Open WebUI is a self-hosted artificial intelligence platform designed to operate entirely offline. Prior to 0.9.5, the validate_url() function in backend/open_webui/retrieval/web/utils.py only validates the initial URL submitted by the caller. The HTTP clients used downstream (sync requests, async aiohttp, langchain's WebBaseLoader) follow HTTP 3xx redirects by default and do not re-validate the redirect target against the private-IP / metadata-IP block list. Any authenticated user can therefore submit a public URL that 302-redirects to an internal address (e.g. 127.0.0.1, 169.254.169.254, RFC1918) and read the internal response body via the /api/v1/retrieval/process/web endpoint, the /api/v1/images/... endpoints, the /api/chat/completions endpoint with an image_url content part, and any other route that calls these helpers. This vulnerability is fixed in 0.9.5.

openwebui

A vulnerability was found in chatchat-space Langchain-Chatchat up to 0.3.1.3. The affected element is the function _get_file_id of the file libs/chatchat-server/chatchat/server/api_server/openai_routes.py of the component Uploaded File Handler. Performing a manipulation results in insufficiently random values. Access to the local network is required for this attack. The attack's complexity is rated as high. The exploitability is described as difficult. The exploit has been made public and could be used. The project was informed of the problem early through an issue report but has not responded yet.

A vulnerability has been found in chatchat-space Langchain-Chatchat up to 0.3.1.3. Impacted is the function files of the file libs/chatchat-server/chatchat/server/api_server/openai_routes.py of the component OpenAI-Compatible File Upload API. Such manipulation of the argument file.filename leads to time-of-check time-of-use. Access to the local network is required for this attack to succeed. The attack requires a high level of complexity. The exploitability is considered difficult. The exploit has been disclosed to the public and may be used. The project was informed of the problem early through an issue report but has not responded yet.

A flaw has been found in chatchat-space Langchain-Chatchat up to 0.3.1.3. This issue affects the function PIL.Image.tobytes of the file libs/chatchat-server/chatchat/webui_pages/dialogue/dialogue.py of the component Vision Chat Paste Image Handler. This manipulation of the argument paste_image.image_data causes use of weak hash. The attacker needs to be present on the local network. The attack is considered to have high complexity. The exploitability is assessed as difficult. The exploit has been published and may be used. The project was informed of the problem early through an issue report but has not responded yet.

A vulnerability was detected in chatchat-space Langchain-Chatchat up to 0.3.1.3. This vulnerability affects the function files/list_files/retrieve_file/retrieve_file_content/delete_file of the file libs/chatchat-server/chatchat/server/api_server/openai_routes.py of the component Compatible File Service. The manipulation results in missing authentication. The attacker must have access to the local network to execute the attack. The exploit is now public and may be used. The project was informed of the problem early through an issue report but has not responded yet.

LangChain is a framework for building agents and LLM-powered applications. Prior to 1.1.14, langchain-openai's _url_to_size() helper (used by get_num_tokens_from_messages for image token counting) validated URLs for SSRF protection and then fetched them in a separate network operation with independent DNS resolution. This left a TOCTOU / DNS rebinding window: an attacker-controlled hostname could resolve to a public IP during validation and then to a private/localhost IP during the actual fetch.

langchain

LangChain is a framework for building agents and LLM-powered applications. Prior to langchain-text-splitters 1.1.2, HTMLHeaderTextSplitter.split_text_from_url() validated the initial URL using validate_safe_url() but then performed the fetch with requests.get() with redirects enabled (the default). Because redirect targets were not revalidated, a URL pointing to an attacker-controlled server could redirect to internal, localhost, or cloud metadata endpoints, bypassing SSRF protections. The response body is parsed and returned as Document objects to the calling application code. Whether this constitutes a data exfiltration path depends on the application: if it exposes Document contents (or derivatives) back to the requester who supplied the URL, sensitive data from internal endpoints could be leaked. Applications that store or process Documents internally without returning raw content to the requester are not directly exposed to data exfiltration through this issue. This vulnerability is fixed in 1.1.2.

langchain

LangChain-ChatChat 0.3.1 contains a remote code execution vulnerability in its MCP STDIO server configuration and execution handling. A remote attacker can access the publicly exposed MCP management interface and configure an MCP STDIO server with attacker-controlled commands and arguments. When the MCP server is started and MCP is enabled for agent execution, subsequent agent activity triggers execution of arbitrary commands on the server. Successful exploitation allows arbitrary command execution within the context of the LangChain-ChatChat service.

