypassing the remediation for CVE-2024-38519. The allowlist explicitly included the unsafe extensions .desktop, .url, and .webloc so that the functionality of the --write-link option (and its variants) could be preserved. These allowlist inclusions can be exploited by an attacker to write malicious OS-shortcut files in the context of a media or subtitles download. This vulnerability is fixed in 2026.06.09.

• Auf 2026.06.09-1 aktualisieren
• Auf 2026.6.9 aktualisieren

tarfile extraction filter bypass allows escaping the destination directory

tarfile.extractall() with the 'data' or 'tar' filter could be bypassed by a crafted archive where a hardlink references a symlink stored at a deeper name than the hardlink itself.  The extraction fallback validated the symlink at it's archived location but recreated it at the hardlink's shallower path, letting a relative target the filter judged contained escape the destination directory.  This allowed a malicious tar archive to create a symlink pointing outside the destination, enabling out-of-destination file reads or writes. This was an incomplete fix of CVE-2025-4330.

• Auf 3.10.21 aktualisieren
• Auf 3.11.16 aktualisieren
• Auf 3.12.14 aktualisieren
• Auf 3.13.15 aktualisieren
• Auf 3.13.15-1 aktualisieren
• Auf 3.13.5-2+deb13u5 aktualisieren
• Auf 3.14.7 aktualisieren
• Auf 3.14.7-1 aktualisieren
• Auf 3.15.0b4 aktualisieren
• Auf 8.0.0+dfsg-1 aktualisieren

OpenHarness - Prompt Injection via /issue and /pr_comments Slash Commands

OpenHarness /issue and /pr_comments slash commands lack remote_invocable=False protection, allowing remote channel senders to write attacker-controlled Markdown into project context files. Admitted remote attackers can inject malicious content into .openharness/issue.md and .openharness/pr_comments.md files, which are subsequently injected into runtime system prompts, persistently influencing local agent behavior.

OpenHarness - Cross-Session Disclosure via /resume and /summary Commands

OpenHarness ohmo gateway /resume and /summary slash commands default remote_invocable to True, allowing admitted remote senders to enumerate and load arbitrary session snapshots by ID. Attackers can exploit this to access victim snapshots containing private prompts, credentials, tool output, and file paths via shared gateway channels.

picklescan - Remote Code Execution via Unblocked Standard Library Modules

picklescan before 1.0.4 fails to block at least seven Python standard library modules (including uuid, _osx_support, _aix_support, _pyrepl.pager, and imaplib) exposing eight functions that provide direct arbitrary command execution. Attackers can craft malicious pickle files importing these unblocked modules to achieve remote code execution while bypassing picklescan's safety validation entirely.

• Auf 1.0.4 aktualisieren

Crawl4AI - Arbitrary File Write via output_path Symlink and TOCTOU

Crawl4AI before 0.8.8 contains an arbitrary file write vulnerability in the screenshot and PDF endpoints that allows unauthenticated attackers to write files outside the intended directory via symlink and time-of-check-time-of-use (TOCTOU) attacks on the output_path parameter. Remote attackers can exploit insufficient path validation and symlink following to achieve arbitrary file write and potential code execution on systems where the runtime user has write access to executable or cron locations.

• Auf 0.8.8 aktualisieren

picklescan - Arbitrary Code Execution via Undetected idlelib.autocomplete.AutoComplete.fetch_completions

picklescan before 0.0.29 fails to detect malicious pickle files using idlelib.autocomplete.AutoComplete.fetch_completions in reduce methods. Attackers can embed undetected code in pickle files that executes arbitrary commands when loaded by victims.

• Auf 0.0.29 aktualisieren

picklescan - Remote Code Execution via torch.jit.unsupported_tensor_ops.execWrapper

picklescan before 0.0.28 fails to detect malicious torch.jit.unsupported_tensor_ops.execWrapper function calls embedded in pickle files. Attackers can craft malicious pickle files that bypass picklescan detection and execute arbitrary code when loaded via pickle.load().

• Auf 0.0.28 aktualisieren

picklescan - Arbitrary Code Execution via numpy.f2py.crackfortran.myeval Detection Bypass

picklescan before 0.0.33 fails to detect malicious pickle files that invoke numpy.f2py.crackfortran.myeval function through the reduce method. Attackers can craft malicious pickle files embedding arbitrary code that evades picklescan detection and executes remote code when loaded.

• Auf 0.0.33 aktualisieren

picklescan - Remote Code Execution via Undetected profile.Profile.runctx

picklescan before 0.0.29 fails to detect the profile.Profile.runctx function when analyzing pickle files, allowing attackers to embed undetected malicious code. Remote attackers can craft malicious pickle files using profile.Profile.runctx in the reduce method to achieve remote code execution when the pickle file is loaded.

• Auf 0.0.29 aktualisieren

vLLM: Artifact Pin Decay in vLLM allows pinned deployments to load unpinned code, weights, and processors

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, vLLM's revision pinning controls do not consistently apply to all artifacts loaded for a model. A deployment that supplies --revision or --code-revision can still load dynamic code, GGUF files, image processors, retrieval side weights, or same-repository subfolder weights/config from an unpinned/default revision. This is a supply-chain integrity issue for pinned vLLM deployments. Operators can believe they are serving a reviewed model revision while vLLM resolves behavior-affecting nested or sibling artifacts outside that reviewed revision. This vulnera

• Auf 0.22.0 aktualisieren

vLLM: Security Check Bypass via assert Statement in Activation Function Loading Allows Arbitrary Code Execution

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, an assert-based security check in vLLM's activation function loading allows any unauthenticated attacker to achieve arbitrary code execution on the server by publishing a malicious HuggingFace model, when vLLM runs in Python optimized mode (python -O or PYTHONOPTIMIZE=1). This vulnerability is fixed in 0.22.0.

• Auf 0.22.0 aktualisieren