How The Apprentice Learns To Build Its Master: Claude Code Gains 'Automated Security Reviews'

In a world where AI is no longer just a tool, people have begun assigning it roles.

No longer confined to cold commands or predictable outputs, AI now wears many hats: an assistant, a consultant, an all-ear friend, a colleague, and most intriguingly, a coding companion. Ever since OpenAI’s ChatGPT took center stage, igniting a full-blown AI arms race, one truth has become undeniable: large language models (LLMs) are remarkably good at coding.

Among the rising stars in this domain is Claude, Anthropic’s sophisticated LLM.

Renowned not only for its creative reasoning but also its calm, human-aligned demeanor, Claude Code has quietly earned a reputation for being smart coder.

And this time, Anthropic has taken its commitment to alignment and transformed it into something deeply practical: a coding assistant that not only writes software, but reviews it with security in mind.

Read: Anthropic 'Claude 3.7 Sonnet' And 'Claude Code' Mark The Next Step Of Human-LLM Collaboration

Anthropic is again putting Claude Code into the spotlight with an innovation that redefines developer trust: automated security reviews.

Introduced as part of Claude's intelligent coding suite, this feature allows developers to uncover vulnerabilities in real time, right from their terminal.

By entering the /security-review command, Claude activates a scan of users' codebase.

Then, using its understanding of secure coding principles to detect a broad range of issues, like injection attacks from SQLi and XSS, to weak authentication patterns, unsafe dependencies, and poor data handling.

Unlike traditional static analyzers, Claude doesn’t just flag the issue.

Instead, it explains it.

It can even recommend or apply a fix, with the user’s approval.

This feature is like like a god-send to even the most veteran and battle-hardened programmers. Let alone vibe coders.

It’s like having a cyber guardian angel with a PhD in software security, perched quietly in the IDE.

Beyond the command-line charm, Claude’s automated security reviews integrate smoothly with GitHub workflows, offering a scalable security mechanism for teams. Developers can connect Claude to their repositories so that every new pull request triggers a security analysis.

The results appear as inline comments on the code diff. Clear, actionable, and without the overwhelming noise.

Teams can even customize which issues to focus on, tailoring the sensitivity based on coding context, repository size, or organizational policy. This means fewer false positives, more signal, and fewer “security theater” moments.

Even the people at Anthropic are using this very feature to support their own work.

With Claude Code’s automated capabilities, they’re able to build, review, and secure the core technologies that power their models. It’s a kind of quiet symmetry: an AI helping to refine itself, while human expertise remains at the helm. What emerges is not a simple workflow, but a feedback loop of intelligence, a recursive collaboration where insight flows fluidly between human and machine.

This is happening because modern AI models are now built with the help of earlier generations.

Foundational architectures are designed with assistance from AI agents who understand not just raw data, but theoretical underpinnings, design patterns, and engineering nuance. Security reviews, once tedious and time-consuming, are now streamlined by AI tools that grasp not only code syntax but the fragile subtleties where real risks tend to hide.

It’s not limited to Anthropic. Across the AI industry, companies are using AIs to build AIs.

Teams at OpenAI also rely on large language models to assist in brainstorming, organizing research, and debugging experimental features. But this AI-on-AI collaboration isn’t without controversy. Recently, Anthropic restricted API access after reports surfaced suggesting OpenAI had used Claude Code to aid in the development of GPT‑5, the highly secretive successor to GPT‑4.

The incident highlighted a strange new reality: AI companies must now guard their own AIs from one another, not just from misuse by outsiders.

Inside these labs, AI is no longer seen as just software. Machine learning engineers and research scientists treat it as a trusted colleague, an ever-learning apprentice that reasons across domains, adapts to unfamiliar contexts, and offers second opinions with a kind of machine-level clarity.

The result is a new kind of creative partnership. Humans shape AI, and in turn, AI is shaping how humans build the future of intelligence itself.

Anthropic’s security reviews in Claude Code aren’t simply a convenience. Now, they’re a statement about responsible AI tooling.

In an era where software ships faster than ever and threat actors evolve just as swiftly, this feature should make Claude stands out.

Developers no longer need to compromise speed for security or vice versa. Whether users are solo coders pouring heart into a side project or an engineering team navigating a high-stakes product release, this automated security review creates a glimpse into how AI might solve the very problems it sometimes creates.

They are not a silver bullet, but they are an intelligent, evolving shield, and always just one command away.