A path traversal vulnerability exists in run-llama/llama_index versions 0.12.27 through 0.12.40, specifically within the `encode_image` function in `generic_utils.py`. This vulnerability allows an attacker to manipulate the `image_path` input to read arbitrary files on the server, including sensitive system files. The issue arises due to improper validation or sanitization of the file path, enabling path traversal sequences to access files outside the intended directory. The vulnerability is fixed in version 0.12.41.

llamaindex

A vulnerability in the ObsidianReader class of the run-llama/llama_index repository, specifically in version 0.12.27, allows for hardlink-based path traversal. This flaw permits attackers to bypass path restrictions and access sensitive system files, such as /etc/passwd, by exploiting hardlinks. The vulnerability arises from inadequate handling of hardlinks in the load_data() method, where the security checks fail to differentiate between real files and hardlinks. This issue is resolved in version 0.5.2.

llamaindex

The JSONReader in run-llama/llama_index versions 0.12.28 is vulnerable to a stack overflow due to uncontrolled recursive JSON parsing. This vulnerability allows attackers to trigger a Denial of Service (DoS) by submitting deeply nested JSON structures, leading to a RecursionError and crashing applications. The root cause is the unsafe recursive traversal design and lack of depth validation, which makes the JSONReader susceptible to stack overflow when processing deeply nested JSON. This impacts the availability of services, making them unreliable and disrupting workflows. The issue is resolved in version 0.12.38.

llamaindex

An XML Entity Expansion vulnerability, also known as a 'billion laughs' attack, exists in the sitemap parser of the run-llama/llama_index repository, specifically affecting version v0.12.21. This vulnerability allows an attacker to supply a malicious Sitemap XML, leading to a Denial of Service (DoS) by exhausting system memory and potentially causing a system crash. The issue is resolved in version v0.12.29.

llamaindex

A vulnerability in the `ObsidianReader` class of the run-llama/llama_index repository, versions 0.12.23 to 0.12.28, allows for arbitrary file read through symbolic links. The `ObsidianReader` fails to resolve symlinks to their real paths and does not validate whether the resolved paths lie within the intended directory. This flaw enables attackers to place symlinks pointing to files outside the vault directory, which are then processed as valid Markdown files, potentially exposing sensitive information.

llamaindex

A vulnerability in the ArxivReader class of the run-llama/llama_index repository, versions up to v0.12.22.post1, allows for MD5 hash collisions when generating filenames for downloaded papers. This can lead to data loss as papers with identical titles but different contents may overwrite each other, preventing some papers from being processed for AI model training. The issue is resolved in version 0.12.28.

llamaindex

A critical deserialization vulnerability exists in the run-llama/llama_index library's JsonPickleSerializer component, affecting versions v0.12.27 through v0.12.40. This vulnerability allows remote code execution due to an insecure fallback to Python's pickle module. JsonPickleSerializer prioritizes deserialization using pickle.loads(), which can execute arbitrary code when processing untrusted data. Attackers can exploit this by crafting malicious payloads to achieve full system compromise. The root cause includes an insecure fallback mechanism, lack of validation or safeguards, misleading design, and violation of Python security guidelines.

llamaindex

LLaMA-Factory is a tuning library for large language models. A remote code execution vulnerability was discovered in LLaMA-Factory versions up to and including 0.9.3 during the LLaMA-Factory training process. This vulnerability arises because the `vhead_file` is loaded without proper safeguards, allowing malicious attackers to execute arbitrary malicious code on the host system simply by passing a malicious `Checkpoint path` parameter through the `WebUI` interface. The attack is stealthy, as the victim remains unaware of the exploitation. The root cause is that the `vhead_file` argument is loaded without the secure parameter `weights_only=True`. Version 0.9.4 contains a fix for the issue.

hiyouga

llama.cpp is an inference of several LLM models in C/C++. Prior to version b5721, there is a signed vs. unsigned integer overflow in llama.cpp's tokenizer implementation (llama_vocab::tokenize) (src/llama-vocab.cpp:3036) resulting in unintended behavior in tokens copying size comparison. Allowing heap-overflowing llama.cpp inferencing engine with carefully manipulated text input during tokenization process. This issue has been patched in version b5721.

