vulnerability classified as problematic was found in chatchat-space Langchain-Chatchat up to 0.3.1. This vulnerability affects unknown code of the file /v1/files?purpose=assistants. The manipulation leads to path
vulnerability classified as critical has been found in chatchat-space Langchain-Chatchat up to 0.3.1. This affects the function upload_temp_docs of the file /knowledge_base/upload_temp_docs of the component Backend
vulnerability in langchain-core versions >=0.1.17,<0.1.53, >=0.2.0,<0.2.43, and >=0.3.0,<0.3.15 allows unauthorized users to read arbitrary files from the host file system. The issue arises from the ability
vulnerability in the GraphCypherQAChain class of langchain-ai/langchain version 0.2.5 allows for SQL injection through prompt injection. This vulnerability can lead to unauthorized data manipulation, data exfiltration, denial
path traversal vulnerability exists in the `getFullPath` method of langchain-ai/langchainjs version 0.2.5. This vulnerability allows attackers to save files anywhere in the filesystem, overwrite existing text files, read
vulnerability in the GraphCypherQAChain class of langchain-ai/langchainjs versions 0.2.5 and all versions with this class allows for prompt injection, leading to SQL injection. This vulnerability permits unauthorized data
vulnerability in the FAISS.deserialize_from_bytes function of langchain-ai/langchain allows for pickle deserialization of untrusted data. This can lead to the execution of arbitrary commands via the os.system
Server-Side Request Forgery (SSRF) vulnerability exists in the Web Research Retriever component of langchain-ai/langchain version 0.1.5. The vulnerability arises because the Web Research Retriever does not restrict
versions of the MLflow platform running version 2.5.0 or newer, enabling a maliciously uploaded Langchain AgentExecutor model to run arbitrary code on an end user’s system when interacted with
langchain-ai/langchain is vulnerable to path traversal due to improper limitation of a pathname to a restricted directory ('Path Traversal') in its LocalFileStore functionality. An attacker can leverage this
vulnerability in the langchain-ai/langchain repository allows for a Billion Laughs Attack, a type of XML External Entity (XXE) exploitation. By nesting multiple layers of entities within
Langchain through 0.0.155, prompt injection allows an attacker to force the service to retrieve data from an arbitrary URL, essentially providing SSRF and potentially injecting content into downstream tasks
LangChain before 0.0.317 allows SSRF via document_loaders/recursive_url_loader.py because crawling can proceed from an external server to an internal server
issue in LanChain-ai Langchain v.0.0.245 allows a remote attacker to execute arbitrary code via the evaluate function in the numexpr library
issue in langchain v.0.0.171 allows a remote attacker to execute arbitrary code via a JSON file to load_prompt. This is related to __subclasses__ or a template
issue in Harrison Chase langchain v.0.0.194 and before allows a remote attacker to execute arbitrary code via the from_math_prompt and from_colored_object_prompt functions
issue in LangChain v.0.0.231 allows a remote attacker to execute arbitrary code via the prompt parameter
issue in Harrison Chase langchain v.0.0.194 allows an attacker to execute arbitrary code via the python exec calls in the PALChain, affected functions include from_math_prompt and from_colored