Breaking Android with AI: a Deep Dive into LLM-Powered Exploitation

The rapid evolution of Artificial Intelligence AI and Large Language Models LLMs has opened up new opportunities in the area of cybersecurity, especially in the exploitation automation landscape and penetration testing. This study explores Android penetration testing automation using LLM-based...

PT-2025-36947

Name of the Vulnerable Software and Affected Versions: Calix GigaCenter ONT versions 844E Calix GigaCenter ONT versions 844G Calix GigaCenter ONT versions 844GE Calix GigaCenter ONT versions 854GE Calix GigaCenter ONT versions 812G Calix GigaCenter ONT versions 813G Calix GigaCenter ONT versions...

Calix GigaCenter ONT Series 安全漏洞

Calix GigaCenter ONT Series is a series of optical network terminals from Calix USA. A security vulnerability exists in the Calix GigaCenter ONT Series that originates from a common user being able to abuse elevated privileges. The following products and versions are affected: GigaCenter ONT 844E...

PatchSeeker: Mapping NVD Records to Their Vulnerability-Fixing Commits with LLM Generated Commits and Embeddings

Software vulnerabilities pose serious risks to modern software ecosystems. While the National Vulnerability Database NVD is the authoritative source for cataloging these vulnerabilities, it often lacks explicit links to the corresponding Vulnerability-Fixing Commits VFCs. VFCs encode precise code...

LLMs in Cybersecurity: Friend or Foe in the Human Decision Loop?

Large Language Models LLMs are transforming human decision-making by acting as cognitive collaborators. Yet, this promise comes with a paradox: while LLMs can improve accuracy, they may also erode independent reasoning, promote over-reliance and homogenize decisions. In this paper, we investigate...

Mask-GCG: Are All Tokens in Adversarial Suffixes Necessary for Jailbreak Attacks?

Jailbreak attacks on Large Language Models LLMs have demonstrated various successful methods whereby attackers manipulate models into generating harmful responses that they are designed to avoid. Among these, Greedy Coordinate Gradient GCG has emerged as a general and effective approach that...

PT-2025-36532

Name of the Vulnerable Software and Affected Versions: MONAI versions up to and including 1.5.0 Description: MONAI is an AI toolkit for health care imaging. The software contains insecure model loading methods that can trigger a deserialization vulnerability, potentially leading to code execution...

Multimodal Prompt Injection Attacks: Risks and Defenses for Modern LLMs

Large Language Models LLMs have seen rapid adoption in recent years, with industries increasingly relying on them to maintain a competitive advantage. These models excel at interpreting user instructions and generating human-like responses, leading to their integration across diverse domains,...

CVE-2025-35452 Pan-Tilt-Zoom cameras default administrative credentials for web interface

PTZOptics and possibly other ValueHD-based pan-tilt-zoom cameras use default, shared credentials for the administrative web interface...

CVE-2025-35452

PTZOptics and ValueHD-based PTZ cameras are affected by an insufficient authentication issue affecting the administrative web interface. The vulnerability stems from default, shared credentials and weak access controls for the /cgi-bin/param.cgi path, enabling remote, unauthenticated access to se...

Behind the Mask: Benchmarking Camouflaged Jailbreaks in Large Language Models

Large Language Models LLMs are increasingly vulnerable to a sophisticated form of adversarial prompting known as camouflaged jailbreaking. This method embeds malicious intent within seemingly benign language to evade existing safety mechanisms. Unlike overt attacks, these subtle prompts exploit...

Between a Rock and a Hard Place: Exploiting Ethical Reasoning to Jailbreak LLMs

Large language models LLMs have undergone safety alignment efforts to mitigate harmful outputs. However, as LLMs become more sophisticated in reasoning, their intelligence may introduce new security risks. While traditional jailbreak attacks relied on singlestep attacks, multi-turn jailbreak...

Breaking to Build: a Threat Model of Prompt-Based Attacks for Securing LLMs

The proliferation of Large Language Models LLMs has introduced critical security challenges, where adversarial actors can manipulate input prompts to cause significant harm and circumvent safety alignments. These prompt-based attacks exploit vulnerabilities in a model's design, training, and...

KubeGuard: LLM-Assisted Kubernetes Hardening Via Configuration Files and Runtime Logs Analysis

The widespread adoption of Kubernetes K8s for orchestrating cloud-native applications has introduced significant security challenges, such as misconfigured resources and overly permissive configurations. Failing to address these issues can result in unauthorized access, privilege escalation, and...

PT-2025-35657

Name of the Vulnerable Software and Affected Versions Dive versions 0.9.0 through 0.9.3 Description Dive is an open-source MCP Host Desktop Application that enables integration with function-calling LLMs. Versions 0.9.0 through 0.9.3 contain a Remote Code Execution RCE vulnerability triggered by ...

VulnRepairEval: an Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities

The adoption of Large Language Models LLMs for automated software vulnerability patching has shown promising outcomes on carefully curated evaluation sets. Nevertheless, existing datasets predominantly rely on superficial validation methods rather than exploit-based verification, leading to...

E-PhishGen: Unlocking Novel Research in Phishing Email Detection

Every day, our inboxes are flooded with unsolicited emails, ranging between annoying spam to more subtle phishing scams. Unfortunately, despite abundant prior efforts proposing solutions achieving near-perfect accuracy, the reality is that countering malicious emails still remains an unsolved...

Detecting Stealthy Data Poisoning Attacks in AI Code Generators

Deep learning DL models for natural language-to-code generation have become integral to modern software development pipelines. However, their heavy reliance on large amounts of data, often collected from unsanitized online sources, exposes them to data poisoning attacks, where adversaries inject...

Phoenix AXC F File Read Write Execute

The vulnerability of microprogrammed software in controllers such as Phoenix AXC F 1152, AXC F 2152, AXC F 3152, BPC 9102S, and RFC 4072S is related to incorrect definition of the reference before accessing the file. Exploiting this vulnerability can allow an attacker to gain read, write, or...

CVE-2025-9575 Linksys RE6250/RE6300/RE6350/RE6500/RE7000/RE9000 upload.cgi cgiMain os command injection

A vulnerability was determined in Linksys RE6250, RE6300, RE6350, RE6500, RE7000 and RE9000 1.0.013.001/1.0.04.001/1.0.04.002/1.1.05.003/1.2.07.001. This issue affects the function cgiMain of the file /cgi-bin/upload.cgi. Executing manipulation of the argument filename can lead to os command...