CVE-2026-53637 Sylius: Cart FormComponent allows modification or deletion of an already-completed order

Sylius is an Open Source eCommerce Framework on Symfony. Versions 2.0.0 through 2.0.17, 2.1.0 through 2.1.14, and 2.2.0 through 2.2.5 contain an improper workflow enforcement vulnerability in the cart FormComponent. When an order is completed while its cart page remains open, the stale...

Aegis aegis-v0.14.1-alpha

AEGIS is a desktop app for monitoring local AI agents and reviewing their files and selected actions. Inspect processes, sensitive-file observations, TCP endpoints and attribution evidence in Observatory. Monitoring requires no agent plugin; policy-controlled execution and MCP action tools requir...

SkillSpector v2.11.1

SkillSpector Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, and security risks before installing agent skills. Overview AI agent skills used by Claude Code, Codex CLI, Gemini CLI, etc. execute with implicit trust and minimal vetting. In the 31,132-skill analyzed...

CVE-2025-14208

creationtimestamp| type| source ---|---|--- 2026-09-08 10:00:03+00:00| seen| The Shadowserver honeypot/common-vulnerabilities - 2026-09-07 2026-09-08 11:00:34+00:00| exploited| https://vulnerability.circl.lu/known-exploited-vulnerabilities-catalog/12253a70-6b5a-44ad-b30d-9849e4011cb8 2026-09-09...

Watcher v3.5.3

AI-Powered Automated Cybersecurity Threat Detection Platform Watcher is a Django & React JS platform designed to discover and monitor emerging cybersecurity threats with AI-powered threat intelligence analysis. It can be deployed on webservers or quickly run via Docker. Watcher Capabilities Watch...

LLMSec-AV: A Vulnerability Taxonomy and LLM-Driven Software Weakness Discovery Framework for Autonomous Vehicles

Automated vehicles rely on millions of lines of safety-critical software, yet general-purpose analyzers do not understand which code can affect vehicle motion. This study asks whether large language models LLMs with explicit automated-vehicle AV security knowledge improve weakness detection beyon...

HoneyRoute: Honeypot-Model Routing for Adversarial LLM Serving

We introduce HoneyRoute, an inference-serving layer that detects whether an incoming request is malicious and, if so, routes it to a dedicated honeypot model, shielding production while the adversary's interaction is continuously harvested for intelligence. Existing defenses embed traps inside...

Windows Malware Detector As a Compound AI System: Trade-Offs in Accuracy, Efficiency, and Adversarial Robustness

Industrial Windows malware detectors are commonly described as Compound AI Systems composed of multiple heterogeneous components, including rule-based mechanisms as well as machine-learning-based static and dynamic analyses. However, due to industrial secrecy and limited public disclosure, the...

Navigating the Latent Manifold: Proactive Concept Drift Adaptation for Resilient NIDS

Network intrusion detection systems NIDS are critical for cybersecurity, safeguarding services and data from potential attacks. However, existing AI-based NIDS often assume static data distributions and fail to handle concept drift, leading to degraded performance and increased false positives in...

yj_nearbyglasses v1.0.10

yjnearbyglasses attempting to detect smart glasses nearby and warn you. ⚠ WARNING! ⚠ nearby-glasses-alert.pages.dev is NOT RELATED TO MY PROJECT. Many apps in Play Store and App Store look or are even called very similar to Nearby Glasses. They seem to hijack the name and try to make a quick prof...

ultralytics v8.4.142

中文 | 한국어 | 日本語 | Русский | Deutsch | Français | Español | Português | Türkçe | Tiếng Việt | العربية Ultralytics creates cutting-edge, state-of-the-art SOTA YOLO models built on years of foundational research in computer vision and AI. Constan...

Flintlock

Flintlock Hardware-assisted memory sandboxing for high-freq...

Frequency-Domain Mixing Data Augmentation for Malicious Traffic Detection

The strong dynamics of network traffic often force malicious traffic detection models to handle out-of-distribution data. Typically, deep learning-based malicious traffic detection models require a large amount of high-quality training data. However, owing to challenges such as high labeling...

LLM-Based Penetration Testing in the Presence of Honeypots

Large language model LLM agents are increasingly employed for offensive cybersecurity tasks such as automated vulnerability discovery, reconnaissance, and penetration testing. This new capability also threatens one of the defender's most valuable tools: deception. Traditional honeypots rely on...

Towards a Resilience-Theoretic Foundation for Adversarial Robustness in Industrial Control System Anomaly Detection

Anomaly-based intrusion detection systems in industrial control systems ICS and operational technology OT environments are increasingly required to meet formal resilience criteria: absorbed adversarial disturbances, graceful degradation under sustained attack, and certified system-level guarantee...

deadair v0.8.0

deadair checks whether enabled SIEM detections still have the telemetry they need. It reports missing or stale data, ingest delays, and schema mismatches. Runs locally · Read-only · No agent · No telemetry upload Read the technical write-up · Featured in Detection Engineering Weekly · Featured in...

Plaintext credentials written to the threat log and readable by any authenticated user

More info at https://github.com/jay123anta/laravel-threat-detection/security/advisories/GHSA-9jh8-pj82-6ccg...

darts v0.47.0

Time Series Made Easy in Python Darts is a Python library for user-friendly forecasting and anomaly detection on time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The forecasting models can all be used in the same way, using fit and predict...

pentest-metasploitable2-lab

Análise de Exploração e Resposta a Incidente — Laboratório Met...

Skynet: Workflow-Level Anomaly Detection for Agentic AI Via Semantic and Structural Modeling

Agentic AI systems execute complex tasks through long-horizon workflows of planning, tool use, and multi-agent coordination. Task failures in these systems often originate from a single step, such as an injected prompt or a flawed plan, and are then amplified through downstream dependencies as th...