diff --git a/.codespell-ignore-words.txt b/.codespell-ignore-words.txt
index 5c0c89e5..8957ca0c 100644
--- a/.codespell-ignore-words.txt
+++ b/.codespell-ignore-words.txt
@@ -4,7 +4,7 @@ subspecs
 crate
 crates
 ethereum
-poseidon2
+poseidon1
 keccak
 blake
 merkle
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/0.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/0.json
index 78197d5a..32826f21 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/0.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/0.json
@@ -1,6 +1,6 @@
 {
-  "attestation_public": "cd64341d83f28533f239153535b45209592342325ed31a5792b2e61935648748d41c384850baf6386c43bf19bfb63f53eb2c8c0b",
-  "attestation_secret": 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-  "proposal_public": "5eba321a84f55461e2c0e94036d24e5107720876752d5c4f6e03183a7e7f1856e372c60dbc6fbc0450c26e58ba402f1da6952a73",
-  "proposal_secret": 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+  "attestation_secret": 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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/1.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/1.json
index 8e28eb3b..c970912e 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/1.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/1.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/10.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/10.json
index 3d3279fa..20c2c0cc 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/10.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/10.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/11.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/11.json
index 1e369cd9..cceadea3 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/11.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/11.json
@@ -1,6 +1,6 @@
 {
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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/2.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/2.json
index 7e0e66b1..55e1429c 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/2.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/2.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/3.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/3.json
index ace50932..53c85794 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/3.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/3.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/4.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/4.json
index 3f93f7c8..b5150624 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/4.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/4.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/5.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/5.json
index 097ad2b3..e474dbe6 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/5.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/5.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/6.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/6.json
index b497ddbc..24867bdb 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/6.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/6.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/7.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/7.json
index 0fbed6a7..f00a6ebc 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/7.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/7.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/8.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/8.json
index 8caa7aba..b2715fad 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/8.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/8.json
@@ -1,6 +1,6 @@
 {
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+  "proposal_public": "694a122a545ea663b52d8d7e2b5581367f475305d97242330c9ed00f5d4bd2421da80c18208cde128ca16944308ee87d54adf37a",
+  "proposal_secret": 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 }
\ No newline at end of file
diff --git a/packages/testing/src/consensus_testing/test_keys/test_scheme/9.json b/packages/testing/src/consensus_testing/test_keys/test_scheme/9.json
index 301828c7..a2d98e46 100644
--- a/packages/testing/src/consensus_testing/test_keys/test_scheme/9.json
+++ b/packages/testing/src/consensus_testing/test_keys/test_scheme/9.json
@@ -1,6 +1,6 @@
 {
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"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+  "proposal_public": "67982a225369f8566554ac5f0aee8535ce298b5708a8801a6f96ae15c7234c154e81f67a9a658e37ab3e18305121b730d7f6253b",
