CVE-2025-54950

An out-of-bounds access vulnerability in the loading of ExecuTorch models can cause the runtime to crash and potentially result in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit b6b7a16df5e7852d976d8c34c8a7e9a1b6f7d005...

CVE-2025-54949

CVE-2025-54949 describes a heap buffer overflow in ExecuTorch model loading, potentially enabling code execution or other destructive effects. Affected software: ExecuTorch prior to commit ede82493dae6d2d43f8c424e7be4721abe5242be. Public metrics list a CVSS v3.1 base score of 9.8 (CRITICAL) with ...

CVE-2025-54949

A heap buffer overflow vulnerability in the loading of ExecuTorch models can potentially result in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit ede82493dae6d2d43f8c424e7be4721abe5242be...

CVE-2025-54949

A heap buffer overflow vulnerability in the loading of ExecuTorch models can potentially result in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit ede82493dae6d2d43f8c424e7be4721abe5242be...

CVE-2025-30405

The CVE-2025-30405 entry describes an integer overflow in the loading of ExecuTorch models, causing objects to be placed outside their allocated memory. Affected software is ExecuTorch prior to commit 0830af8207240df8d7f35b984cdf8bc35d74fa73. Reported impact includes potential code execution or o...

CVE-2025-30405

An integer overflow vulnerability in the loading of ExecuTorch models can cause objects to be placed outside their allocated memory area, potentially resulting in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit 0830af8207240df8d7f35b984cdf8bc35d74fa73...

CVE-2025-30405

An integer overflow vulnerability in the loading of ExecuTorch models can cause objects to be placed outside their allocated memory area, potentially resulting in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit 0830af8207240df8d7f35b984cdf8bc35d74fa73...

CVE-2025-30405

An integer overflow vulnerability in the loading of ExecuTorch models can cause objects to be placed outside their allocated memory area, potentially resulting in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit 0830af8207240df8d7f35b984cdf8bc35d74fa73...

CVE-2025-30404

An integer overflow vulnerability in the loading of ExecuTorch models can cause overlapping allocations, potentially resulting in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit d158236b1dc84539c1b16843bc74054c9dcba006...

CVE-2025-30404

An integer overflow vulnerability in the loading of ExecuTorch models can cause overlapping allocations, potentially resulting in code execution or other undesirable effects. This issue affects ExecuTorch prior to commit d158236b1dc84539c1b16843bc74054c9dcba006...

PRvL: Quantifying the Capabilities and Risks of Large Language Models for PII Redaction

Redacting Personally Identifiable Information PII from unstructured text is critical for ensuring data privacy in regulated domains. While earlier approaches have relied on rule-based systems and domain-specific Named Entity Recognition NER models, these methods fail to generalize across formats...

PT-2025-32323

Name of the Vulnerable Software and Affected Versions ExecuTorch versions prior to commit cea9b23aa8ff78aff92829a466da97461cc7930c Description A group of related buffer overflow vulnerabilities in the loading of ExecuTorch models can cause the runtime to crash and potentially result in code...

PT-2025-32321

Name of the Vulnerable Software and Affected Versions ExecuTorch versions prior to commit ede82493dae6d2d43f8c424e7be4721abe5242be Description A heap buffer overflow exists in the loading of ExecuTorch models, potentially leading to code execution or other adverse outcomes. Recommendations Update...

AuthPrint: Fingerprinting Generative Models against Malicious Model Providers

Generative models are increasingly adopted in high-stakes domains, yet current deployments offer no mechanisms to verify the origin of model outputs. We address this gap by extending model fingerprinting techniques beyond the traditional collaborative setting to one where the model provider may a...

From Learning to Unlearning: Biomedical Security Protection in Multimodal Large Language Models

The security of biomedical Multimodal Large Language Models MLLMs has attracted increasing attention. However, training samples easily contain private information and incorrect knowledge that are difficult to detect, potentially leading to privacy leakage or erroneous outputs after deployment. An...

Prompt Injection Vulnerability of Consensus Generating Applications in Digital Democracy

Large Language Models LLMs are gaining traction as a method to generate consensus statements and aggregate preferences in digital democracy experiments. Yet, LLMs may introduce critical vulnerabilities in these systems. Here, we explore the impact of prompt-injection attacks targeting consensus...

AWS VDP: AWS | Self Registration Internal LibreChat : Access to internal/proprietary LLMs

Issue Summary A LibreChat endpoint/UI is found to be accessible to the public Internet, with self registration for any non AWS/Amazon Corporate domains enabled, allowing an attacker to use a ChatGPT like UI to access multiple public models Example : Claude with the API access it has enabled, as...

When Good Sounds Go Adversarial: Jailbreaking Audio-Language Models with Benign Inputs

As large language models become increasingly integrated into daily life, audio has emerged as a key interface for human-AI interaction. However, this convenience also introduces new vulnerabilities, making audio a potential attack surface for adversaries. Our research introduces WhisperInject, a...

From Legacy to Standard: LLM-Assisted Transformation of Cybersecurity Playbooks into CACAO Format

Existing cybersecurity playbooks are often written in heterogeneous, non-machine-readable formats, which limits their automation and interoperability across Security Orchestration, Automation, and Response platforms. This paper explores the suitability of Large Language Models, combined with Prom...

BadBlocks: Low-Cost and Stealthy Backdoor Attacks Tailored for Text-To-Image Diffusion Models

In recent years,Diffusion models have achieved remarkable progress in the field of image generation.However,recent studies have shown that diffusion models are susceptible to backdoor attacks,in which attackers can manipulate the output by injecting covert triggers such as specific visual pattern...