Is AI “healthy” to use? (Lock and Code S06E14)

This week on the Lock and Code podcast … “Health” isn’t the first feature that most anyone thinks about when trying out a new technology, but a recent spate of news is forcing the issue when it comes to artificial intelligence AI. In June, The New York Times reported on a group of ChatGPT users w...

Improving IT efficiency with Microsoft Security Copilot in Microsoft Intune and Microsoft Entra

When Microsoft introduced Microsoft Security Copilot last year, our vision was to empower organizations with generative AI that helps security and IT teams simplify operations and respond faster. Since then, we’ve continuously innovated and learned alongside our customers. They consistently tell ...

What Security Leaders Need to Know About AI Governance for SaaS

Generative AI is not arriving with a bang, it’s slowly creeping into the software that companies already use on a daily basis. Whether it is video conferencing or CRM, vendors are scrambling to integrate AI copilots and assistants into their SaaS applications. Slack can now provide AI summaries o...

Temporal Unlearnable Examples: Preventing Personal Video Data from Unauthorized Exploitation by Object Tracking

With the rise of social media, vast amounts of user-uploaded videos e.g., YouTube are utilized as training data for Visual Object Tracking VOT. However, the VOT community has largely overlooked video data-privacy issues, as many private videos have been collected and used for training commercial...

CAVGAN: Unifying Jailbreak and Defense of LLMs Via Generative Adversarial Attacks on Their Internal Representations

Security alignment enables the Large Language Model LLM to gain the protection against malicious queries, but various jailbreak attack methods reveal the vulnerability of this security mechanism. Previous studies have isolated LLM jailbreak attacks and defenses. We analyze the security protection...

Taming Data Challenges in ML-Based Security Tasks: Lessons from Integrating Generative AI

Machine learning-based supervised classifiers are widely used for security tasks, and their improvement has been largely focused on algorithmic advancements. We argue that data challenges that negatively impact the performance of these classifiers have received limited attention. We address the...

From AI to Zero-Days: Why CISOs Can’t Ignore the 2024 Threat Shifts

Running short on time but still want to stay in the know? Well, we’ve got you covered! We’ve condensed all the key takeaways into a handy audio summary. Our AI-driven podcasts are fit for on the go. Two weeks ago, we published the key insights from our Cyber Horizons 2025 Threat Report ,...

Vercel's v0 AI Tool Weaponized by Cybercriminals to Rapidly Create Fake Login Pages at Scale

Unknown threat actors have been observed weaponizing v0, a generative artificial intelligence AI tool from Vercel, to design fake sign-in pages that impersonate their legitimate counterparts. "This observation signals a new evolution in the weaponization of Generative AI by threat actors who have...

5 Cyber Trends That Should Be Shaping Your 2025 Security Strategy

Running short on time but still want to stay in the know? Well, we’ve got you covered! We’ve condensed all the key takeaways into a handy audio summary. Our AI-driven podcasts are fit for on the go. 2024 was the year cyber threats got faster, smarter, and far more lethal. Ransomware groups became...

Boosting Generative Adversarial Transferability with Self-Supervised Vision Transformer Features

The ability of deep neural networks DNNs come from extracting and interpreting features from the data provided. By exploiting intermediate features in DNNs instead of relying on hard labels, we craft adversarial perturbation that generalize more effectively, boosting black-box transferability...

CodeGuard: a Generalized and Stealthy Backdoor Watermarking for Generative Code Models

Generative code models GCMs significantly enhance development efficiency through automated code generation and code summarization. However, building and training these models require computational resources and time, necessitating effective digital copyright protection to prevent unauthorized lea...

Google Adds Multi-Layered Defenses to Secure GenAI from Prompt Injection Attacks

Google has revealed the various safety measures that are being incorporated into its generative artificial intelligence AI systems to mitigate emerging attack vectors like indirect prompt injections and improve the overall security posture for agentic AI systems. "Unlike direct prompt injections,...

Risks and Benefits of LLMs and GenAI for Platform Integrity, Healthcare Diagnostics, Cybersecurity, Privacy and AI Safety: a Comprehensive Survey, Roadmap and Implementation Blueprint

Large Language Models LLMs and generative AI GenAI systems such as ChatGPT, Claude, Gemini, LLaMA, and Copilot, developed by OpenAI, Anthropic, Google, Meta, and Microsoft are reshaping digital platforms and app ecosystems while introducing key challenges in cybersecurity, privacy, and platform...

Organizational Adaptation to Generative AI in Cybersecurity: a Systematic Review

Cybersecurity organizations are adapting to GenAI integration through modified frameworks and hybrid operational processes, with success influenced by existing security maturity, regulatory requirements, and investments in human capital and infrastructure. This qualitative research employs...

An Attack Method for Medical Insurance Claim Fraud Detection Based on Generative Adversarial Network

Insurance fraud detection represents a pivotal advancement in modern insurance service, providing intelligent and digitalized monitoring to enhance management and prevent fraud. It is crucial for ensuring the security and efficiency of insurance systems. Although AI and machine learning algorithm...

Understanding Content Moderation Policies and User Experiences in Generative AI Products

While recent research has focused on developing safeguards for generative AI GAI model-level content safety, little is known about how content moderation to prevent malicious content performs for end-users in real-world GAI products. To bridge this gap, we investigated content moderation policies...

Secure Time-Modulated Intelligent Reflecting Surface via Generative Flow Networks

We propose a novel directional modulation DM design for OFDM transmitters aided by a time-modulated intelligent reflecting surface TM-IRS. The TM-IRS is configured to preserve the integrity of transmitted signals toward multiple legitimate users while scrambling the signal in all other directions...

Your Meta AI chats might be public, and it’s not a bug

Conversations that people are having with the Meta AI app are being exposed publicly, often without the users realizing it, revealing a variety of medical, legal, and private matters. The standalone app and the company's integrations with artificial intelligence AI across its platforms—Facebook,...

MAYA: Addressing Inconsistencies in Generative Password Guessing through a Unified Benchmark

Recent advances in generative models have led to their application in password guessing, with the aim of replicating the complexity, structure, and patterns of human-created passwords. Despite their potential, inconsistencies and inadequate evaluation methodologies in prior research have hindered...

Quantifying Mix Network Privacy Erosion with Generative Models

Modern mix networks improve over Tor and provide stronger privacy guarantees by robustly obfuscating metadata. As long as a message is routed through at least one honest mixnode, the privacy of the users involved is safeguarded. However, the complexity of the mixing mechanisms makes it difficult ...