🐬ETA Weekly🦀
🪺94 Intrusion Prevention Systems (IPS)🐳
🚥Update in Audit🧤
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github.com/ETAAcademy/ETAAca…👗
🤽♂️IDS detects threats by observing network traffic and issuing alerts, while IPS builds upon detection capabilities to actively mitigate threats. Intrusion Detection and Prevention Systems (IDS/IPS), as core technologies in network security, have evolved from traditional signature-based and anomaly detection open-source tools like Snort to artificial intelligence-driven systems that integrate machine learning, deep learning, natural language processing, and reinforcement learning.🪽
🍱Modern IDPS employs multi-layered architectural design, integrating multi-source data through data collection layers and utilizing AI technologies such as Deep Learning Multi-Layer Perceptrons (DLMLP), Convolutional Neural Networks (CNN), and Generative Adversarial Networks (GAN) to process large-scale datasets, achieving high-precision detection and low false-positive classification for various attacks including DDoS, MITM, and Mirai. The system's core AI threat detection engine combines supervised learning, unsupervised learning, and reinforcement learning models, optimizing processing effectiveness through feature extraction, PCA dimensionality reduction, and time series analysis, while the automated response layer implements real-time mitigation measures such as firewall rule generation, instance isolation, and zero-trust architecture.🐑
🍕Addressing the special requirements of IoT and robotic systems, blockchain-assisted intelligent protection architectures and specialized Robot Intrusion Prevention Systems (RIPS) have been developed. The latter, based on ROS and DDS middleware, achieves comprehensive threat detection from message-level to graph-structure-level through three categories of expression syntax: Message events, Graph events, and External events. It integrates the advantages of tools like HAROS and ROS-FM, supports centralized, distributed, and hybrid cloud deployment models, and achieves scalability optimization through technologies such as federated learning, AutoML, and GPU acceleration, providing complete intelligent security protection solutions from traffic monitoring, anomaly identification, and threat assessment to response execution. Although challenges remain in areas such as adversarial attacks, data privacy, and computational overhead, the field is advancing toward next-generation network security technologies including self-healing, blockchain enhancement, and quantum AI.🧵
✉️📩📨💌
🤿BMX-Deli-Swap 🥋Malda 🥊zksync ⛸️XSY-UTYAsyncVault
- Rebalancer can drain market funds via excessive bridge fees
- Gas consumed in notifyUnsubscribe is underestimated during tests and is greater than 300,000 without pre-warming
- Batch State Commitment Bypass Leading to Replay Attacks
- Donation attack on vault depositors
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github.com/ETAAcademy/ETAAca…🏓
🫡No new report, no update 🚵
⛹️♀️1 to 4 bugs / report, different from existing 300 🫖
🍋Update in Check-Context-Openzeppelin-Uniswap🚟
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