+  "proposal_secret": "6f6d68afd1b387ed3204f7ab6c0d398d4e9a00b0391c9051d2bf5396e63a5c014e81f67a9a658e37ab3e18305121b730d7f6253b00000000000000007000000000000000580000000000000000000000fc0200004007000008000000000000000400000000000000140000001400000020010000ac010000f80100004402000000000000000000000c0000005c15b5369fbb8245c1fd6a01bbda56741a4b201209f11967ec1ef809aaa52f054f1e7b3ae960737c5e6bec5d2f3d8073151f621b23e3fa2fe2c2b95d570b0e0457bb2c604654574e2d1fd704114b55234ab348191311706870771e0645d2ec2bbb085677c1374e076b08583a37525c1c7e59f72ae2b7a412c8fe4341d9de2a2eacecaf070fd6840cf6b2180bf8252a406a09bf6b745ebe773421ac5cc96496168c897406da70e644c0d5d101cc7b415c583a857a5170ca4bd51f40374718ab2b1d70607afab50a2d7ad6e05455c55d0297c41d7bc3207431832bd85f7067287ac31d674d0ba1a82602bff25411ce9f4b6fc15f010f342a6cafe385467c33f46500000000000000000c0000007237915ca1bbdd4af5d02b7eee8e2305007ceb27d7e42f4296ce7d20e069dd368815790571a59d52ada6277047a4d4656c7821366909fa2a80a43720b2e9ed42a5e52f6d06af4d799448796fa2c4f52a229aed5f80f3ad428cf3c91091700b4f92f2937777afcc686631b9582e741f25c0becc14b1f5080df4b1d62b26330c5700000000000000000c00000038ded37e4ac0f64deda4ff423dd25c7947392a778317232faaa5317176f3017a5c1c566ba4d1044790cb914978bd487e1fac62226234e212bec81140a086b51600000000000000000c0000008fc4d226ef60851f8513d9780eab3b6e0e084b24844cad4ebd0ef330e4de6f06bc8cdc50129f394be45e390211821039c2755f2e6afada11e676a87eb19a1b3d00000000000000000c00000067982a225369f8566554ac5f0aee8535ce298b5708a8801a6f96ae15c7234c15f93f7430737908266295152ffd7fbb7aecc33a611cfd9968b07b9755e39e0972080000000000000000000000000000001400000014000000200200002c030000b80300000404000000000000000000000c00000054f9532ab840a22dbf34b4234ddda34e7ba3862063c3587ca89e280bb70fb71a65cedb0845856c0caebc4d6958364d5ed049710955c4522b4878ba1db84a731f56acc93c2797626c8a2d377ade1142249bd82408615db06daa39f83796d8b146c9fbbe114e79f66758f0654d0f2cea105d531f02c1adea7061bcf9402a1d854240376259e3d37c1f9244a035439636751851332960b5f06bdc592512b508ac553dc8953a63c0f0239190290194f91f6ef4539931ad6c982d0cdb5c6aeb95ae260303882f1915912c4364ec383e0bc21a7ba7e52410ee072e24b3427a3741c238b338e812011c9368e2a86228b041171e73b0d96a7c04201ad775be5759e9362f0fb8da692024c65c31c52763f6fbe676332b1c75f6a10613d142624503d19d42f2665265faeb5b253cda6c3b2712ea109aab16784b7e8e1f198b314e243f0076857f981199e76016e7d0d345d7aae8505b66261aa18697644a7dad26175b2445b5fb3434c50c9e630341227a6b0f7e24daf1ed4e658ddd15f085fe2b023e4654b087be04c6bde73c151b42625ace356498ce0a72f76cc40fc7f62c288b45b11c54a136578b409945668c5c680f18ef6f53603513a4816d66316e8648e4330d219e9445069d842940d58feb662e7d871eb03e7475d70e726e76a5070f8c136f6a9906446b8c25470788e4a649c72239428d03c03587d4eb1585330e77aeda101e00000000000000000c000000b4d9fd452c0ff969b47a1a69c69815797cd4414b2f006b195db0e76c0e84d74379d922204b3dee447b2da52aef9ea360ea324d6c4428cf50b81e520e76dec046c9d9953a444504360d2db176eba5270b54f4e44d4ecc7c641a32ef386085c51c12adbb36482f9c4512aa911634c59955bf77e67e85c4165ee2e0b910e4e12f0cbd78a8035ee9cf3673e72679c827d8620ce96434a3c52b5596b66631b6b2ef24d3ffb96a3b766e21fa949c78ab38605a6c8afe24b71ce65a81e50b5a76798a410eca6e2987532d2bb563194fd470cd09b9ef2104691d43111d390a17295fd22cead965295157a97c816f645b8ebec13de59315164205202cf329b1413518671900000000000000000c0000000f482940fe58c207c11ef1478f2c4c42e8d30f4b760f1c48ba869e63092eba1d20b00515d220f0784843667188b98a6d5ad8f47dc4e0d60cbac9dd6851a4625b1baacc33882d0a5da137515600e95a7bf0b32d1226026157f71eb709d525a555eea0ab2cccd32611c79e9b4e7f582c5d8bd63a1d4fa85f75ca7e9d7df5ad013700000000000000000c000000ec460f20fef0b6407683727822c8eb1aedc90d3902dc88308a1ebd0760bb8e64a3fd410a2f809a4d5e58a02bfc46726b0aa4e4092d6b1376864ca93fd9409b1300000000000000000c0000005c15b5369fbb8245c1fd6a01bbda56741a4b201209f11967ec1ef809aaa52f05080000000000000000000000000000001400000014000000200200002c030000b80300000404000010000000000000000c000000045b42549fc3a85c80a9583e52b0752c327c8f2de6a1c9657828ec0fa054b4790ac03c0aa38ee5434d577a3c0632cb41e2312f6a95c97d0f3da979121fd1da41fc8adb4b9f4d3c188453ff58f0328d48e5491d58d6285867c8a2913175ddbc6401ee0509a176407b8201bb3cfdddd32b845e0d7a6f939e6ac13c1f00baae6522d9f3d5478257d608b582fe396dd5772626cffa53503b59382ce0924cdf2e50737fb5b5106292400eb1f64338b52cd7422e91e43daf7e1b0d1c8e5b3b26921f25d62f5d708d7b00424a19253851bede72efe1a7594bf5244d66c121339589be5826e59849cab15216d87e115ce6ea803e9d29f313da59f5177fe5e14052170a0b1c53962953df0278c0551815d2452a3c9aae0530c3a8ca2e2bc56e6054a0b377cda8796dd820393c62c5243976d55a550600e2208d1479480279c70f1a2e8521c8b83b68d5b7e51a377f96288edb9d6e77c74235dfca3622a266b1735c0b7b0255fd39132399b32055733905795c3c5e6fc4144909948342bc4e4640cedd7200585c74244dbd315424f1243235c3d25a5cd0b26d4be3355eb350226494d55f7c1ab017332fb030314e566439e910db2dddbf7e147e410f1bb26e323da45bb13caaa68714918ce92ee7261220087d4573780c880c3d88d81aae47557c5f99e74c7616687024883a49cd23a44392d7aa3c580c247c7b3c2a6283e72829957d646d08000000000000000c0000001c53b52ade04774c41e26373d492b120e4119a5a46d6aa01372cf026428a4008609aaf06c755a85ff637fc729d407e043d7e2670e9350b796165c4212714526297121a3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 }
\ No newline at end of file
diff --git a/src/lean_spec/subspecs/containers/__init__.py b/src/lean_spec/subspecs/containers/__init__.py
index d5588d5b..6dffe32d 100644
--- a/src/lean_spec/subspecs/containers/__init__.py
+++ b/src/lean_spec/subspecs/containers/__init__.py
@@ -5,7 +5,7 @@
 efficient merkleization.
