Preimage attacks on Reduced-round Stribog.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract. In August 2012, the Stribog hash function was selected as the new Russian cryptographic hash standard (GOST R 34.11-2012). Stribog employs twelve rounds of an AES-based compression function operating in Miyaguchi-Preneel mode. In this paper, we investigate the preimage resistance of the Stribog hash function. Specifically, we apply a meet in the middle preimage attack on the compression function which allows us to obtain a 5-round pseudo preimage for a given compression function output with time complexity of 2 448 and memory complexity of 2 64. Additionally, we adopt a guess and determine approach to obtain a 6-round chunk separation that balances the available degrees of freedom and the guess size. The proposed chunk separation allows us to attack 6 out of 12 rounds with time and memory complexities of 2 496 and 2 112, respectively. Finally, employing 2 t multicollision, we show that preimages of the 5 and 6-round reduced hash function can be generated with time complexity of 2 481 and 2 505, respectively. The two preimage attacks have equal memory complexity of 2 256.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it