ggml

A vulnerability in the PDF scanning processes of ClamAV could allow an unauthenticated, remote attacker to cause a buffer overflow condition, cause a denial of service (DoS) condition, or execute arbitrary code on an affected device. This vulnerability exists because memory buffers are allocated incorrectly when PDF files are processed. An attacker could exploit this vulnerability by submitting a crafted PDF file to be scanned by ClamAV on an affected device. A successful exploit could allow the attacker to trigger a buffer overflow, likely resulting in the termination of the ClamAV scanning process and a DoS condition on the affected software. Although unproven, there is also a possibility that an attacker could leverage the buffer overflow to execute arbitrary code with the privileges of the ClamAV process.

clamav

A vulnerability in Universal Disk Format (UDF) processing of ClamAV could allow an unauthenticated, remote attacker to cause a denial of service (DoS) condition on an affected device. This vulnerability is due to a memory overread during UDF file scanning. An attacker could exploit this vulnerability by submitting a crafted file containing UDF content to be scanned by ClamAV on an affected device. A successful exploit could allow the attacker to terminate the ClamAV scanning process, resulting in a DoS condition on the affected software. For a description of this vulnerability, see the .

clamav · cisco

llama.cpp is an inference of several LLM models in C/C++. Prior to version b5662, an attacker‐supplied GGUF model vocabulary can trigger a buffer overflow in llama.cpp’s vocabulary‐loading code. Specifically, the helper _try_copy in llama.cpp/src/vocab.cpp: llama_vocab::impl::token_to_piece() casts a very large size_t token length into an int32_t, causing the length check (if (length < (int32_t)size)) to be bypassed. As a result, memcpy is still called with that oversized size, letting a malicious model overwrite memory beyond the intended buffer. This can lead to arbitrary memory corruption and potential code execution. This issue has been patched in version b5662.

ggml

Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') vulnerability in Renzo Tejada Libro de Reclamaciones y Quejas libro-de-reclamaciones-y-quejas allows SQL Injection.This issue affects Libro de Reclamaciones y Quejas: from n/a through <= 0.9.

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

An SQL injection vulnerability exists in the delete function of DuckDBVectorStore in run-llama/llama_index version v0.12.19. This vulnerability allows an attacker to manipulate the ref_doc_id parameter, enabling them to read and write arbitrary files on the server, potentially leading to remote code execution (RCE).

llamaindex

LLama-Index CLI version v0.12.20 contains an OS command injection vulnerability. The vulnerability arises from the improper handling of the `--files` argument, which is directly passed into `os.system`. An attacker who controls the content of this argument can inject and execute arbitrary shell commands. This vulnerability can be exploited locally if the attacker has control over the CLI arguments, and remotely if a web application calls the LLama-Index CLI with a user-controlled filename. This issue can lead to arbitrary code execution on the affected system.

llamaindex

Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability in ivanrojas Libro de Reclamaciones libro-de-reclamaciones allows Stored XSS.This issue affects Libro de Reclamaciones: from n/a through <= 1.0.1.

A vulnerability in the Ollama server version 0.5.11 allows a malicious user to cause a Denial of Service (DoS) attack by customizing the manifest content and spoofing a service. This is due to improper validation of array index access when downloading a model via the /api/pull endpoint, which can lead to a server crash.

ollama

A Denial of Service (DoS) vulnerability has been identified in the KnowledgeBaseWebReader class of the run-llama/llama_index project, affecting version ~ latest(v0.12.15). The vulnerability arises due to inappropriate secure coding measures, specifically the lack of proper implementation of the max_depth parameter in the get_article_urls function. This allows an attacker to exhaust Python's recursion limit through repeated function calls, leading to resource consumption and ultimately crashing the Python process.

llamaindex

LLama Factory enables fine-tuning of large language models. Prior to version 1.0.0, a critical vulnerability exists in the `llamafy_baichuan2.py` script of the LLaMA-Factory project. The script performs insecure deserialization using `torch.load()` on user-supplied `.bin` files from an input directory. An attacker can exploit this behavior by crafting a malicious `.bin` file that executes arbitrary commands during deserialization. This issue has been patched in version 1.0.0.

hiyouga

open-webui v0.5.16 is vulnerable to SSRF in routers/ollama.py in function verify_connection.

openwebui