CVE-2025-7647 Insecure Temporary File Handling in run-llama/llama_index

The llama-index-core package, up to version 0.12.44, contains a vulnerability in the getcachedir function where a predictable, hardcoded directory path /tmp/llamaindex is used on Linux systems without proper security controls. This vulnerability allows attackers on multi-user systems to steal...

CVE-2025-7647

CVE-2025-7647 affects llama-index-core up to version 0.12.44, with a vulnerability in get_cache_dir() that uses a predictable, hardcoded directory path (/tmp/llama_index) on Linux. On multi-user Linux systems, this insecure temporary directory can enable local attackers to steal proprietary model...

LlamaIndex 安全漏洞

LlamaIndex is a data framework for LLM applications from the LlamaIndex open source. A security vulnerability exists in LlamaIndex version 0.12.44 and earlier, which stems from the use of hard-coded paths and lack of security controls in the getcachedir function, which could lead to model stealin...

Attack and Defense Techniques in Large Language Models: a Survey and New Perspectives

Large Language Models LLMs have become central to numerous natural language processing tasks, but their vulnerabilities present significant security and ethical challenges. This systematic survey explores the evolving landscape of attack and defense techniques in LLMs. We classify attacks into...

SONNI: Secure Oblivious Neural Network Inference

In the standard privacy-preserving Machine learning as-a-service MLaaS model, the client encrypts data using homomorphic encryption and uploads it to a server for computation. The result is then sent back to the client for decryption. It has become more and more common for the computation to be...

Critical Flaws in Ollama AI Framework Could Enable DoS, Model Theft, and Poisoning

Cybersecurity researchers have disclosed six security flaws in the Ollama artificial intelligence AI framework that could be exploited by a malicious actor to perform various actions, including denial-of-service, model poisoning, and model theft. "Collectively, the vulnerabilities could allow an...

De-risk Generative AI: Enterprise TruRisk Platform Advances to Secure AI and LLM Workloads

As we stand at the frontier of technological innovation, artificial intelligence AI and large language models LLMs are reshaping industries, driving automation, enhancing customer experiences, optimizing processes, and unlocking business opportunities for modern enterprises. However, this rapid...

Google Expands Its Bug Bounty Program to Tackle Artificial Intelligence Threats

Google has announced that it's expanding its Vulnerability Rewards Program VRP to compensate researchers for finding attack scenarios tailored to generative artificial intelligence AI systems in an effort to bolster AI safety and security. "Generative AI raises new and different concerns than...

New Framework Released to Protect Machine Learning Systems From Adversarial Attacks

Microsoft, in collaboration with MITRE, IBM, NVIDIA, and Bosch, has released a new open framework that aims to help security analysts detect, respond to, and remediate adversarial attacks against machine learning ML systems. Called the Adversarial ML Threat Matrix, the initiative is an attempt to...

Cyberattacks against machine learning systems are more common than you think

Machine learning ML is making incredible transformations in critical areas such as finance, healthcare, and defense, impacting nearly every aspect of our lives. Many businesses, eager to capitalize on advancements in ML, have not scrutinized the security of their ML systems. Today, along with...

Cyberattacks against machine learning systems are more common than you think

Machine learning ML is making incredible transformations in critical areas such as finance, healthcare, and defense, impacting nearly every aspect of our lives. Many businesses, eager to capitalize on advancements in ML, have not scrutinized the security of their ML systems. Today, along with...