CVE-2025-69873

ajv Another JSON Schema Validator before 8.18.0 is vulnerable to Regular Expression Denial of Service ReDoS when the $data option is enabled. The pattern keyword accepts runtime data via JSON Pointer syntax $data reference, which is passed directly to the JavaScript RegExp constructor without...

Introducing the WIN Partner Index: The Integrations That Powered Modern Cloud Security in 2025

A data-driven industry benchmark showing how integrations are adopted, gain traction, and deliver value across modern cloud security programs...

Safeguard: Security Controls at the Software Defined Network Layer

Improvements in software defined networking allow for policy to be informed and modified by data-driven applications that can adjust policy to accommodate fluctuating requirements at line speed. However, there is some concern that over-correction can occur and cause unintended consequences...

Cybersecurity Predictions 2026: The Hype We Can Ignore (And the Risks We Can't)

As organizations plan for 2026, cybersecurity predictions are everywhere. Yet many strategies are still shaped by headlines and speculation rather than evidence. The real challenge isn't a lack of forecasts—it's identifying which predictions reflect real, emerging risks and which can safely be...

CurricuLLM: Designing Personalized and Workforce-Aligned Cybersecurity Curricula Using Fine-Tuned LLMs

The cybersecurity landscape is constantly evolving, driven by increased digitalization and new cybersecurity threats. Cybersecurity programs often fail to equip graduates with skills demanded by the workforce, particularly concerning recent developments in cybersecurity, as curriculum design is...

Hybrid Quantum-Classical Autoencoders for Unsupervised Network Intrusion Detection

Unsupervised anomaly-based intrusion detection requires models that can generalize to attack patterns not observed during training. This work presents the first large-scale evaluation of hybrid quantum-classical HQC autoencoders for this task. We construct a unified experimental framework that...

A Secured Intent-Based Networking (SIBN) with Data-Driven Time-Aware Intrusion Detection

While Intent-Based Networking IBN promises operational efficiency through autonomous and abstraction-driven network management, a critical unaddressed issue lies in IBN's implicit trust in the integrity of intent ingested by the network. This inherent assumption of data reliability creates a blin...

AgentCyTE: Leveraging Agentic AI to Generate Cybersecurity Training and Experimentation Scenarios

Designing realistic and adaptive networked threat scenarios remains a core challenge in cybersecurity research and training, still requiring substantial manual effort. While large language models LLMs show promise for automated synthesis, unconstrained generation often yields configurations that...

[Extended] Ethics in Computer Security Research: a Data-Driven Assessment of the Past, the Present, and the Possible Future

Ethical questions are discussed regularly in computer security. Still, researchers in computer security lack clear guidance on how to make, document, and assess ethical decisions in research when what is morally right or acceptable is not clear-cut. In this work, we give an overview of the...

This “insidious” police tech claims to predict crime (Lock and Code S06E18)

This week on the Lock and Code podcast… In the late 2010s, a group of sheriffs out of Pasco County, Florida, believed they could predict crime. The Sheriff’s Department there had piloted a program called “Intelligence-Led Policing” and the program would allegedly analyze disparate points of data ...

Unleashing Agentic AI for Superior Threat-Informed Risk Prioritization with Agent Nyra

The cybersecurity landscape evolves relentlessly, with new adversaries and threats emerging daily. For organizations navigating these challenges, reactive responses are no longer enough. It’s about moving from complex, disconnected data streams to proactive, autonomous solutions with actionable...

Attack Pattern Mining to Discover Hidden Threats to Industrial Control Systems

This work focuses on validation of attack pattern mining in the context of Industrial Control System ICS security. A comprehensive security assessment of an ICS requires generating a large and variety of attack patterns. For this purpose we have proposed a data driven technique to generate attack...

The CryptoNeo Threat Modelling Framework (CNTMF): Securing Neobanks and Fintech in Integrated Blockchain Ecosystems

The rapid integration of blockchain, cryptocurrency, and Web3 technologies into digital banks and fintech operations has created an integrated environment blending traditional financial systems with decentralised elements. This paper introduces the CryptoNeo Threat Modelling Framework CNTMF, a...

Data-Driven Marketing in 2025: Navigating Risks, Ethics and Compliance Management

The modern marketing stack and every effective marketing platform runs on data. From ad campaigns to user journeys,…...

Salt 安全漏洞

Salt is an automation, infrastructure management, data-driven orchestration, and remote execution application from the Salt project. A security vulnerability exists in Salt that stems from the failure to clean up the input value jid in the main pubret method, which could lead to a denial of servi...

Cyber Security of Sensor Systems for State Sequence Estimation: an AI Approach

Sensor systems are extremely popular today and vulnerable to sensor data attacks. Due to possible devastating consequences, counteracting sensor data attacks is an extremely important topic, which has not seen sufficient study. This paper develops the first methods that accurately...

Towards Quantum Resilience: Data-Driven Migration Strategy Design

The advancements in quantum computing are a threat to classical cryptographic systems. The traditional cryptographic methods that utilize factorization-based or discrete-logarithm-based algorithms, such as RSA and ECC, are some of these. This paper thoroughly investigates the vulnerabilities of...

Data-Driven Falsification of Cyber-Physical Systems

Whitepaper called Data-Driven Falsification Of Cyber-Physical Systems...

CVE-2025-27508

Emissary is a P2P based data-driven workflow engine. The ChecksumCalculator class within allows for hashing and checksum generation, but it includes or defaults to algorithms that are no longer recommended for secure cryptographic use cases e.g., SHA-1, CRC32, and SSDEEP. These algorithms, while...

EmbedAI 安全漏洞

EmbedAI is a platform from EmbedAI that enables users to use their data to create AI chatbots powered by ChatGPT. A security vulnerability exists in EmbedAI version 2.1 and prior versions that stems from improper access control...