TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification Utilizing OOD Data

Federated learning FL systems allow decentralized data-owning clients to jointly train a global model through uploading their locally trained updates to a centralized server. The property of decentralization enables adversaries to craft carefully designed backdoor updates to make the global model...

The Impact of AI on the Cyber Offense-Defense Balance and the Character of Cyber Conflict

Unlike other domains of conflict, and unlike other fields with high anticipated risk from AI, the cyber domain is intrinsically digital with a tight feedback loop between AI training and cyber application. Cyber may have some of the largest and earliest impacts from AI, so it is important to...

DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-Based Intrusion Detection against Adversarial Attacks

The rapid proliferation of the Internet of Things IoT has introduced substantial security vulnerabilities, highlighting the need for robust Intrusion Detection Systems IDS. Machine learning-based intrusion detection systems ML-IDS have significantly improved threat detection capabilities; however...

Attack-Defense Trees with Offensive and Defensive Attributes (With Appendix)

Effective risk management in cybersecurity requires a thorough understanding of the interplay between attacker capabilities and defense strategies. Attack-Defense Trees ADTs are a commonly used methodology for representing this interplay; however, previous work in this domain has only focused on...

Security-First AI: Foundations for Robust and Trustworthy Systems

The conversation around artificial intelligence AI often focuses on safety, transparency, accountability, alignment, and responsibility. However, AI security i.e., the safeguarding of data, models, and pipelines from adversarial manipulation underpins all of these efforts. This manuscript posits...

Cyber Signals Issue 9 | AI-powered deception: Emerging fraud threats and countermeasures

Introduction | Security snapshot | Threat briefing Defending against attacks | Expert profile Microsoft maintains a continuous effort to protect its platforms and customers from fraud and abuse. From blocking imposters on Microsoft Azure and adding anti-scam features to Microsoft Edge, to fightin...

Bypassing Prompt Injection and Jailbreak Detection in LLM Guardrails

Large Language Models LLMs guardrail systems are designed to protect against prompt injection and jailbreak attacks. However, they remain vulnerable to evasion techniques. We demonstrate two approaches for bypassing LLM prompt injection and jailbreak detection systems via traditional character...

Cisco Firepower Threat Defense Software Snort 3 Geolocation IP Filter Bypass (cisco-sa-ftdsnort3sip-bypass-LMz2ThKn)

According to its self-reported version, Cisco Firepower Threat Defense FTD Software is affected by a vulnerability. - A vulnerability in the IP geolocation rules of Snort 3 could allow an unauthenticated, remote attacker to potentially bypass IP address restrictions. This vulnerability exists...

Secure Transfer Learning: Training Clean Models against Backdoor in (Both) Pre-Trained Encoders and Downstream Datasets

Transfer learning from pre-trained encoders has become essential in modern machine learning, enabling efficient model adaptation across diverse tasks. However, this combination of pre-training and downstream adaptation creates an expanded attack surface, exposing models to sophisticated backdoor...

RAID: an In-Training Defense against Attribute Inference Attacks in Recommender Systems

In various networks and mobile applications, users are highly susceptible to attribute inference attacks, with particularly prevalent occurrences in recommender systems. Attackers exploit partially exposed user profiles in recommendation models, such as user embeddings, to infer private attribute...

Exploring Backdoor Attack and Defense for LLM-Empowered Recommendations

The fusion of Large Language Models LLMs with recommender systems RecSys has dramatically advanced personalized recommendations and drawn extensive attention. Despite the impressive progress, the safety of LLM-based RecSys against backdoor attacks remains largely under-explored. In this paper, we...

Cybersecurity through Entropy Injection: a Paradigm Shift from Reactive Defense to Proactive Uncertainty

Cybersecurity often hinges on unpredictability, with a system's defenses being strongest when sensitive values and behaviors cannot be anticipated by attackers. This paper explores the concept of entropy injection-deliberately infusing randomness into security mechanisms to increase...

Token-Level Constraint Boundary Search for Jailbreaking Text-To-Image Models

Recent advancements in Text-to-Image T2I generation have significantly enhanced the realism and creativity of generated images. However, such powerful generative capabilities pose risks related to the production of inappropriate or harmful content. Existing defense mechanisms, including prompt...

The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injections

A Large Language Model LLM powered GUI agent is a specialized autonomous system that performs tasks on the user's behalf according to high-level instructions. It does so by perceiving and interpreting the graphical user interfaces GUIs of relevant apps, often visually, inferring necessary sequenc...

Concept Enhancement Engineering: a Lightweight and Efficient Robust Defense against Jailbreak Attacks in Embodied AI

Embodied Intelligence EI systems integrated with large language models LLMs face significant security risks, particularly from jailbreak attacks that manipulate models into generating harmful outputs or executing unsafe physical actions. Traditional defense strategies, such as input filtering and...

It’s All in the Cards: Preventing Payment Abuse for Retailers

Carding attacks have become a serious challenge for retailers. Learn how Akamai Account Protector can help organizations defend against payment abuse...

Wordfence Intelligence Weekly WordPress Vulnerability Report (March 31, 2025 to April 6, 2025)

In case you missed it, Wordfence just published itsannual WordPress security report for 2024. Read it now to learn more about the evolving risk landscape of WordPress so you can keep your sites protected in 2025 and beyond. Last week, there were 551 vulnerabilities disclosed in 485 WordPress...

Stopping attacks against on-premises Exchange Server and SharePoint Server with AMSI

Exchange Server and SharePoint Server are business-critical assets and considered crown jewels for many organizations, making them attractive targets for attacks. To help customers protect their environments and respond to these attacks, Exchange Server and SharePoint Server now integrate with th...

Brinker Named Among “10 Most Promising Defense Tech Startups of 2025”

Delaware, USA, 2nd April 2025, CyberNewsWire...

Advanced XSS Exploitation - How to Record User Audio

In this paper, the author teaches advanced persistent cross site scripting techniques that can be used to record client audio conversations and send them to an external server. The paper is primarily focusing on a pentesting perspective but also discusses mitigations. Written in Brazilian...