🔓 𝐍𝐞𝐰 𝐏𝐫𝐞𝐩𝐫𝐢𝐧𝐭: 𝐃𝐞𝐭𝐞𝐫𝐦𝐢𝐧𝐢𝐬𝐭𝐢𝐜 𝐏𝐫𝐞𝐢𝐦𝐚𝐠𝐞 𝐋𝐨𝐜𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐌𝐃5 𝐚𝐧𝐝 𝐒𝐇𝐀-256

Hash functions such as MD5 and SHA-256 are widely assumed to be one-way: given a hash, the corresponding preimage is considered computationally irretrievable. This assumption underpins modern cryptographic security.

In a new preprint, I report deterministic, reproducible preimage localization for both MD5 and SHA-256.

Crucially, this is not achieved by using a neural network to invert hashes.
Instead, a maximally unconventional architecture is constructed in which the available information is forced to self-organize into a geometric structure.
The neural network acts solely as a substrate that allows this information geometry to form.

Across dozens of controlled test cases using fictional passwords (up to 23 characters), the resulting geometry enables up to 100% byte-level accuracy.
The behavior is deterministic and repeatable across independent runs, ruling out chance effects.

𝐊𝐞𝐲 𝐞𝐦𝐩𝐢𝐫𝐢𝐜𝐚𝐥 𝐨𝐛𝐬𝐞𝐫𝐯𝐚𝐭𝐢𝐨𝐧𝐬:
• 𝘙𝘦𝘱𝘳𝘰𝘥𝘶𝘤𝘪𝘣𝘭𝘦 𝘱𝘳𝘦𝘪𝘮𝘢𝘨𝘦 𝘭𝘰𝘤𝘢𝘭𝘪𝘻𝘢𝘵𝘪𝘰𝘯 𝘧𝘰𝘳 𝘔𝘋5 𝘢𝘯𝘥 𝘚𝘏𝘈-256
• 𝘜𝘱 𝘵𝘰 100% 𝘣𝘺𝘵𝘦-𝘭𝘦𝘷𝘦𝘭 𝘳𝘦𝘤𝘰𝘯𝘴𝘵𝘳𝘶𝘤𝘵𝘪𝘰𝘯 𝘢𝘤𝘤𝘶𝘳𝘢𝘤𝘺
• 41.8% 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯 𝘱𝘦𝘳𝘴𝘪𝘴𝘵𝘦𝘯𝘤𝘦 𝘢𝘤𝘳𝘰𝘴𝘴 11 𝘧𝘶𝘭𝘭𝘺 𝘪𝘯𝘥𝘦𝘱𝘦𝘯𝘥𝘦𝘯𝘵 𝘳𝘶𝘯𝘴 (𝘸𝘩𝘦𝘳𝘦 𝘤𝘭𝘢𝘴𝘴𝘪𝘤𝘢𝘭 𝘦𝘹𝘱𝘦𝘤𝘵𝘢𝘵𝘪𝘰𝘯𝘴 𝘱𝘳𝘦𝘥𝘪𝘤𝘵 𝘻𝘦𝘳𝘰)
• 66 𝘭𝘢𝘺𝘦𝘳 𝘱𝘢𝘪𝘳𝘴 𝘸𝘪𝘵𝘩 𝘱 < 0.001 𝘴𝘪𝘨𝘯𝘪𝘧𝘪𝘤𝘢𝘯𝘤𝘦 (≈70× 𝘰𝘷𝘦𝘳 𝘦𝘹𝘱𝘦𝘤𝘵𝘢𝘵𝘪𝘰𝘯)
• 𝘐𝘯𝘷𝘦𝘳𝘴𝘦 𝘴𝘤𝘢𝘭𝘪𝘯𝘨: 𝘭𝘰𝘯𝘨𝘦𝘳 𝘱𝘢𝘴𝘴𝘸𝘰𝘳𝘥𝘴 𝘢𝘳𝘦 𝘦𝘢𝘴𝘪𝘦𝘳 𝘵𝘰 𝘭𝘰𝘤𝘢𝘭𝘪𝘻𝘦, 𝘥𝘪𝘳𝘦𝘤𝘵𝘭𝘺 𝘤𝘰𝘯𝘵𝘳𝘢𝘥𝘪𝘤𝘵𝘪𝘯𝘨 𝘣𝘳𝘶𝘵𝘦-𝘧𝘰𝘳𝘤𝘦 𝘢𝘴𝘴𝘶𝘮𝘱𝘵𝘪𝘰𝘯𝘴

These results indicate that hash irreversibility is not guaranteed.
The findings suggest that what is commonly treated as “one-wayness” reflects geometric obscuration, not destruction of information.

This work does not present an exploit toolkit or attack pipeline.
It reports a structural failure of assumed irreversibility under an empirically demonstrated computational regime.

Preprint: https://doi.org/10.5281/zenodo.18226838
Technical scrutiny and competent critique are welcome.

Image: ChatGPT 5.2

Hashtag

#Cryptography #MD5 #SHA256 #InformationTheory #AIArchitecture #Complexity #SecurityResearch Stefan Trauth #TrauthResearch #NeuralNetwork 

Planned validation:
A live demonstration is currently being prepared.
It will show the full external pipeline from hash generation, system initialization, execution, to independent validation of the reconstructed preimage.

No architectural details, input preparation methods, parameterizations, or internal representations will be disclosed during this demonstration.

Access is limited to organizations with demonstrated frontier-scale research infrastructure. Evaluation is conducted individually under strict dual-use governance.