LangChain is a framework for building agents and LLM-powered applications. Prior to 0.3.84 and 1.2.28, LangChain's f-string prompt-template validation was incomplete in two respects. First, some prompt template classes accepted f-string templates and formatted them without enforcing the same attribute-access validation as PromptTemplate. In particular, DictPromptTemplate and ImagePromptTemplate could accept templates containing attribute access or indexing expressions and subsequently evaluate those expressions during formatting. Second, f-string validation based on parsed top-level field names did not reject nested replacement fields inside format specifiers. In this pattern, the nested replacement field appears in the format specifier rather than in the top-level field name. As a result, earlier validation based on parsed field names did not reject the template even though Python formatting would still attempt to resolve the nested expression at runtime. This vulnerability is fixed in 0.3.84 and 1.2.28.

langchain

LangChain is a framework for building agents and LLM-powered applications. Prior to version 1.2.22, multiple functions in langchain_core.prompts.loading read files from paths embedded in deserialized config dicts without validating against directory traversal or absolute path injection. When an application passes user-influenced prompt configurations to load_prompt() or load_prompt_from_config(), an attacker can read arbitrary files on the host filesystem, constrained only by file-extension checks (.txt for templates, .json/.yaml for examples). This issue has been patched in version 1.2.22.

langchain

Langchain Helm Charts are Helm charts for deploying Langchain applications on Kubernetes. Prior to langchain-ai/helm version 0.12.71, a URL parameter injection vulnerability existed in LangSmith Studio that could allow unauthorized access to user accounts through stolen authentication tokens. The vulnerability affected both LangSmith Cloud and self-hosted deployments. Authenticated LangSmith users who clicked on a specially crafted malicious link would have their bearer token, user ID, and workspace ID transmitted to an attacker-controlled server. With this stolen token, an attacker could impersonate the victim and access any LangSmith resources or perform any actions the user was authorized to perform within their workspace. The attack required social engineering (phishing, malicious links in emails or chat applications) to convince users to click the crafted URL. The stolen tokens expired after 5 minutes, though repeated attacks against the same user were possible if they could be convinced to click malicious links multiple times. The fix in version 0.12.71 implements validation requiring user-defined allowed origins for the baseUrl parameter, preventing tokens from being sent to unauthorized servers. No known workarounds are available. Self-hosted customers must upgrade to the patched version.

langchain

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.8.0, the CSV Agent node in Langflow hardcodes `allow_dangerous_code=True`, which automatically exposes LangChain’s Python REPL tool (`python_repl_ast`). As a result, an attacker can execute arbitrary Python and OS commands on the server via prompt injection, leading to full Remote Code Execution (RCE). Version 1.8.0 fixes the issue.

langflow

LangChain is a framework for building LLM-powered applications. Prior to version 1.1.8, a redirect-based Server-Side Request Forgery (SSRF) bypass exists in `RecursiveUrlLoader` in `@langchain/community`. The loader validates the initial URL but allows the underlying fetch to follow redirects automatically, which permits a transition from a safe public URL to an internal or metadata endpoint without revalidation. This is a bypass of the SSRF protections introduced in 1.1.14 (CVE-2026-26019). Users should upgrade to `@langchain/community` 1.1.18, which validates every redirect hop by disabling automatic redirects and re-validating `Location` targets before following them. In this version, automatic redirects are disabled (`redirect: "manual"`), each 3xx `Location` is resolved and validated with `validateSafeUrl()` before the next request, and a maximum redirect limit prevents infinite loops.

langchain

@langchain/langgraph-checkpoint-redis is the Redis checkpoint and store implementation for LangGraph. A query injection vulnerability exists in the @langchain/langgraph-checkpoint-redis package's filter handling. The RedisSaver and ShallowRedisSaver classes construct RediSearch queries by directly interpolating user-provided filter keys and values without proper escaping. RediSearch has special syntax characters that can modify query behavior, and when user-controlled data contains these characters, the query logic can be manipulated to bypass intended access controls. This vulnerability is fixed in 1.0.2.

