AI's New Mission: Cracking the Codes That Shaped WWII

The Turing Test, Revisited

When we think of Alan Turing, we often recall his famous test — a benchmark for artificial intelligence that asks whether a machine can exhibit intelligent behavior indistinguishable from a human. But what's less known is the other monumental challenge Turing faced during World War II: cracking the Enigma code used by Nazi Germany.

"The real measure of intelligence is not how well a machine mimics a human, but how effectively it can solve complex problems that shape history."

Now, two independent researchers have demonstrated that modern AI models — specifically OpenAI's Astra and Anthropic's Opus — are capable of solving those very same historical puzzles.

Breaking the Enigma: A New Kind of Cryptanalysis

In a remarkable development, Carter Leffen, a developer with an interest in cryptography, used OpenAI's latest model, Astra, to decode messages that had remained unbroken since 2005. Using nothing more than a database of Enigma-encoded messages, Astra conducted its own archival research, reconstructed the conditions of the original encryptions, and ultimately recovered the plaintext of one such message.

This isn't just an academic exercise — it's a powerful demonstration of how AI is now not only understanding historical data but actively reconstructing lost knowledge. Leffen even created an interactive website to walk users through the process, offering transparency into how Astra achieved its breakthrough.

Validated by Experts

The decoding wasn't just a solo victory. Frode Weierud, a retired electrical engineer and maintainer of the Crypto Cellar, which hosts one of the world's most comprehensive databases of Enigma messages, confirmed Leffen's solution. He was struck by the AI's precision and efficiency.

"GPT–6 Astra is behaving like a very professional cryptanalyst and archive researcher," Weierud wrote. "What it has achieved in two days would take a human researcher weeks or even months."

Weierud's validation was important not just for credibility, but because he noted that the AI's logs referenced messages from a “private collection” — suggesting either shared resources or access to previously unseen archival materials. The question remains: how much of this was actual data, and how much was inference?

Another Breakthrough: Opus in Action

A few days later, another researcher, Jack Willis, demonstrated that Anthropic's Claude Opus 5 could crack a different message using significantly more direct guidance. Willis used known elements like an officer's name to guide the model's search, showing how AI can adapt its methods depending on available context.

Both developments signal a new frontier in AI research — not just as tools for language or computation, but as agents of historical understanding. As Weierud pointed out, only seven Enigma messages remain unbroken, and one message has known plaintext but still eludes full decryption.

The Broader Implications

What's at stake here isn't just the history of cryptography or the capabilities of AI models. It's the very nature of how we preserve, access, and interpret historical knowledge.

This development challenges assumptions about what constitutes a human expert in fields like cryptology. We're witnessing a shift where AI tools may not just assist historians — they may become essential collaborators in solving problems that once required entire teams of specialists.

But it also raises serious questions. If AI can access and interpret classified or archival material, what are the implications for privacy, security, and control over historical records? The technology's ability to reason through complex puzzles might soon make it a key player in fields like law enforcement, intelligence work, and national security.

What Comes Next?

The next logical step is not just decoding more messages — but understanding how these AI systems are actually learning. Are they mimicking historical processes, or are they discovering new ways to interpret the past? If AI models like Astra and Opus continue to evolve, we may see a future where the distinction between machine and human intelligence in problem-solving becomes even more blurred.

As AI becomes increasingly capable of interpreting complex data sets and solving long-standing mysteries, it also becomes more powerful as a historical tool — one that could reshape how we understand both past and future. The age of the AI archaeologist is well underway.

The Human Element in the Machine Age

Despite the impressive capabilities shown by Astra and Opus, this story remains very much grounded in human curiosity and ingenuity. Leffen and Willis didn't simply rely on the models — they provided context, direction, and purpose.

Their work demonstrates that while AI can enhance and accelerate research, it cannot replace the human judgment and ethical reasoning that guide historical interpretation. As these systems become more autonomous, ensuring responsible use becomes ever more critical.

For now, we're watching history unfold in real time — not through military victories or political shifts, but through the quiet triumph of computational logic meeting historical mystery.