 
 Hash functions used for merkleization differ by devnet. Early devnets use
-SHA256. Later devnets will switch to Poseidon2 for better SNARK compatibility.
+SHA256. Later devnets will switch to Poseidon1 for better SNARK compatibility.
 """
 
 from .attestation import (
diff --git a/src/lean_spec/subspecs/poseidon1/__init__.py b/src/lean_spec/subspecs/poseidon1/__init__.py
new file mode 100644
index 00000000..04f4932f
--- /dev/null
+++ b/src/lean_spec/subspecs/poseidon1/__init__.py
@@ -0,0 +1,15 @@
+"""Specification for the Poseidon1 permutation."""
+
+from .permutation import (
+    PARAMS_16,
+    PARAMS_24,
+    Poseidon1,
+    Poseidon1Params,
+)
+
+__all__ = [
+    "Poseidon1",
+    "Poseidon1Params",
+    "PARAMS_16",
+    "PARAMS_24",
+]
diff --git a/src/lean_spec/subspecs/poseidon1/constants.py b/src/lean_spec/subspecs/poseidon1/constants.py
new file mode 100644
index 00000000..39c4159b
--- /dev/null
+++ b/src/lean_spec/subspecs/poseidon1/constants.py
@@ -0,0 +1,1219 @@
+"""Round constants for the Poseidon1 permutation over the KoalaBear field."""
+
+from __future__ import annotations
+
+from ..koalabear.field import Fp
+
+# For width 16: 28 rounds x 16 = 448 constants
+# Layout: initial_full (4 x 16) + partial (20 x 16) + terminal_full (4 x 16)
+_RAW_CONSTANTS_16: list[int] = [
+    # Initial full rounds (4 rounds x 16 constants)
+    0x7EE56A48,
+    0x11367045,
+    0x12E41941,
+    0x7EBBC12B,
+    0x1970B7D5,
+    0x662B60E8,
+    0x3E4990C6,
+    0x679F91F5,
+    0x350813BB,
+    0x00874AD4,
+    0x28A0081A,
+    0x18FA5872,
+    0x5F25B071,
+    0x5E5D5998,
+    0x5E6FD3E7,
+    0x5B2E2660,
+    0x6F1837BF,
+    0x3FE6182B,
+    0x1EDD7AC5,
+    0x57470D00,
+    0x43D486D5,
+    0x1982C70F,
+    0x0EA53AF9,
+    0x61D6165B,
+    0x51639C00,
+    0x2DEC352C,
+    0x2950E531,
+    0x2D2CB947,
+    0x08256CEF,
+    0x1A0109F6,
+    0x1F51FAF3,
+    0x5CEF1C62,
+    0x3D65E50E,
+    0x33D91626,
+    0x133D5A1E,
+    0x0FF49B0D,
+    0x38900CD1,
+    0x2C22CC3F,
+    0x28852BB2,
+    0x06C65A02,
+    0x7B2CF7BC,
+    0x68016E1A,
+    0x15E16BC0,
+    0x5248149A,
+    0x6DD212A0,
+    0x18D6830A,
+    0x5001BE82,
+    0x64DAC34E,
+    0x5902B287,
+    0x426583A0,
+    0x0C921632,
+    0x3FE028A5,
+    0x245F8E49,
+    0x43BB297E,
+    0x7873DBD9,
+    0x3CC987DF,
+    0x286BB4CE,
+    0x640A8DCD,
+    0x512A8E36,
+    0x03A4CF55,
+    0x481837A2,
+    0x03D6DA84,
+    0x73726AC7,
+    0x760E7FDF,
+    # Partial rounds (20 rounds x 16 constants)
+    0x54DFEB5D,
+    0x7D40AFD6,
+    0x722CB316,
+    0x106A4573,
+    0x45A7CCDB,
+    0x44061375,
+    0x154077A5,
+    0x45744FAA,
+    0x4EB5E5EE,
+    0x3794E83F,
+    0x47C7093C,
+    0x5694903C,
+    0x69CB6299,
+    0x373DF84C,
+    0x46A0DF58,
+    0x46B8758A,
+    0x3241EBCB,
+    0x0B09D233,
+    0x1AF42357,
+    0x1E66CEC2,
+    0x43E7DC24,
+    0x259A5D61,
+    0x27E85A3B,
+    0x1B9133FA,
+    0x343E5628,
+    0x485CD4C2,
+    0x16E269F5,
+    0x165B60C6,
+    0x25F683D9,
+    0x124F81F9,
+    0x174331F9,
