LLM Security and Safety: Insights from Homotopy-Inspired Prompt Obfuscation

In this study, we propose a homotopy-inspired prompt obfuscation framework to enhance understanding of security and safety vulnerabilities in Large Language Models LLMs. By systematically applying carefully engineered prompts, we demonstrate how latent model behaviors can be influenced in...

VulnResolver: A Hybrid Agent Framework for LLM-Based Automated Vulnerability Issue Resolution

As software systems grow in complexity, security vulnerabilities have become increasingly prevalent, posing serious risks and economic costs. Although automated detection tools such as fuzzers have advanced considerably, effective resolution still often depends on human expertise. Existing...

AJAR: Adaptive Jailbreak Architecture for Red-Teaming

As Large Language Models LLMs evolve from static chatbots into autonomous agents capable of tool execution, the landscape of AI safety is shifting from content moderation to action security. However, existing red-teaming frameworks remain bifurcated: they either focus on rigid, script-based text...

EUVD-2026-2708

SparkyFitness v0.15.8.2 is vulnerable to Cross Site Scripting XSS via user input and LLM output...

SparkyFitness security vulnerability

SparkyFitness is a fitness and health management platform developed by CodeWithCJ. Version SparkyFitness v0.15.8.2 contains a security vulnerability, which stems from improper handling of user input and LLM outputs, potentially leading to cross-site scripting attacks...

CVE-2025-65368

SparkyFitness v0.15.8.2 is vulnerable to Cross Site Scripting XSS via user input and LLM output...

Integrating APK Image and Text Data for Enhanced Threat Detection: A Multimodal Deep Learning Approach to Android Malware

As zero-day Android malware attacks grow more sophisticated, recent research highlights the effectiveness of using image-based representations of malware bytecode to detect previously unseen threats. However, existing studies often overlook how image type and resolution affect detection and ignor...

opencode 安全漏洞

opencode is an AI programming intelligence open-sourced by Anomaly. A security vulnerability exists in versions prior to opencode 1.1.10, which stems from the Markdown renderer not cleaning up the LLM response, and could lead to the execution of JavaScript via HTML injection...

PYSEC-2026-143

vLLM is an inference and serving engine for large language models LLMs. In versions from 0.6.4 to before 0.12.0, users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a specially crafted 1x1 pixel image. This causes a tensor dimensi...

PYSEC-2026-143

vLLM is an inference and serving engine for large language models LLMs. In versions from 0.6.4 to before 0.12.0, users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a specially crafted 1x1 pixel image. This causes a tensor dimensi...

PT-2026-2260

Name of the Vulnerable Software and Affected Versions vLLM versions 0.6.4 through 0.11.9 Description vLLM is an inference and serving engine for large language models LLMs. Users can cause the vLLM engine to crash when serving multimodal models that utilize the Idefics3 vision model implementatio...

CVE-2025-62327

In HCL DevOps Deploy 8.1.2.0 through 8.1.2.3, a user with LLM configuration privileges may be able to recover a credential previously saved for performing authenticated LLM Queries...

LLMs, You Can Evaluate It! Design of Multi-Perspective Report Evaluation for Security Operation Centers

Security operation centers SOCs often produce analysis reports on security incidents, and large language models LLMs will likely be used for this task in the near future. We postulate that a better understanding of how veteran analysts evaluate reports, including their feedback, can help produce...

Exploit for CVE-2025-68664

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Explainable AI Agents: Capture LLM Tool Call Reasoning with Spring AI

When building AI agents with tool calling capabilities, developers often need insights into why an LLM chose a particular tool—not just which tool it selected. Understanding the model's reasoning process is important for debugging, observability, and building trustworthy AI systems. Spring AI now...

ReGAIN: Retrieval-Grounded AI Framework for Network Traffic Analysis

Modern networks generate vast, heterogeneous traffic that must be continuously analyzed for security and performance. Traditional network traffic analysis systems, whether rule-based or machine learning-driven, often suffer from high false positives and lack interpretability, limiting analyst...

dify 安全漏洞

dify is an open source LLM application development platform from LangGenius Open Source. A security vulnerability exists in version 1.5.1 of dify that stems from default credentials and could lead to unauthorized access...

CVE-2025-14148

IBM UCD - IBM DevOps Deploy 8.1 through 8.1.2.3 could allow an authenticated user with LLM integration configuration privileges to recover a previously saved LLM API Token...

CVE-2025-14148 IBM DevOps Deploy is susceptible to a Insufficiently Protected Credentials vulnerability

IBM UCD - IBM DevOps Deploy 8.1 through 8.1.2.3 could allow an authenticated user with LLM integration configuration privileges to recover a previously saved LLM API Token...

Detecting Prompt Injection Attacks against Application Using Classifiers

Prompt injection attacks can compromise the security and stability of critical systems, from infrastructure to large web applications. This work curates and augments a prompt injection dataset based on the HackAPrompt Playground Submissions corpus and trains several classifiers, including LSTM,...