Prompt Optimization and Evaluation for LLM Automated Red Teaming

Applications that use Large Language Models LLMs are becoming widespread, making the identification of system vulnerabilities increasingly important. Automated Red Teaming accelerates this effort by using an LLM to generate and execute attacks against target systems. Attack generators are evaluat...

Strategic Deflection: Defending LLMs from Logit Manipulation

With the growing adoption of Large Language Models LLMs in critical areas, ensuring their security against jailbreaking attacks is paramount. While traditional defenses primarily rely on refusing malicious prompts, recent logit-level attacks have demonstrated the ability to bypass these safeguard...

ZIUM: Zero-Shot Intent-Aware Adversarial Attack on Unlearned Models

Machine unlearning MU removes specific data points or concepts from deep learning models to enhance privacy and prevent sensitive content generation. Adversarial prompts can exploit unlearned models to generate content containing removed concepts, posing a significant security risk. However,...

CVE-2025-54568

Akamai Rate Control alpha before 2025 allows attackers to send requests above the stipulated thresholds because the rate is measured separately for each edge node...

Two Views, One Truth: Spectral and Self-Supervised Features Fusion for Robust Speech Deepfake Detection

Recent advances in synthetic speech have made audio deepfakes increasingly realistic, posing significant security risks. Existing detection methods that rely on a single modality, either raw waveform embeddings or spectral based features, are vulnerable to non spoof disturbances and often overfit...

Sparse Regression Codes for Secret Key Agreement: Achieving Strong Secrecy and Near-Optimal Rates for Gaussian Sources

Secret key agreement from correlated physical layer observations is a cornerstone of information-theoretic security. This paper proposes and rigorously analyzes a complete, constructive protocol for secret key agreement from Gaussian sources using Sparse Regression Codes SPARCs. Our protocol...

ConSeg: Contextual Backdoor Attack against Semantic Segmentation

Despite significant advancements in computer vision, semantic segmentation models may be susceptible to backdoor attacks. These attacks, involving hidden triggers, aim to cause the models to misclassify instances of the victim class as the target class when triggers are present, posing serious...

CVE-2025-54568

Akamai Rate Control alpha before 2025 allows attackers to send requests above the stipulated thresholds because the rate is measured separately for each edge node...

CVE-2025-54568

Akamai Rate Control alpha before 2025 allows attackers to send requests above the stipulated thresholds because the rate is measured separately for each edge node...

Akamai Rate Control 安全漏洞

Akamai Rate Control is an API access frequency control software from Akamai Corporation. A security vulnerability exists in Akamai Rate Control versions prior to 2025, which stems from inconsistent rate measurements that could cause requests to exceed thresholds...

On Anti-Collusion Codes for Averaging Attack in Multimedia Fingerprinting

Multimedia fingerprinting is a technique to protect the copyrighted contents against being illegally redistributed under various collusion attack models. Averaging attack is the most fair choice for each colluder to avoid detection, and also makes the pirate copy have better perceptional quality...

CVE-2025-54568

Akamai Rate Control alpha before 2025 allows attackers to send requests above the stipulated thresholds because the rate is measured separately for each edge node...

CVE-2025-54568

Summary (CVE-2025-54568) : The vulnerability concerns Akamai Rate Control. Descriptions across sources indicate that alpha before 2025 versions permit attackers to exceed rate thresholds because the rate is measured separately for each edge node. The provided documents do not specify affected pro...

Secure One-Sided Device-Independent Quantum Key Distribution under Collective Attacks with Enhanced Robustness

We study the security of a quantum key distribution QKD protocol under the one-sided device-independent 1sDI setting, which assumes trust in only one party's measurement device. This approach effectively provides a balance between the experimental viability of device-dependent DD-QKD and the...

LLM Meets the Sky: Heuristic Multi-Agent Reinforcement Learning for Secure Heterogeneous UAV Networks

This work tackles the physical layer security PLS problem of maximizing the secrecy rate in heterogeneous UAV networks HetUAVNs under propulsion energy constraints. Unlike prior studies that assume uniform UAV capabilities or overlook energy-security trade-offs, we consider a realistic scenario...

Secure Wireless Communication Via Polarforming

Polarforming is a promising technique that enables dynamic adjustment of antenna polarization to mitigate depolarization effects commonly encountered during electromagnetic EM wave propagation. In this letter, we investigate the polarforming design for secure wireless communication systems, where...

The vulnerability of the fromSpeedTestSet() function (/goform/setRateTest) in the Tenda O3 wireless access point software allows a hacker to execute arbitrary code or cause service interruptions.

The vulnerability of the fromSpeedTestSet function /goform/setRateTest in the Tenda O3 wireless access point software is related to the operation that goes beyond the buffer in memory when processing the destIP parameter. Exploiting this vulnerability could allow an attacker to execute arbitrary...

Data-Plane Telemetry to Mitigate Long-Distance BGP Hijacks

Poor security of Internet routing enables adversaries to divert user data through unintended infrastructures hijack. Of particular concern -- and the focus of this paper -- are cases where attackers reroute domestic traffic through foreign countries, exposing it to surveillance, bypassing legal...

Tenda O3V2 /goform/setRateTest File Buffer Overflow Vulnerability

Tenda O3V2 is an outdoor wireless bridge from Tenda, China. The Tenda O3V2 suffers from a buffer overflow vulnerability, which originates from the parameter destIP in the file /goform/setRateTest that fails to correctly validate the length of the input data, which can be exploited by an attacker ...

Enterprise Security Incident Analysis and Countermeasures Based on the T-Mobile Data Breach

This paper presents a comprehensive analysis of T-Mobile's critical data breaches in 2021 and 2023, alongside a full-spectrum security audit targeting its systems, infrastructure, and publicly exposed endpoints. By combining case-based vulnerability assessments with active ethical hacking...