+    0x77344DC5,
+    0x5A821DBA,
+    0x5FC4177F,
+    0x54153BF5,
+    0x5E3F1194,
+    0x3BDBF191,
+    0x088C84A3,
+    0x68256C9B,
+    0x3C90BBC6,
+    0x6846166A,
+    0x03F4238D,
+    0x463335FB,
+    0x5E3D3551,
+    0x6E59AE6F,
+    0x32D06CC0,
+    0x596293F3,
+    0x6C87EDB2,
+    0x08FC60B5,
+    0x34BCCA80,
+    0x24F007F3,
+    0x62731C6F,
+    0x1E1DB6C6,
+    0x0CA409BB,
+    0x585C1E78,
+    0x56E94EDC,
+    0x16D22734,
+    0x18E11467,
+    0x7B2C3730,
+    0x770075E4,
+    0x35D1B18C,
+    0x22BE3DB5,
+    0x4FB1FBB7,
+    0x477CB3ED,
+    0x7D5311C6,
+    0x5B62AE7D,
+    0x559C5FA8,
+    0x77F15048,
+    0x3211570B,
+    0x490FEF6A,
+    0x77EC311F,
+    0x2247171B,
+    0x4E0AC711,
+    0x2EDF69C9,
+    0x3B5A8850,
+    0x65809421,
+    0x5619B4AA,
+    0x362019A7,
+    0x6BF9D4ED,
+    0x5B413DFF,
+    0x617E181E,
+    0x5E7AB57B,
+    0x33AD7833,
+    0x3466C7CA,
+    0x6488DFF4,
+    0x71F068F4,
+    0x056E891F,
+    0x04F1ECCC,
+    0x663257D5,
+    0x671E31B9,
+    0x5871987C,
+    0x280C109E,
+    0x2A227761,
+    0x350A25E9,
+    0x5B91B1C4,
+    0x7A073546,
+    0x01826270,
+    0x53A67720,
+    0x0ED4B074,
+    0x34CF0C4E,
+    0x6E751E88,
+    0x29BD5F59,
+    0x49EC32DF,
+    0x7693452B,
+    0x3CF09E58,
+    0x6BA0E2BF,
+    0x7AB93ACF,
+    0x3CE597DF,
+    0x536E3D42,
+    0x147A808D,
+    0x5E32EB56,
+    0x5A203323,
+    0x50965766,
+    0x6D44B7C5,
+    0x6698636A,
+    0x57B84F9F,
+    0x554B61B9,
+    0x6DA0AB28,
+    0x1585B6AC,
+    0x6705A2B4,
+    0x152872F6,
+    0x0F4409FD,
+    0x23A9DD60,
+    0x6F2B18D4,
+    0x65AC9FD4,
+    0x2F0EFBEA,
+    0x591E67FD,
+    0x217CA19B,
+    0x469C90CA,
+    0x03D60EF5,
+    0x4EA7857E,
+    0x07C86A4F,
+    0x288ED461,
+    0x2FE51B22,
+    0x7E293614,
+    0x2C4BEB85,
+    0x5B0B7D11,
+    0x1E17DFF6,
+    0x089BEAE1,
+    0x0A5ACF1A,
+    0x2FC33D8F,
+    0x60422DC6,
+    0x6E1DC939,
+    0x635351B9,
+    0x55522FC0,
+    0x3EB94EF7,
+    0x2A24A65C,
+    0x2E139C76,
+    0x51391144,
+    0x78CC0742,
+    0x579538F9,
+    0x44DE9AAE,
+    0x3C2F1E2E,
+    0x195747BE,
+    0x2496339C,
+    0x650B2E39,
+    0x52899665,
+    0x6CB35558,
+    0x0F461C1C,
+    0x70F6B270,
+    0x3FAAA36F,
+    0x62E3348A,
+    0x672167CB,
+    0x394C880B,
+    0x2A46BA82,
+    0x63FFB74A,
+    0x1CF875D6,
+    0x53D12772,
+    0x036A4552,
+    0x3BDD9F2B,
+    0x02F72C24,
+    0x02B6006C,
+    0x077FE158,
+    0x1F9D6EA4,
+    0x20904D6F,
+    0x5D6534FA,
+    0x066D8974,
+    0x6198F1F4,
+    0x26301AB4,
+    0x41F274C2,
+    0x00EAC15C,
+    0x28B54B47,
+    0x2339739D,
+    0x48C6281C,
+    0x4ED935FC,
+    0x3F9187FA,
+    0x4A1930A6,
+    0x3AD4D736,
+    0x0F3F1889,
+    0x635A388F,
+    0x2862C145,
+    0x277ED1E8,
+    0x4DB23CAD,
+    0x1F1B11F5,
+    0x1F3DBA2B,
+    0x1C26EB4E,
+    0x0F7F5546,
+    0x6CD024B0,
+    0x67C47902,
+    0x793B8900,
+    0x0E8A283C,
+    0x4590B7EA,
+    0x6F567A2B,
+    0x5DC97300,
+    0x15247BC6,
+    0x50567FCB,
+    0x133EFF84,
+    0x547DC2EF,
