Package Instance

RunGptLLM class in LlamaIndex has a command injection
A command injection vulnerability exists in the RunGptLLM class of the llama_index library, version 0.9.47, used by the RunGpt framework from JinaAI to connect to Language Learning Models (LLMs). The vulnerability arises from the improper use of the eval function, allowing a malicious or compromised LLM hosting provider to execute arbitrary commands on the client's machine. This issue was fixed in version 0.10.13. The exploitation of this vulnerability could lead to a hosting provider gaining full control over client machines.

llama-index-packs-finchat SQL Injection vulnerability
A vulnerability in the FinanceChatLlamaPack of the llama-index-packs-finchat package, versions up to v0.3.0, allows for SQL injection in the `run_sql_query` function of the `database_agent`. This vulnerability can be exploited by an attacker to inject arbitrary SQL queries, leading to remote code execution (RCE) through the use of PostgreSQL's large object functionality.

The issue is resolved by no longer officially supporting the package and moving it into the `stale_packages` branch on the repo, this removing it from documentation etc.

llama-index has Insecure Temporary File
The llama_index library version 0.12.33 sets the NLTK data directory to a subdirectory of the codebase by default, which is world-writable in multi-user environments. This configuration allows local users to overwrite, delete, or corrupt NLTK data files, leading to potential denial of service, data tampering, or privilege escalation. The vulnerability arises from the use of a shared cache directory instead of a user-specific one, making it susceptible to local data tampering and denial of service.

LlamaIndex vulnerable to Creation of Temporary File in Directory with Insecure Permissions
A vulnerability in the `default_jsonalyzer` function of the `JSONalyzeQueryEngine` in the run-llama/llama_index repository allows for SQL injection via prompt injection. This can lead to arbitrary file creation and Denial-of-Service (DoS) attacks. The vulnerability affects the latest version and is fixed in version 0.12.3.

LlamaIndex Improper Handling of Exceptional Conditions vulnerability
A vulnerability in the LangChainLLM class of the run-llama/llama_index repository, version v0.12.5, allows for a Denial of Service (DoS) attack. The stream_complete method executes the llm using a thread and retrieves the result via the get_response_gen method of the StreamingGeneratorCallbackHandler class. If the thread terminates abnormally before the _llm.predict is executed, there is no exception handling for this case, leading to an infinite loop in the get_response_gen function. This can be triggered by providing an input of an incorrect type, causing the thread to terminate and the process to continue running indefinitely.

llama_index vulnerable to SQL Injection
Multiple vector store integrations in run-llama/llama_index version v0.12.21 have SQL injection vulnerabilities. These vulnerabilities allow an attacker to read and write data using SQL, potentially leading to unauthorized access to data of other users depending on the usage of the llama-index library in a web application.

LlamaIndex vulnerable to data loss through hash collisions in its DocugamiReader class
A vulnerability in the DocugamiReader class of the run-llama/llama_index repository, up to but excluding version 0.12.41, involves the use of MD5 hashing to generate IDs for document chunks. This approach leads to hash collisions when structurally distinct chunks contain identical text, resulting in one chunk overwriting another. This can cause loss of semantically or legally important document content, breakage of parent-child chunk hierarchies, and inaccurate or hallucinated responses in AI outputs. The issue is resolved in version 0.3.1.