An open model nearly matches Claude Mythos on cybersecurity capabilities: GLM-5.3 solves 12% and Cla...
TL;DR · AI 摘要
GLM-5.3在网络安全任务中表现接近Claude Mythos，仅需20美元token成本即可发现Google Chrome漏洞，Andrew Ng认为防御方具备长期优势。
核心要点
- GLM-5.3解决12%的ExploitBench任务，Claude Mythos解决14%（Anthropic数据）
- 4美元token成本发现Google Chrome安全漏洞
- Andrew Ng认为AI安全是工程问题，防御方有长期优势
结构提纲
按章节快速跳转。
GLM-5.3与Claude Mythos在ExploitBench任务中的表现数据对比。
- ·成本案例
通过20.4美元token成本发现Google Chrome漏洞的具体案例。
- ›专家观点
Andrew Ng对AI安全能力的工程问题判断及防御方优势分析。
思维导图
用一张图看清主题之间的关系。
查看大纲文本（无障碍 / 无 JS 友好）
- AI模型网络安全能力分析
- 模型表现对比
- GLM-5.3 12% vs Claude Mythos 14%
- 实际应用案例
- $20.40发现Chrome漏洞
- 专家观点
- 工程问题论
金句 / Highlights
值得收藏与分享的关键句。
GLM-5.3解决12%和Claude Mythos解决14%的ExploitBench任务（Anthropic数据）
仅需$20.40 token成本发现Google Chrome安全漏洞
Andrew Ng认为这是工程问题，防御方长期占优
DeepLearning.AI on X: "An open model nearly matches Claude Mythos on cybersecurity capabilities: GLM-5.3 solves 12% and Claude Mythos 14% of ExploitBench exploit tasks, per Anthropic. Just $20.40 in tokens found a recent security exploit in Google Chrome. 💸 In this week’s letter, Andrew Ng has a … / X
DeepLearning.AI
@DeepLearningAI
An open model nearly matches Claude Mythos on cybersecurity capabilities: GLM-5.3 solves 12% and Claude Mythos 14% of ExploitBench exploit tasks, per Anthropic. Just $20.40 in tokens found a recent security exploit in Google Chrome. 💸 In this week’s letter, Andrew Ng has a different take from those who worry about these capabilities in the wrong hands: This is an engineering problem, and defenders hold the long term edge 🛡️ 📖
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#DeepLearningAI
#Cybersecurity
#OpenWeights
2:59 AM · Oct 4, 2026
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