DAVSP: Safety Alignment for Large Vision-Language Models Via Deep Aligned Visual Safety Prompt

Large Vision-Language Models LVLMs have achieved impressive progress across various applications but remain vulnerable to malicious queries that exploit the visual modality. Existing alignment approaches typically fail to resist malicious queries while preserving utility on benign ones effectivel...

CVE-2025-49619: Improper Neutralization of Special Elements Used in a Template Engine

Skyvern through 0.1.85 is vulnerable to server-side template injection SSTI in the Prompt field of workflow blocks such as the Navigation v2 Block. Improper sanitization of Jinja2 template input allows authenticated users to inject crafted expressions that are evaluated on the server, leading to...

CVE-2025-49619

Skyvern through 0.1.85 is vulnerable to server-side template injection SSTI in the Prompt field of workflow blocks such as the Navigation v2 Block. Improper sanitization of Jinja2 template input allows authenticated users to inject crafted expressions that are evaluated on the server, leading to...

Stealix: Model Stealing Via Prompt Evolution

Model stealing poses a significant security risk in machine learning by enabling attackers to replicate a black-box model without access to its training data, thus jeopardizing intellectual property and exposing sensitive information. Recent methods that use pre-trained diffusion models for data...

Sentinel: SOTA Model to Protect against Prompt Injections

Large Language Models LLMs are increasingly powerful but remain vulnerable to prompt injection attacks, where malicious inputs cause the model to deviate from its intended instructions. This paper introduces Sentinel, a novel detection model, qualifire/prompt-injection-sentinel, based on the...

CLSA-2025-1748945064 Fix CVE(s): CVE-2019-10206, CVE-2019-14856

SECURITY UPDATE: password prompt vulnerability from template expansion - debian/patches/CVE-2019-10206.patch: prevent templating of passwords from prompt to avoid special characters triggering it incorrectly - CVE-2019-10206 - debian/patches/CVE-2019-14856.patch: fix incomplete CVE-2019-10206 pat...

ATAG: AI-Agent Application Threat Assessment with Attack Graphs

Evaluating the security of multi-agent systems MASs powered by large language models LLMs is challenging, primarily because of the systems' complex internal dynamics and the evolving nature of LLM vulnerabilities. Traditional attack graph AG methods often lack the specific capabilities to model...

VPI-Bench: Visual Prompt Injection Attacks for Computer-Use Agents

Computer-Use Agents CUAs with full system access enable powerful task automation but pose significant security and privacy risks due to their ability to manipulate files, access user data, and execute arbitrary commands. While prior work has focused on browser-based agents and HTML-level attacks,...

Timing Side-channel Attacks

vllm is vulnerable to Timing side-channel attacks. The vulnerability is due to timing discrepancies during the prefill phase by the PageAttention mechanism reusing matching prefix chunks, which speeds up token generation and allows an attacker to infer prompt similarity or presence...

Browser is prompted to install Citrix Workspace lite.

Receiving prompt to install Citrix Workspace lite when accessing store URL When accessing workspace we see that as Citrix workspace lite However, the installed app is Citrix Workspace app...

SafeGenes: Evaluating the Adversarial Robustness of Genomic Foundation Models

Genomic Foundation Models GFMs, such as Evolutionary Scale Modeling ESM, have demonstrated significant success in variant effect prediction. However, their adversarial robustness remains largely unexplored. To address this gap, we propose SafeGenes: a framework for Secure analysis of genomic...

Security Concerns for Large Language Models: a Survey

Large Language Models LLMs such as GPT-4 and its recent iterations, Google's Gemini, Anthropic's Claude 3 models, and xAI's Grok have caused a revolution in natural language processing, but their capabilities also introduce new security vulnerabilities. In this survey, we provide a comprehensive...

Adversarial Threat Vectors and Risk Mitigation for Retrieval-Augmented Generation Systems

Retrieval-Augmented Generation RAG systems, which integrate Large Language Models LLMs with external knowledge sources, are vulnerable to a range of adversarial attack vectors. This paper examines the importance of RAG systems through recent industry adoption trends and identifies the prominent...

CVE-2025-5276

Versions of the package mcp-markdownify-server before 1.0.0 are vulnerable to Server-Side Request Forgery SSRF via the Markdownify.get function. An attacker can craft a prompt that, once accessed by the MCP host, can invoke the webpage-to-markdown, bing-search-to-markdown, and youtube-to-markdown...

PT-2025-23141

Name of the Vulnerable Software and Affected Versions: mcp-markdownify-server versions all Description: The issue allows an attacker to craft a prompt that, once accessed by the MCP host, will enable it to read arbitrary files from the host running the server via the get-markdown-file tool...

Important: thunderbird

Issue Overview: Through a series of popup and window.print calls, an attacker can cause a window to go fullscreen without the user seeing the notification prompt, resulting in potential user confusion or spoofing attacks. This vulnerability affects Firefox ESR 102.5, Thunderbird 102.5, and Firefo...

Hijacking Large Language Models Via Adversarial In-Context Learning

In-context learning ICL has emerged as a powerful paradigm leveraging LLMs for specific downstream tasks by utilizing labeled examples as demonstrations demos in the preconditioned prompts. Despite its promising performance, crafted adversarial attacks pose a notable threat to the robustness of...

PT-2025-23167 · Blackmagic Design · Davinci Resolve

Name of the Vulnerable Software and Affected Versions: DaVinci Resolve versions prior to the fixed version Description: The issue is related to the use of entitlement "com.apple.security.cs.disable-library-validation" and the lack of launch and library load constraints, allowing a local attacker...

GHSA-4QJH-9FV9-R85R Potential Timing Side-Channel Vulnerability in vLLM’s Chunk-Based Prefix Caching

This issue arises from the prefix caching mechanism, which may expose the system to a timing side-channel attack. Description When a new prompt is processed, if the PageAttention mechanism finds a matching prefix chunk, the prefill process speeds up, which is reflected in the TTFT Time to First...

Microsoft OneDrive File Picker Flaw Grants Apps Full Cloud Access — Even When Uploading Just One File

Cybersecurity researchers have discovered a security flaw in Microsoft's OneDrive File Picker that, if successfully exploited, could allow websites to access a user's entire cloud storage content, as opposed to just the files selected for upload via the tool. "This stems from overly broad OAuth...