CVE-2026-44688

In Eclipse Theia versions prior to 1.71.0, the AI chat agent processed workspace file and directory names as part of its prompt context without distinguishing them from system instructions. An attacker could craft a malicious repository with adversarial directory or file names that, when analyzed...

LLM Agent Safety, Multi-Turn Red-Teaming, Jailbreak Benchmarks, Adversarial Robustness, Safety-Critical Systems

Large language model LLM agents are increasingly proposed as supervisory components for safety-critical systems, yet their robustness under sustained, adaptive adversarial pressure remains poorly characterized. We present NRT-Bench, a benchmark for multi-turn red-teaming of LLM agents acting as...

Adversarial Exposure Validation Turns Security Visibility into Confident Prioritization

For security teams, the findings never stop, but confidence in knowing which ones matter is becoming harder to maintain. The problem is no longer visibility. It's validation. Security teams must decide which findings warrant action while operating under constant pressure and incomplete informatio...

OpenAnt: LLM-Powered Vulnerability Discovery through Code Decomposition, Adversarial Verification, and Dynamic Testing

Automated vulnerability discovery in large codebases remains challenging: traditional static analysis produces high false-positive rates, while dynamic approaches such as fuzzing require substantial infrastructure and often target narrow classes of bugs. Recent advances in large language models...

MAStrike: Shapley-Guided Collusive Red-Teaming on Multi-Agent Systems

Hierarchical multi-agent systems MAS are rapidly being deployed in high-stakes workflows across domains such as finance and software engineering. In these systems, safety and security are inherently distributed across role-specialized agents, significantly expanding the attack surface, particular...

SEVRA-BENCH: Social Engineering of Vulnerabilities in Review Agents

Large language model LLM reviewers are increasingly used in pull-request PR workflows, where their approvals help decide which code is merged into a repository. This raises a question that benchmarks for static vulnerability detection or code generation do not address: can an automated reviewer...

Smarter Saboteurs, Better Fixers: Scaling and Security in Linear Multi-Agent Workflows

As LLM-based multi-agent systems MAS are deployed in the wild, the resilience of their collaboration structures against adversarial compromise becomes a critical safety concern. Attackers may leverage prompt-injection or jailbreaking to sabotage individual agents within MAS workflows, but the...

Categorical Robustness Assessment for Machine Learning Based Network Intrusion Detection Systems

Network Intrusion Detection Systems NIDS heavily utlize Machine Learning ML but ML models can be manipulated via adversarial attacks. These attacks add carefully crafted perturbations to network traffic data that leads to misclassifications. While prior work has demonstrated adversarial...

MemVenom: Triggered Poisoning of Multimodal Memories in Web Agents

External memory has become a core component of modern web agents, enabling long-horizon reasoning through the retrieval of past experiences. However, this paradigm introduces a critical vulnerability: malicious content injected into memory can be persistently recalled and repeatedly influence age...

Context-Based Adversarial Attacks on AI Code Generators: Vulnerability Analysis and Implications

AI-powered code generation systems have transformed software development but introduce critical inference-time security vulnerabilities. This research presents a systematic investigation of context-based adversarial attacks, where strategically crafted contextual inputs, including comments,...

Semantic Multi-Agent Intrusion Detection for IoT:Zero-Day and Adversarial Threats with Risk-Aware Reasoning

The rapid proliferation of Internet of Things IoT devices has enabled unprecedented automation and connectivity, but it has also substantially increased the attack surface, exposing networks to sophisticated cyber threats, including zero-day and adversarial intrusions. Traditional Intrusion...

The Chronicles of Radio Frequency Fingerprinting

Radio Frequency Fingerprinting RFF has evolved from an early idea for radar emitter identification into a broad research field for wireless device identification and spectrum monitoring for security. Rather than presenting a conventional literature survey, this work provides a critical historical...

acapi (>=0.5.0, <=0.8.1), achoz (>=0.3.0, <=0.3.42) +1388 more potentially affected by CVE-2026-45409 via idna (2.8.0)

idna PYPI version 2.8.0 is affected by a known vulnerability. The following packages have a transitive dependency on idna and may be impacted: - acapi =0.5.0, =0.3.0, =0.1.0, =0.1.0, =0.1.7, =3.6.0, =0.0.1, =0.0.2, =2022.9.19, =0.5.0, =0.5.2, =0.75.14 and more Source cves: CVE-2026-45409 Source...

CVE-2026-31229

A flaw was found in the Adversarial Robustness Toolbox ART, specifically within its Kubeflow component. This vulnerability, categorized as insecure deserialization CWE-502, occurs when loading model weights without proper security restrictions. A remote attacker can exploit this by uploading a...

CVE-2026-31230

A flaw was found in Adversarial Robustness Toolbox ART. This command-line argument injection vulnerability exists in its Kubeflow component due to the unsafe use of the eval function, which parses string values from --clipvalues and --inputshape arguments. A remote attacker can exploit this by...

CVE-2026-31228

A flaw was found in the Adversarial Robustness Toolbox ART, specifically within its Kubeflow component. The robustness evaluation function for PyTorch models uses the eval function to dynamically evaluate user-supplied strings for the LossFn and Optimizer parameters without proper sanitization. A...

TinyML-Driven Cybersecurity for Autonomous Spacecraft: Latency-Accuracy Analysis for SPARTA RF and Cyber Threat Detection

Autonomous spacecraft require rapid, lightweight, and reliable onboard detection of cyber-RF threats. Using the SPARTA attack model, we analyze the latency-accuracy trade-offs of TinyML-compatible classical models -- Random Forest, Logistic Regression, SVM, and MLP -- for detecting uplink jamming...

Detecting Aimbot Cheaters in MOGs

Multiplayer Online Games have become a multibillion dollar industry in the entertainment sector. However, the presence of cheaters undermines the experience of honest players and devalues the effort of game developers, as it directly affects player retention, competitive integrity, the legitimacy...

Operationalizing Cyber Attack Prediction: A Gap-Prioritized Framework with Dataset and Model Selection Guidelines

While AI and machine learning for cyber attack prediction have advanced, a critical gap persists between theoretical research and practical operational deployment. Building on Ankalaki et al. 2025, this paper provides a comprehensive analysis of 150+ benchmark datasets and 200+ studies to identif...

SECUREVENT: Hybrid AI/ML Security Monitoring for Distributed Event-Based Systems

Distributed event-based systems have become a common substrate for Internet-scale publish/subscribe services, IoT telemetry, cloud-native microservices, and security operations pipelines. Their loose coupling and asynchronous delivery improve scalability, but they also expand the attack surface:...