+    0x34EB3DBB,
+    0x12402317,
+    0x66C6AE49,
+    0x174338B6,
+    0x24251008,
+    0x1B514927,
+    0x062D98D6,
+    0x7AF30BBC,
+    0x26AF15E8,
+    0x70D907A3,
+    0x5DFC5CAC,
+    0x731F27EC,
+    0x53AA7D3F,
+    0x63AB0EC6,
+    0x216053F4,
+    0x18796B39,
+    0x19156AFD,
+    0x5EEA6973,
+    0x6704C6A9,
+    0x0DCE002B,
+    0x331169C0,
+    0x714D7178,
+    0x3DDAFFAF,
+    0x7E464957,
+    0x20CA59EA,
+    0x679820C9,
+    0x42EF21A1,
+    0x798EA089,
+    0x14A74FA3,
+    0x0C06CF18,
+    0x6A4C8D52,
+    0x620F6D81,
+    0x2220901A,
+    0x5277BB90,
+    0x230BF95E,
+    0x0AD8847A,
+    0x5E96E8B6,
+    0x77B4056E,
+    0x70A50D2C,
+    0x5F0EED59,
+    0x3646C4DF,
+    0x10EB9A87,
+    0x21EED6B7,
+    0x534ADD36,
+    0x6E3E7421,
+    0x2B25810E,
+    0x1D8F707B,
+    0x45318A1A,
+    0x677F8FF2,
+    0x0258C9E0,
+    0x4CD02A00,
+    0x2E24FF15,
+    0x634A715D,
+    0x4AC01E59,
+    0x601511E1,
+    0x26E9C01A,
+    0x4C165C6E,
+    0x57CD1140,
+    0x3AC6543B,
+    0x6787D847,
+    0x037DFBF9,
+    0x6DD9D079,
+    0x4D24B281,
+    0x2A6F407D,
+    0x0131DF8E,
+    0x4B8A7896,
+    0x23700858,
+    0x2CF5E534,
+    0x12AAFC3F,
+    0x54568D03,
+    0x1A250735,
+    0x5331686D,
+    0x4CE76D91,
+    0x799C1A8C,
+    0x2B7A8AC9,
+    0x60AEE672,
+    0x74F7421C,
+    0x3C42146D,
+    0x26D369C5,
+    0x4AE54A12,
+    0x7EEA16D1,
+    0x5CE3EAE8,
+    0x69F28994,
+    0x262B8642,
+    0x610D4CC4,
+    0x5E1AF21C,
+    0x1A8526D0,
+    0x316B127B,
+    0x3576FE5D,
+    0x02D968A0,
+    0x4BA00F51,
+    0x40BED993,
+    0x377FB907,
+    0x7859216E,
+    0x1931D9D1,
+    0x53B0934E,
+    0x71914FF7,
+    0x4EABAE6C,
+    0x7196468E,
+    0x164B3CC2,
+    0x58CB66C0,
+    0x4C147307,
+    0x6B3AFCCD,
+    0x4236518B,
+    0x4AD85605,
+    0x291382E1,
+    0x1E89B6CF,
+    0x5E16C3A8,
+    0x2E675921,
+    0x24300954,
+    0x05E555C3,
+    0x78880A24,
+    # Terminal full rounds (4 rounds x 16 constants)
+    0x763A3125,
+    0x4F53B240,
+    0x18B7FA43,
+    0x2BBE8A73,
+    0x1C9A12F2,
+    0x3F6FD40D,
+    0x0E1D4EC4,
+    0x1361C64D,
+    0x09A8F470,
+    0x03D23A40,
+    0x109AD290,
+    0x28C2FB88,
+    0x3B6498F2,
+    0x74D8BE57,
+    0x6A4277D2,
+    0x18C2B3D4,
+    0x6252C30C,
+    0x07CC2560,
+    0x209FE15B,
+    0x52A55FAC,
+    0x4DF19EB7,
+    0x02521116,
+    0x5E414FF1,
+    0x3CD9A1F4,
+    0x005AAD15,
+    0x27A53F00,
+    0x72BBE9CB,
+    0x71D8BD7D,
+    0x4194B79A,
+    0x48E87A72,
+    0x3341553C,
+    0x63D34FAA,
+    0x132A01E3,
+    0x3833E2D9,
+    0x49726E04,
+    0x054957F8,
+    0x7B71BCE4,
+    0x73EEC57D,
+    0x556E5533,
+    0x1FA93FDE,
+    0x346A8CA8,
+    0x1162DFDE,
+    0x5C30D028,
+    0x094A4294,
+    0x3052DCDA,
+    0x37988498,
+    0x51F06B97,
+    0x65848779,
+    0x7599B0D4,
+    0x436FDABC,
+    0x66C5B77D,
+    0x40C86A9E,
+    0x27E7055B,
+    0x6D0DD9D8,
+    0x7E5598B5,
+    0x1A4D04F3,
+    0x5E3B2BC7,
+    0x533B5B2F,
+    0x3E33A125,
+    0x664D71CE,
+    0x382E6C2A,
+    0x24C4EB6E,
