---
title: "Hidden Software Bugs: AI Model Claude Finds Hundreds of Flaws"
description: "Anthropic announced that its Claude model verified the security of 123 open-source libraries and discovered hundreds of hidden bugs using mathematical proofs."
date: 2026-10-23T14:38:49.051Z
lang: en
url: https://xab.info/en/posts/claude-finds-hidden-software-bugs
tags: [claude, anthropic, artificial-intelligence, cybersecurity, software-testing, programming]
author: "Alexander Buran"
publisher: "XAB.info"
---

# Hidden Software Bugs: AI Model Claude Finds Hundreds of Flaws

![Laptop on a wooden desk showing the Claude artificial intelligence interface and code on the screen](https://xab.info/media/2026/10/23/claude-nashel-skrytye-oshibki-v-po/claude-nashel-skrytye-oshibki-v-po-1.webp)

## Key Points

- Claude model verified the security of 123 open-source libraries.
- AI used mathematical proofs to analyze RISC-V assembly code.
- Defects missed by testers for years were uncovered.
- The model is capable of automatically fixing discovered errors.

Anthropic has officially announced the successful application of its Claude model to verify the security properties of 123 open-source libraries. Using advanced mathematical proofs, the artificial intelligence was able to uncover hundreds of hidden errors and vulnerabilities that traditional testing methods had missed for years.

### Mathematical Approach to Code Verification

As part of a joint project with Theorem, a firm specializing in program verification, Anthropic developers applied rigorous mathematical proofs directly to compiled machine code. Traditional testing and fuzzing tools generate large volumes of input data but are physically unable to exhaust all possible combinations to guarantee absolute safety.

To solve this task, the Claude model transformed existing fuzz tests into precise mathematical specifications. This allowed the artificial intelligence to generate proofs demonstrating that 239 entry points across 123 libraries are guaranteed not to fail under specific conditions within RISC-V assembly code.

### Automation of Verification and Bug Fixing

For independent verification of the generated specification-compliance proofs, researchers utilized a separate tool called Rocq. This approach completely freed developers from the necessity of manually inspecting every single line of code.

Furthermore, the neural network demonstrated the ability not only to find defects but also to fix them independently and create new proofs for updated software. This significantly accelerates the development cycle and enhances the overall reliability of critical components.

### Discovered Vulnerabilities and Method Limitations

The new methodology successfully exposed complex defects that had eluded testers for years. These included an underflow counter capable of triggering out-of-bounds writes, an image decoder error, out-of-bounds reads, and a logical error bypassing file upload restriction functions.

Despite the impressive results, Anthropic specialists emphasize that formally verified software does not become completely flawless. The obtained guarantees apply exclusively to the specific properties, input data, and assumptions described in each individual proof within a simulated Linux environment.

### Significance of the Technology for Future Development

The integration of artificial intelligence models into the mathematical verification process opens new horizons for global cybersecurity. It is expected that further advancements in technology and the reusability of proofs will drastically reduce the financial and time costs of auditing complex software systems.

## Fact-Check & Sources

- [Скрытые ошибки в ПО: Claude нашел сотни багов, которые тесты пропускали годами](https://www.rbc.ua/ukr/news/prihovani-pomilki-pz-claude-znayshov-sotni-1792763196.html) - The primary source confirms all details of Anthropic's statement regarding the verification of 123 libraries, the use of the Claude model, and mathematical proofs.

## FAQ

### What task did the Claude model perform?

Claude verified the security of 123 open-source libraries by transforming fuzz tests into mathematical specifications and finding hundreds of hidden errors.

### What tools were used to verify the results?

Researchers used a separate independent tool called Rocq to check the generated proofs.

### Does software become completely safe after such verification?

No, the obtained guarantees apply only to the specific properties, input data, and assumptions described in each individual proof.