615 matches found
Neurosymbolic Learning for Advanced Persistent Threat Detection under Extreme Class Imbalance
The growing deployment of Internet of Things IoT devices in smart cities and industrial environments increases vulnerability to stealthy, multi-stage advanced persistent threats APTs that exploit wireless communication. Detection is challenging due to severe class imbalance in network traffic,...
CVE-2026-3071
Deserialization of untrusted data in the LanguageModel class of Flair from versions 0.4.1 to latest are vulnerable to arbitrary code execution when loading a malicious model...
CVE-2026-3071
The CVE concerns Flair’s LanguageModel class where deserialization of untrusted data in versions 0.4.1 to latest allows arbitrary code execution when loading a malicious model. The issue, with CVSSv3.1 metrics indicating HIGH severity (Local access, no user interaction, full scope and high confid...
PT-2026-22151
Name of the Vulnerable Software and Affected Versions Flair versions 0.4.1 through latest Description The deserialization of untrusted data in the LanguageModel class can lead to arbitrary code execution when loading a malicious model. Recommendations Versions prior to 0.4.1 are not affected. At...
flair 安全漏洞
Flair is a very simple and advanced NLP framework developed by Flair OpenSource. There are security vulnerabilities in Flair versions 0.4.1 onwards. These vulnerabilities stem from the LanguageModel class’s ability to deserialize untrusted data, which may allow arbitrary code to be executed when...
CVE-2026-25802
New API is a large language mode LLM gateway and artificial intelligence AI asset management system. Prior to version 0.10.8-alpha.9, a potential unsafe operation occurs in component MarkdownRenderer.jsx, allowing for Cross-Site ScriptingXSS when the model outputs items containing...
CVE-2026-25802
New API is a large language mode LLM gateway and artificial intelligence AI asset management system. Prior to version 0.10.8-alpha.9, a potential unsafe operation occurs in component MarkdownRenderer.jsx, allowing for Cross-Site ScriptingXSS when the model outputs items containing tag. Version...
CVE-2026-25802 New API has Potential XSS in its MarkdownRenderer component
New API is a large language mode LLM gateway and artificial intelligence AI asset management system. Prior to version 0.10.8-alpha.9, a potential unsafe operation occurs in component MarkdownRenderer.jsx, allowing for Cross-Site ScriptingXSS when the model outputs items containing tag. Version...
EUVD-2026-7452
New API is a large language mode LLM gateway and artificial intelligence AI asset management system. Prior to version 0.10.8-alpha.9, a potential unsafe operation occurs in component MarkdownRenderer.jsx, allowing for Cross-Site ScriptingXSS when the model outputs items containing tag. Version...
ICSSPulse: A Modular LLM-Assisted Platform for Industrial Control System Penetration Testing
It is well established that industrial control systems comprise the operational backbone of modern critical infrastructures, yet their increasing connectivity exposes them to cyber threats that are difficult to study and remedy safely under real-time operational conditions. In this paper, we...
How Exposed Endpoints Increase Risk Across LLM Infrastructure
As more organizations run their own Large Language Models LLMs, they are also deploying more internal services and Application Programming Interfaces APIs to support those models. Modern security risks are being introduced less from the models themselves and more from the infrastructure that...
FuzzySQL: Uncovering Hidden Vulnerabilities in DBMS Special Features with LLM-Driven Fuzzing
Traditional database fuzzing techniques primarily focus on syntactic correctness and general SQL structures, leaving critical yet obscure DBMS features, such as system-level modes e.g., GTID, programmatic constructs e.g., PROCEDURE, advanced process commands e.g., KILL, largely underexplored...
Evaluating the Reliability of Digital Forensic Evidence Discovered by Large Language Model: A Case Study
The growing reliance on AI-identified digital evidence raises significant concerns about its reliability, particularly as large language models LLMs are increasingly integrated into forensic investigations. This paper proposes a structured framework that automates forensic artifact extraction,...
LLM Scalability Risk for Agentic-AI and Model Supply Chain Security
Large Language Models LLMs & Generative AI are transforming cybersecurity, enabling both advanced defenses and new attacks. Organizations now use LLMs for threat detection, code review, and DevSecOps automation, while adversaries leverage them to produce malwares and run targeted social-engineeri...
Kestrel
Kestrel LLM-Assisted Bug Bounty Hunting Platform for Kali L...
Automatic, Expressive, and Scalable Fuzzing with Stitching
Fuzzing is a powerful technique for finding bugs in software libraries, but scaling it remains difficult. Automated harness generation commits to fixed API sequences at synthesis time, limiting the behaviors each harness can test. Approaches that instead explore new sequences dynamically lack the...
Meta patents AI that could keep you posting from beyond the grave
Tech bros have been wanting to become immortal for years. Until they get there, their fallback might be continuing to post nonsense on social media from the afterlife. On December 30, 2025, Meta was granted US patent 12513102B2: Simulation of a user of a social networking system using a language...
OpenClaw: Unsanitized CWD path injection into LLM prompts
Overview OpenClaw embedded the current working directory workspace path into the agent system prompt without sanitization. If an attacker can cause OpenClaw to run inside a directory whose name contains control/format characters for example newlines or Unicode bidi/zero-width markers, those...
Can Adversarial Code Comments Fool AI Security Reviewers -- Large-Scale Empirical Study of Comment-Based Attacks and Defenses against LLM Code Analysis
AI-assisted code review is widely used to detect vulnerabilities before production release. Prior work shows that adversarial prompt manipulation can degrade large language model LLM performance in code generation. We test whether similar comment-based manipulation misleads LLMs during...