+    0x13F246F7,
+    0x07E2D7EF,
+]
+
+# For width 24: 31 rounds x 24 = 744 constants
+# Layout: initial_full (4 x 24) + partial (23 x 24) + terminal_full (4 x 24)
+_RAW_CONSTANTS_24: list[int] = [
+    # Initial full rounds (4 rounds x 24 constants)
+    0x1D0939DC,
+    0x6D050F8D,
+    0x628058AD,
+    0x2681385D,
+    0x3E3C62BE,
+    0x032CFAD8,
+    0x5A91BA3C,
+    0x015A56E6,
+    0x696B889C,
+    0x0DBCD780,
+    0x5881B5C9,
+    0x2A076F2E,
+    0x55393055,
+    0x6513A085,
+    0x547AC78F,
+    0x4281C5B8,
+    0x3E7A3F6C,
+    0x34562C19,
+    0x2C04E679,
+    0x0ED78234,
+    0x5F7A1AA9,
+    0x0177640E,
+    0x0EA4F8D1,
+    0x15BE7692,
+    0x6EAFDD62,
+    0x71A572C6,
+    0x72416F0A,
+    0x31CE1AD3,
+    0x2136A0CF,
+    0x1507C0EB,
+    0x1EB6E07A,
+    0x3A0CCF7B,
+    0x38E4BF31,
+    0x44128286,
+    0x6B05E976,
+    0x244A9B92,
+    0x6E4B32A8,
+    0x78EE2496,
+    0x4761115B,
+    0x3D3A7077,
+    0x75D3C670,
+    0x396A2475,
+    0x26DD00B4,
+    0x7DF50F59,
+    0x0CB922DF,
+    0x0568B190,
+    0x5BD3FCD6,
+    0x1351F58E,
+    0x52191B5F,
+    0x119171B8,
+    0x1E8BB727,
+    0x27D21F26,
+    0x36146613,
+    0x1EE817A2,
+    0x71ABE84E,
+    0x44B88070,
+    0x5DC04410,
+    0x2AEAA2F6,
+    0x2B7BB311,
+    0x6906884D,
+    0x0522E053,
+    0x0C45A214,
+    0x1B016998,
+    0x479B1052,
+    0x3ACC89BE,
+    0x0776021A,
+    0x7A34A1F5,
+    0x70F87911,
+    0x2CAF9D9E,
+    0x026AFF1B,
+    0x2C42468E,
+    0x67726B45,
+    0x09B6F53C,
+    0x73D76589,
+    0x5793EEB0,
+    0x29E720F3,
+    0x75FC8BDF,
+    0x4C2FAE0E,
+    0x20B41DB3,
+    0x7E491510,
+    0x2CADEF18,
+    0x57FC24D6,
+    0x4D1ADE4A,
+    0x36BF8E3C,
+    0x3511B63C,
+    0x64D8476F,
+    0x732BA706,
+    0x46634978,
+    0x0521C17C,
+    0x5EE69212,
+    0x3559CBA9,
+    0x2B33DF89,
+    0x653538D6,
+    0x5FDE8344,
+    0x4091605D,
+    0x2933BDDE,
+    # Partial rounds (23 rounds x 24 constants)
+    0x1395D4CA,
+    0x5DBAC049,
+    0x51FC2727,
+    0x13407399,
+    0x39AC6953,
+    0x45E8726C,
+    0x75A7311C,
+    0x599F82C9,
+    0x702CF13B,
+    0x026B8955,
+    0x44E09BBC,
+    0x2211207F,
+    0x5128B4E3,
+    0x591C41AF,
+    0x674F5C68,
+    0x3981D0D3,
+    0x2D82F898,
+    0x707CD267,
+    0x3B4CCA45,
+    0x2AD0DC3C,
+    0x0CB79B37,
+    0x23F2F4E8,
+    0x3DE4E739,
+    0x7D232359,
+    0x389D82F9,
+    0x259B2E6C,
+    0x45A94DEF,
+    0x0D497380,
+    0x5B049135,
+    0x3C268399,
+    0x78FEB2F9,
+    0x300A3EEC,
+    0x505165BB,
+    0x20300973,
+    0x2327C081,
+    0x1A45A2F4,
+    0x5B32EA2E,
+    0x2D5D1A70,
+    0x053E613E,
+    0x5433E39F,
+    0x495529F0,
+    0x1EAA1AA9,
+    0x578F572A,
+    0x698EDE71,
+    0x5A0F9DBA,
+    0x398A2E96,
+    0x0C7B2925,
+    0x2E6B9564,
+    0x026B00DE,
+    0x7644C1E9,
+    0x5C23D0BD,
+    0x3470B5EF,
+    0x6013CF3A,
+    0x48747288,
+    0x13B7A543,
+    0x3EAEBD44,
+    0x0004E60C,
+    0x1E8363A2,
+    0x2343259A,
+    0x69DA0C2A,
+    0x06E3E4C4,
+    0x1095018E,
+    0x0DEEA348,
+    0x1F4C5513,
