<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>红队测试 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E7%BA%A2%E9%98%9F%E6%B5%8B%E8%AF%95/</link><description>Recent content in 红队测试 on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 16 Jul 2026 11:22:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E7%BA%A2%E9%98%9F%E6%B5%8B%E8%AF%95/index.xml" rel="self" type="application/rss+xml"/><item><title>AI红队测试方法论：系统化发现模型安全漏洞</title><link>https://guijiagi.com/posts/b1-b4f957a6/</link><pubDate>Thu, 16 Jul 2026 11:22:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-b4f957a6/</guid><description>介绍AI红队测试的系统化方法论，涵盖攻击面分析、测试设计、漏洞分类与修复验证</description></item><item><title>AI安全对齐技术栈：从RLHF到Constitutional AI</title><link>https://guijiagi.com/posts/b2-fd3b570e/</link><pubDate>Thu, 16 Jul 2026 10:05:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-fd3b570e/</guid><description>全面梳理大模型安全对齐技术体系，涵盖RLHF、DPO、Constitutional AI及红队测试实践</description></item><item><title>AI红队测试自动化：构建持续的安全验证体系</title><link>https://guijiagi.com/posts/ai-red-team-automation/</link><pubDate>Thu, 02 Jul 2026 10:22:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-red-team-automation/</guid><description>探讨AI红队测试的自动化框架设计、攻击模拟与持续验证机制</description></item><item><title>AI Agent 安全攻防 2026：从越狱到权限管理</title><link>https://guijiagi.com/posts/agent-security-defense-2026/</link><pubDate>Tue, 30 Jun 2026 17:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/agent-security-defense-2026/</guid><description>2026年AI Agent安全全景：常见攻击向量、防御策略、权限管理框架与安全评估方法</description></item><item><title>大模型安全审计：漏洞扫描与渗透测试</title><link>https://guijiagi.com/posts/llm-security-audit-vulnerability-scanning/</link><pubDate>Tue, 30 Jun 2026 11:35:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-security-audit-vulnerability-scanning/</guid><description>系统介绍大模型安全审计的完整方法论，包括漏洞分类、扫描工具、渗透测试流程和修复建议，提供可操作的审计指南</description></item><item><title>AI红队测试实战：从Prompt注入到数据泄露</title><link>https://guijiagi.com/posts/ai-red-teaming-prompt-injection-to-data-leak/</link><pubDate>Tue, 30 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-red-teaming-prompt-injection-to-data-leak/</guid><description>深入探讨2026年AI红队测试的实战方法论，覆盖Prompt注入、数据泄露、权限逃逸等关键攻击向量，提供完整测试框架与防御建议</description></item><item><title>LLM 红队测试实战：20 种越狱手法与防御</title><link>https://guijiagi.com/posts/llm-red-team-jailbreak-20-methods/</link><pubDate>Sun, 28 Jun 2026 11:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-red-team-jailbreak-20-methods/</guid><description>20种LLM越狱攻击手法实战解析及对应的防御策略，附红队测试框架</description></item><item><title>大模型红队测试方法论</title><link>https://guijiagi.com/posts/llm-red-team-methodology/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-red-team-methodology/</guid><description>大模型红队测试方法论</description></item><item><title>LLM 红队测试实践：攻击即防御</title><link>https://guijiagi.com/posts/red-teaming-llm/</link><pubDate>Wed, 24 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/red-teaming-llm/</guid><description>系统性介绍 LLM 红队测试方法论，涵盖攻击向量分析、自动化工具链、修复流程与真实案例</description></item></channel></rss>