How Can We Effectively Use LLMs for Phishing Detection?: Evaluating the Effectiveness of Large Language Model-Based Phishing Detection Models

Large language models LLMs have emerged as a promising phishing detection mechanism, addressing the limitations of traditional deep learning-based detectors, including poor generalization to previously unseen websites and a lack of interpretability. However, LLMs' effectiveness for phishing...

One Signature, Multiple Payments: Demystifying and Detecting Signature Replay Vulnerabilities in Smart Contracts

Smart contracts have significantly advanced blockchain technology, and digital signatures are crucial for reliable verification of contract authority. Through signature verification, smart contracts can ensure that signers possess the required permissions, thus enhancing security and scalability...

Taught by the Flawed: How Dataset Insecurity Breeds Vulnerable AI Code

AI programming assistants have demonstrated a tendency to generate code containing basic security vulnerabilities. While developers are ultimately responsible for validating and reviewing such outputs, improving the inherent quality of these generated code snippets remains essential. A key...

StyleBreak: Revealing Alignment Vulnerabilities in Large Audio-Language Models Via Style-Aware Audio Jailbreak

Large Audio-language Models LAMs have recently enabled powerful speech-based interactions by coupling audio encoders with Large Language Models LLMs. However, the security of LAMs under adversarial attacks remains underexplored, especially through audio jailbreaks that craft malicious audio promp...

EUVD-2025-106750

A vulnerability has been identified in LOGO! 12/24RCE 6ED1052-1MD08-0BA2 All versions, LOGO! 12/24RCEo 6ED1052-2MD08-0BA2 All versions, LOGO! 230RCE 6ED1052-1FB08-0BA2 All versions, LOGO! 230RCEo 6ED1052-2FB08-0BA2 All versions, LOGO! 24CE 6ED1052-1CC08-0BA2 All versions, LOGO! 24CEo...

Cisco Finds Open-Weight AI Models Easy to Exploit in Long Chats

Cisco’s new research shows that open-weight AI models, while driving innovation, face serious security risks as multi-turn attacks, including conversational persistence, can bypass safeguards and expose data...

PT-2025-46543

Name of the Vulnerable Software and Affected Versions LOGO! 12/24RCE 6ED1052-1MD08-0BA2 affected versions not specified LOGO! 12/24RCEo 6ED1052-2MD08-0BA2 affected versions not specified LOGO! 230RCE 6ED1052-1FB08-0BA2 affected versions not specified LOGO! 230RCEo 6ED1052-2FB08-0BA2 affected...

Siemens LOGO! 访问控制错误漏洞

Siemens LOGO! is a programmable logic controller from Siemens Germany. An access control error vulnerability exists in Siemens LOGO! that arises from the absence of certain authentication, which could allow an unauthenticated, remote attacker to alter the device's time, which could in turn affect...

From LLMs to Agents: A Comparative Evaluation of LLMs and LLM-Based Agents in Security Patch Detection

The widespread adoption of open-source software OSS has accelerated software innovation but also increased security risks due to the rapid propagation of vulnerabilities and silent patch releases. In recent years, large language models LLMs and LLM-based agents have demonstrated remarkable...

Publish Your Threat Models! the Benefits Far Outweigh the Dangers

Threat modeling has long guided software development work, and we consider how Public Threat Models PTM can convey useful security information to others. We list some early adopter precedents, explain the many benefits, address potential objections, and cite regulatory drivers. Internal threat...

NVIDIA Megatron-LM 代码注入漏洞

NVIDIA Megatron-LM is a PyTorch-based distributed training framework from NVIDIA that is specifically designed for training large Transformer language models. NVIDIA Megatron-LM suffers from a code injection vulnerability that stems from scripts improperly handling malicious data, which could lea...

DrAttack

DrAttack: Prompt Decomposition and Reconstruction Makes Powerf...

JPRO: Automated Multimodal Jailbreaking Via Multi-Agent Collaboration Framework

The widespread application of large VLMs makes ensuring their secure deployment critical. While recent studies have demonstrated jailbreak attacks on VLMs, existing approaches are limited: they require either white-box access, restricting practicality, or rely on manually crafted patterns, leadin...

EASE: Practical and Efficient Safety Alignment for Small Language Models

Small language models SLMs are increasingly deployed on edge devices, making their safety alignment crucial yet challenging. Current shallow alignment methods that rely on direct refusal of malicious queries fail to provide robust protection, particularly against adversarial jailbreaks. While...

KG-DF: A Black-Box Defense Framework against Jailbreak Attacks Based on Knowledge Graphs

With the widespread application of large language models LLMs in various fields, the security challenges they face have become increasingly prominent, especially the issue of jailbreak. These attacks induce the model to generate erroneous or uncontrolled outputs through crafted inputs, threatenin...

Microsoft Uncovers 'Whisper Leak' Attack That Identifies AI Chat Topics in Encrypted Traffic

Microsoft has disclosed details of a novel side-channel attack targeting remote language models that could enable a passive adversary with capabilities to observe network traffic to glean details about model conversation topics despite encryption protections under certain circumstances. This...

CVE-2020-36870 Ruijie Gateway EG & NBR Models v11.1(6)B9P1 - 11.9(4)B12P1 RCE

Various Ruijie Gateway EG and NBR models firmware versions 11.16B9P1 11.94B12P1 contain a code execution vulnerability in the EWEB management system that can be abused via front-end functionality. Attackers can exploit front-end code when features such as guest authentication, local server...

​​Whisper Leak: A novel side-channel attack on remote language models

Microsoft has discovered a new type of side-channel attack on remote language models. This type of side-channel attack could allow a cyberattacker a position to observe your network traffic to conclude language model conversation topics, despite being end-to-end encrypted via Transport Layer...

​​Whisper Leak: A novel side-channel attack on remote language models

Microsoft has discovered a new type of side-channel attack on remote language models. This type of side-channel attack could allow a cyberattacker a position to observe your network traffic to conclude language model conversation topics, despite being end-to-end encrypted via Transport Layer...

[SECURITY] Fedora 42 Update: GeographicLib-2.5.2-1.fc42

GeographicLib is a small set of C++ classes for performing conversions between geographic, UTM, UPS, MGRS, geocentric, and local Cartesian coordinates, for gravity e.g., EGM2008, geoid height and geomagnetic field e.g., WMM2010 calculations, and for solving geodesic problems. The emphasis is on...