Claude Security (formerly Claude Code Security): What the AI Security Scan Delivers

What is Claude Security?

Claude Security (previously Claude Code Security) is a tool from Anthropic that scans entire codebases for security vulnerabilities and suggests patches for manual review. Instead of just looking for known patterns, the AI analyses how components interact and how data flows through the application. Each finding receives a severity rating, and no change is applied without human approval. Since April 2026, Claude Security has been available in a public beta for Claude Enterprise customers. Anthropic first introduced it in February 2026 as a research preview under the name Claude Code Security.

Key insights for you

• Prevention: Claude Security also finds complex vulnerabilities that traditional rule-based scanners miss and suggests concrete fixes.
• Human in the loop: The AI does not change any code itself. All patches must be reviewed and approved by your team.
• Data protection: Your code is transmitted to Anthropic for analysis. You therefore need a data processing agreement and clear rules on which repositories are connected.
• Legal responsibility: Technical safeguards do not replace an AI policy, a review of third-country transfers or your own review processes.

The new era of AI-assisted software development

AI-powered code assistants have transformed the way modern development teams work in record time. Tools like Claude Code are no longer experimental gadgets but actively support your team in writing, refactoring and optimising production-critical code. However, the deeper the integration into your development environment, the greater the risk. An AI that has access to your repositories is a powerful tool, but also a potential vulnerability in your supply chain security.

With Claude Security, Anthropic puts AI on the other side: it is meant not only to help avoid vulnerabilities but to actively find them. For you as a technical decision-maker, CTO or CISO, the question is: how much can such a tool achieve, and is it enough to meet the requirements of the GDPR and the EU AI Act? This article provides a factual assessment of the technical capabilities and highlights the legal guardrails you still need to put in place. You can find basic information on Claude Code’s security architecture in Anthropic’s official documentation.

How does Claude Security work technically?

Claude Security is accessible directly in Claude.ai, uses the Claude Opus 4.7 model and builds on Anthropic’s security research with its models – including Capture the Flag competitions. According to Anthropic, this research uncovered more than 500 previously unknown vulnerabilities in open-source projects.

The core components

• Analysis of entire codebases: The AI reads the code like a security researcher, traces data flows across components and also detects logical vulnerabilities, such as flawed access checks.
• Multi-stage verification: Each finding is re-checked to reduce false positives and receives a severity and confidence rating.
• Patch suggestions with approval: For each finding, Claude generates instructions for a targeted patch. Your team reviews it and implements it in Claude Code on the web – nothing is applied without approval.
• Scheduled scans and traceability: Scans can be limited to specific directories or branches and scheduled regularly. Dismissed findings are documented with a reason, and results can be exported as CSV or Markdown or sent to tools such as Slack or Jira via webhooks.

In addition, Claude Code offers further security mechanisms, such as a permission system that makes changes and commands subject to your approval, and centrally managed settings for companies.

Why security is becoming critical for AI code assistants in your company

The professionalisation of AI usage reflects real challenges your team faces every day. What began as an experimental tool now processes protected business logic and in some cases personal data.

Professionalisation and pressure to perform

Your team uses AI assistants for code that goes live with customers tomorrow. At the same time, your compliance and legal departments are asking legitimate questions about liability and traceability. Pure functionality (“Write me this function”) is no longer enough; you need processes that document how AI-generated code is reviewed and approved.

Growing risk awareness

The deeper you integrate AI, the clearer the risks become:

1. Quality defects: AI models also learn from flawed or outdated code. Without review, insecure patterns can end up in your software.
2. Data protection leaks: Developers could accidentally enter real customer data or credentials into prompts to reproduce errors. This data then leaves your company.
3. Licensing risks: Generated code snippets may resemble copyrighted code. Check origin and licence compliance before adopting code.

The legal perspective: focus on the GDPR

As soon as you use Claude Code or Claude Security in your company, the rules of the GDPR apply. Technical security features support you, but they do not release you from your legal obligations.

