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Browse all posts by publish date.
2026
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How I Verified the Local Database Unlock Chain in WeChat macOS 4.0.1.52
A retrospective on engineering-focused forensics conducted on my own device. By tracing static files, runtime open paths, and SQLCipher parameters in sequence, I ultimately confirmed that the local database unlock chain in WeChat macOS 4.0.1.52 is based on an account-level key distribution model.
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If You Want to Automate Your Own WeChat Account, First Think Through These Three Layers
If the goal is “automation for your own account,” what really needs to be separated first is not a feature checklist, but the listening layer, execution layer, and storage layer.
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From Assisted Coding to Integrated R&D: Putting AI Programming into Team Practice (PPT)
A Slidev-style Chinese presentation translated into English, explaining Agentic Coding, Skills and MCP, AGENTS.md and CLAUDE.md, sandboxing and permission controls, and how a team can truly operationalize AI programming with Plans, a YApi Skill, and docs-sync.
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How QClaw Works: How It Turns OpenClaw into a Desktop Application
This article goes beyond the broad “control plane / execution plane” framing and instead walks through the current implementation piece by piece—covering the bridging layer, IPC, configuration fields, the WeChat flow, rollback mechanisms, and the evidence index—to explain how QClaw organizes OpenClaw into a deliverable desktop runtime.
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OpenClaw v2026.3.8 Release Analysis: Backup, Remote Gateway, Talk Mode, and Multi-Endpoint Routing Continue to Improve
Based on the official release notes, this article summarizes the key changes in OpenClaw v2026.3.8: backup commands arriving in the main workflow, macOS remote gateway onboarding, Talk silence timeout, Brave search integration, ACP receipts, and multi-platform routing fixes.
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Designing an Offensive–Defensive Strategy for Browser Automation: Detection Models and Layered Control Planes
Abstract browser automation in highly adversarial environments as a multi-dimensional risk scoring system, and build a layered control plane using three core dimensions—consistency, rarity, and temporal distribution.
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Designing Browser Automation Offense/Defense: Detection Models and a Layered Control Plane
This article abstracts browser automation in highly adversarial environments into a multidimensional risk scoring system, and builds a layered control plane around three core dimensions: consistency, rarity, and temporal distribution.
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Designing Attack and Defense Strategies for Cloudflare Turnstile: System Principles and the Control Plane
Reframes the Turnstile risk model from a capability-token perspective, focusing on issuance/consumption semantics, scope binding, and execution integrity, and provides a defense prioritization for high-adversary environments.
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Use agent-browser-stealth Instead of agent-browser
For growth and promotion use cases: improve AI browser operability on high-risk-control sites like Amazon, and support reusing a user’s existing browser state.