The shift from AI assistants to AI agents changes the security surface entirely. An agent that can browse the web, write code, call APIs, and initiate payments is not just a smarter chatbot. It is a new class of software principal, and the existing security playbook was not written for it. At I/O Connect India 2026, Google announced a coordinated set of tools and open standards aimed squarely at this gap: Sec-Gemini v3, CodeMender, CAPSEM, DBSC, and AP2. Together they form something closer to a security architecture than a product release.
The problem no one solved yet
Traditional security treats safety as a final checkpoint before shipping. The agentic era changes that responsibility: software can now interpret intent, use tools, and take action autonomously. That means a compromised agent does not just leak data. It can take actions, make purchases, and propagate damage across systems at machine speed. The threat model is fundamentally different, and Google's argument is that security must be baked into the underlying architecture, not bolted on afterward.
There is also a supply-side problem. As agents write more code, that code needs to be secured at the same speed and scale it is being produced. AI-generated codebases are growing faster than human reviewers can audit them. The tools announced here are a direct response to that asymmetry.
Sec-Gemini v3: the defender's co-pilot
Sec-Gemini v3 is Google's specialized cybersecurity agent, now being brought to trusted government and enterprise testers including Flipkart. It can reason across complex security data and help security operations teams automate tasks like incident investigation, digital forensics, and malware analysis at machine speed.
Effectively powering SecOps workflows requires state-of-the-art reasoning capabilities and extensive current cybersecurity knowledge. Because Sec-Gemini is constantly ingesting updated Google threat intelligence, it can provide up-to-date answers on security topics in close to real time, factoring in whether a CVE for a software vulnerability has been updated in the past few days with a new patch. The model is trained on highly curated, security-specific data streams, not general web text, which is what makes it useful for incident response rather than just trivia.
Access to Sec-Gemini v3 is currently limited to a trusted tester program. The repository on GitHub hosts SDKs and a CLI for Sec-Gemini, described as an experimental cybersecurity-focused AI from Google. You can explore the
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