+    0x4F9A3A98,
+    0x3179112B,
+    0x524ABB1F,
+    0x21615BA2,
+    0x23AB4065,
+    0x1202A1D1,
+    0x21D25B83,
+    0x6ED17C2F,
+    0x391E6B09,
+    0x5E4ED894,
+    0x6A2F58F2,
+    0x5D980D70,
+    0x3FA48C5E,
+    0x1F6366F7,
+    0x63540F5F,
+    0x6A8235ED,
+    0x14C12A78,
+    0x6EDDE1C9,
+    0x58CE1C22,
+    0x718588BB,
+    0x334313AD,
+    0x7478DBC7,
+    0x647AD52F,
+    0x39E82049,
+    0x6FEE146A,
+    0x082C2F24,
+    0x1F093015,
+    0x30173C18,
+    0x53F70C0D,
+    0x6028AB0C,
+    0x2F47A1EE,
+    0x26A6780E,
+    0x3540BC83,
+    0x1812B49F,
+    0x5149C827,
+    0x631DD925,
+    0x001F2DEA,
+    0x7DC05194,
+    0x3789672E,
+    0x7CABF72E,
+    0x242DBE2F,
+    0x0B07A51D,
+    0x38653650,
+    0x50785C4E,
+    0x60E8A7E0,
+    0x07464338,
+    0x3482D6E1,
+    0x08A69F1E,
+    0x3F2AFF24,
+    0x5814C30D,
+    0x13FECAB2,
+    0x61CB291A,
+    0x68C8226F,
+    0x5C757EEA,
+    0x289B4E1E,
+    0x0198D9B3,
+    0x070A92E6,
+    0x2F1B6CB3,
+    0x535008BB,
+    0x35AF339A,
+    0x7A38E92C,
+    0x4FF71B5C,
+    0x3B193ABA,
+    0x34D12A1E,
+    0x17E94240,
+    0x2EC214DC,
+    0x43E09385,
+    0x7D546918,
+    0x71AF9DFD,
+    0x761A21BB,
+    0x43FDC986,
+    0x05DDA714,
+    0x2D0E78B5,
+    0x1FCD387B,
+    0x76E10A76,
+    0x28A112D5,
+    0x1A7BD787,
+    0x40190DE2,
+    0x2E27906A,
+    0x2033954E,
+    0x20AFD2C8,
+    0x71B5ECB2,
+    0x57828FB3,
+    0x222851D8,
+    0x732DF0E9,
+    0x73F48435,
+    0x7E63EA98,
+    0x058BE348,
+    0x229E7A5F,
+    0x04576A2F,
+    0x29939F10,
+    0x7AFD830A,
+    0x5D6DD961,
+    0x0EB65D94,
+    0x39DA2B79,
+    0x36BCE8BA,
+    0x5F53A7D4,
+    0x383B1CD2,
+    0x1FDC3C5F,
+    0x7D9CA544,
+    0x77480711,
+    0x36C51A1A,
+    0x009EA59B,
+    0x731B17FD,
+    0x201359BD,
+    0x22BF6499,
+    0x610F1A29,
+    0x3C73AA45,
+    0x6A092599,
+    0x1C7CB703,
+    0x79533459,
+    0x7EF62D86,
+    0x5AB925AB,
+    0x67722AB1,
+    0x33CA4CFF,
+    0x007F7DCE,
+    0x0EEAC41E,
+    0x4724BEA7,
+    0x45EAF64F,
+    0x21A6C90F,
+    0x094B4150,
+    0x0D942630,
+    0x18712C30,
+    0x3A470338,
+    0x6EBA7720,
+    0x487827C8,
+    0x77013A6D,
+    0x4AD07390,
+    0x57D802EA,
+    0x720F5FD4,
+    0x5B8A5357,
+    0x3649DB1F,
+    0x35EA476A,
+    0x4C6589F5,
+    0x02C9F31F,
+    0x16D04670,
+    0x62D74B20,
+    0x1DE813CC,
+    0x189966ED,
+    0x527ADD06,
+    0x1704F5AF,
+    0x000F1703,
+    0x00152A1F,
+    0x2F49A365,
+    0x40EE4288,
+    0x0AB86260,
+    0x080C8576,
+    0x36C6CC05,
+    0x0AB9346F,
+    0x62AA3EC8,
+    0x51109797,
+    0x0FEB1585,
+    0x04700024,
+    0x01DEE723,
+    0x5CD4AAA8,
+    0x1FE43CE5,
+    0x25C31267,
+    0x58512B48,
+    0x54147539,
+    0x4E340AB9,
+    0x563FBAEB,
+    0x60C8353A,
+    0x65A12D49,
+    0x6C499FB2,
+    0x7EA07556,
+    0x396E2BBB,
+    0x31A318F1,
+    0x11F855AE,
+    0x6EDFFB87,
+    0x59977042,
+    0x6EC5FA94,
+    0x75B4F690,
+    0x44B6FC61,
+    0x02A8BED8,
+    0x4C88C824,
+    0x08E31432,
+    0x09A4C09F,
+    0x4796B47D,