LangChain is a framework for building LLM-powered applications. Prior to 1.1.14, the RecursiveUrlLoader class in @langchain/community is a web crawler that recursively follows links from a starting URL. Its preventOutside option (enabled by default) is intended to restrict crawling to the same site as the base URL. The implementation used String.startsWith() to compare URLs, which does not perform semantic URL validation. An attacker who controls content on a crawled page could include links to domains that share a string prefix with the target, causing the crawler to follow links to attacker-controlled or internal infrastructure. Additionally, the crawler performed no validation against private or reserved IP addresses. A crawled page could include links targeting cloud metadata services, localhost, or RFC 1918 addresses, and the crawler would fetch them without restriction. This vulnerability is fixed in 1.1.14.

langchain

LangChain is a framework for building agents and LLM-powered applications. Prior to 1.2.11, the ChatOpenAI.get_num_tokens_from_messages() method fetches arbitrary image_url values without validation when computing token counts for vision-enabled models. This allows attackers to trigger Server-Side Request Forgery (SSRF) attacks by providing malicious image URLs in user input. This vulnerability is fixed in 1.2.11.

langchain

LangChain versions up to and including 0.3.1 contain a regular expression denial-of-service (ReDoS) vulnerability in the MRKLOutputParser.parse() method (libs/langchain/langchain/agents/mrkl/output_parser.py). The parser applies a backtracking-prone regular expression when extracting tool actions from model output. An attacker who can supply or influence the parsed text (for example via prompt injection in downstream applications that pass LLM output directly into MRKLOutputParser.parse()) can trigger excessive CPU consumption by providing a crafted payload, causing significant parsing delays and a denial-of-service condition.

langchain

LangChain is a framework for building LLM-powered applications. Prior to @langchain/core versions 0.3.80 and 1.1.8, and prior to langchain versions 0.3.37 and 1.2.3, a serialization injection vulnerability exists in LangChain JS's toJSON() method (and subsequently when string-ifying objects using JSON.stringify(). The method did not escape objects with 'lc' keys when serializing free-form data in kwargs. The 'lc' key is used internally by LangChain to mark serialized objects. When user-controlled data contains this key structure, it is treated as a legitimate LangChain object during deserialization rather than plain user data. This issue has been patched in @langchain/core versions 0.3.80 and 1.1.8, and langchain versions 0.3.37 and 1.2.3

langchain

LangChain is a framework for building agents and LLM-powered applications. Prior to versions 0.3.81 and 1.2.5, a serialization injection vulnerability exists in LangChain's dumps() and dumpd() functions. The functions do not escape dictionaries with 'lc' keys when serializing free-form dictionaries. The 'lc' key is used internally by LangChain to mark serialized objects. When user-controlled data contains this key structure, it is treated as a legitimate LangChain object during deserialization rather than plain user data. This issue has been patched in versions 0.3.81 and 1.2.5.

langchain

LangChain is a framework for building agents and LLM-powered applications. From versions 0.3.79 and prior and 1.0.0 to 1.0.6, a template injection vulnerability exists in LangChain's prompt template system that allows attackers to access Python object internals through template syntax. This vulnerability affects applications that accept untrusted template strings (not just template variables) in ChatPromptTemplate and related prompt template classes. This issue has been patched in versions 0.3.80 and 1.0.7.

A SQL injection vulnerability exists in the langchain-ai/langchain repository, specifically in the LangGraph's SQLite store implementation. The affected version is langgraph-checkpoint-sqlite 2.0.10. The vulnerability arises from improper handling of filter operators ($eq, $ne, $gt, $lt, $gte, $lte) where direct string concatenation is used without proper parameterization. This allows attackers to inject arbitrary SQL, leading to unauthorized access to all documents, data exfiltration of sensitive fields such as passwords and API keys, and a complete bypass of application-level security filters.

The HTMLSectionSplitter class in langchain-text-splitters version 0.3.8 is vulnerable to XML External Entity (XXE) attacks due to unsafe XSLT parsing. This vulnerability arises because the class allows the use of arbitrary XSLT stylesheets, which are parsed using lxml.etree.parse() and lxml.etree.XSLT() without any hardening measures. In lxml versions up to 4.9.x, external entities are resolved by default, allowing attackers to read arbitrary local files or perform outbound HTTP(S) fetches. In lxml versions 5.0 and above, while entity expansion is disabled, the XSLT document() function can still read any URI unless XSLTAccessControl is applied. This vulnerability allows remote attackers to gain read-only access to any file the LangChain process can reach, including sensitive files such as SSH keys, environment files, source code, or cloud metadata. No authentication, special privileges, or user interaction are required, and the issue is exploitable in default deployments that enable custom XSLT.