Data minimisation and purpose limitation

Article 5 of the GDPR is your constant companion. Make sure the AI assistant only accesses the data necessary for the development purpose. Real customer data, production databases or test data containing personal data do not belong in repositories you share for analysis. You can use permissions and project settings to restrict Claude Code’s access to certain directories.

Third-country transfer and prompt privacy

Anthropic is a US company. Your code is transmitted to Anthropic for analysis.

• Data processing agreement: Sign a data processing agreement with Anthropic and check the legal basis for the third-country transfer, such as the EU-US Data Privacy Framework or standard contractual clauses. Make sure your data is not used to train the models in the commercial plans.
• heyData supports you: We check whether the provider’s contractual assurances meet EU requirements and support you with a data protection impact assessment (DPIA) where one is required.

Regulatory classification under the EU AI Act

The EU AI Act entered into force in 2024 and applies in stages. As the person responsible for technology, you need to know how Claude Security fits into this framework.

AI in software development as a risk category

The language model behind Claude Code is a general-purpose AI model. The obligations for it fall on Anthropic as the provider. Your company, as a user, is a so-called deployer. A code assistant is not a high-risk system in itself. However, if you use it to develop software that is itself a high-risk system (e.g. in medical technology), you must meet the strict requirements for quality, documentation and risk management for that product – regardless of whether AI helped write the code.

• AI literacy: Since February 2025, companies must ensure that their employees have sufficient competence in using the AI systems they deploy (Art. 4 AI Act). This also applies to development teams working with Claude Code.
• Human oversight: For high-risk systems, the AI Act requires effective human oversight. Beyond that, it is good practice anyway: Claude Security supports it because no patch is applied without approval.

Security challenges: from prompt injection to liability

The autonomy of tools such as Claude Code creates new attack surfaces. The technical solution is only as strong as the weakest link in your process chain.

The phenomenon of prompt injection

An attacker could try to influence the code assistant via comments in external libraries or manipulated documentation. If Claude analyses such a file, a hidden command could cause the AI to suggest unwanted actions or build a backdoor into your code. Anthropic uses safeguards against prompt injection, but the creative nature of such attacks always requires a vigilant human eye.

Who is liable for the code?

This is the most important question for your management. As things stand, liability for software errors – whether AI-generated or not – lies with your company. Anthropic accepts no liability for the correctness of the code.

Recommended action: Establish clear review processes. No AI-generated code should flow into the main branch without the okay of a developer. Use Claude’s security features as an additional filter, but never as the final authority.

Practical significance for your company: how to proceed

For you as a technical decision-maker, introducing Claude Security involves several operational steps. Simply switching on the feature is not enough.

Evaluation and tool selection

Systematically compare Claude Security with other solutions such as GitHub Copilot Autofix, GitLab Duo or classic SAST tools. Pay particular attention to:

1. Transparency: How traceable are findings and approvals? Can you prove who accepted or rejected which patch?
2. Integration: Can the tool be integrated into your existing security infrastructure (e.g. CI/CD pipelines, SonarQube)?
3. Customisability: Can you define your own security policies specific to your industry?

Integration into your governance processes

The introduction requires adapting your internal guidelines:

• AI policy: Create a binding AI policy that specifies which data (e.g. no real passwords or customer data) may be transmitted to the assistant and which repositories may be connected.
• Training: Train your team to interpret Claude Security’s results correctly and not to adopt patch suggestions “blindly”.

Conclusion: security as a competitive advantage

Claude Security is more than just a new feature – it shows that AI can not only write code but also find vulnerabilities that traditional tools miss. For you, this is an opportunity to improve the quality of your software and reduce risks.

However, responsibility for the final code quality and legal compliance remains with you and your team. Tools can help, but they cannot replace well-thought-out governance processes. When you combine technical excellence with legal certainty, you create a real competitive advantage.

With heyData’s AI compliance, you use AI tools like Claude Code in a legally compliant way: from vetting the provider and creating an AI policy to training your team under Art. 4 AI Act.

Take the first step: Book a free demo now