+    0x215B7E75,
+    0x0C639599,
+    0x0D93DD4C,
+    0x2FAC41DE,
+    0x4F46DADD,
+    0x03905848,
+    0x2B1C39C1,
+    0x25FFF199,
+    0x38621F7B,
+    0x69E59315,
+    0x1874C308,
+    0x024A3959,
+    0x2BAE1F12,
+    0x3C200626,
+    0x6BA5D369,
+    0x2FE9B97E,
+    0x674CC08E,
+    0x2CBB9657,
+    0x550E56C2,
+    0x5B80E0EC,
+    0x6549CCFF,
+    0x54E3E61A,
+    0x0FA689E3,
+    0x2C534848,
+    0x1EB24382,
+    0x61B959B5,
+    0x4D5F001E,
+    0x003A95CD,
+    0x1EDD4507,
+    0x621E895D,
+    0x7DC6E599,
+    0x0FBC2771,
+    0x152D0879,
+    0x77801087,
+    0x6A2DD731,
+    0x3644ABA2,
+    0x2E43A814,
+    0x12FF923F,
+    0x01CFE2C9,
+    0x35F8A572,
+    0x5789FD35,
+    0x16F39E7A,
+    0x7C0CA31C,
+    0x01016283,
+    0x2C9DCD96,
+    0x5D3C6F4E,
+    0x0058A186,
+    0x16354360,
+    0x502A262B,
+    0x2B56F93E,
+    0x0BC41ECB,
+    0x33C83E8B,
+    0x21968FC3,
+    0x6364490C,
+    0x16A45AA5,
+    0x286D873F,
+    0x2BE17254,
+    0x381FBC06,
+    0x0DF309AA,
+    0x15D48B84,
+    0x0FB2C5DD,
+    0x7C440D21,
+    0x74908F00,
+    0x75520624,
+    0x7E58F065,
+    0x141E1E41,
+    0x6582F4AE,
+    0x2C4479E5,
+    0x7A09FFF8,
+    0x1BAA979F,
+    0x45AB39BD,
+    0x774F78BC,
+    0x3C5F9AA2,
+    0x115D9DC9,
+    0x4B1546D7,
+    0x196C1A55,
+    0x6A88FB5E,
+    0x4C1CA910,
+    0x34869067,
+    0x2662DCBB,
+    0x0A4625D4,
+    0x25B121C8,
+    0x1A50CCD2,
+    0x490EA316,
+    0x42556FFA,
+    0x6B5E4F88,
+    0x329FAF33,
+    0x54F39A88,
+    0x3B411E09,
+    0x6950AE8E,
+    0x310A912C,
+    0x63BDDCBA,
+    0x347977C0,
+    0x52831335,
+    0x41F32FC6,
+    0x67DD5ACB,
+    0x41AE544E,
+    0x1D83750A,
+    0x4BB58D20,
+    0x2F5496EE,
+    0x353819EC,
+    0x412EE425,
+    0x1BFD2747,
+    0x32A14699,
+    0x2F7BE906,
+    0x38AFDA41,
+    0x5B1E6316,
+    0x7B810B48,
+    0x6AEBB30D,
+    0x55D94F89,
+    0x69DB4833,
+    0x3A6ECB6C,
+    0x50E7D206,
+    0x148A4B69,
+    0x1AC5548D,
+    0x40019CF9,
+    0x1E566F2A,
+    0x0998A950,
+    0x5BC887F0,
+    0x73FBBD18,
+    0x341E05A8,
+    0x7D0597D5,
+    0x582308D9,
+    0x7A98ADDF,
+    0x0938B854,
+    0x544BF13D,
+    0x50090144,
+    0x13BAF374,
+    0x1896A8D5,
+    0x75EA7475,
+    0x23510DD8,
+    0x72C93BCC,
+    0x1C41410E,
+    0x4B72D5F9,
+    0x103CCC4E,
+    0x3896BEF2,
+    0x2C5E0B1C,
+    0x1E2096DE,
+    0x15594D47,
+    0x04E035CE,
+    0x2785D1B1,
+    0x795BC87D,
+    0x373FECBF,
+    0x0B18C3A0,
+    0x6516874A,
+    0x2B567BE9,
+    0x5A2A3D1B,
+    0x74D99C04,
+    0x437DE605,
+    0x047DF991,
+    0x322FAAD4,
+    0x2EF2F76F,
+    0x5F9E7278,
+    0x62740235,
+    0x18C1E8C2,
+    0x0691E203,
+    0x3324646D,
+    0x59542C9F,
+    0x32433D0D,
+    0x42C17492,
+    0x45AC808A,
+    0x685394E0,
+    0x316F7193,
+    0x5EA108A0,
+    0x6BB3F12F,
+    0x232F8865,
+    0x7C162B62,
+    0x52AA9E45,
+    0x1B69F8DB,
+    0x3EC35206,
+    0x1EF086DD,
+    0x34D7A5E3,
+    0x33AEEA57,
+    0x03565CC8,
+    0x5BC5FD47,
+    0x47ADC343,
+    0x1D5857A2,
+    0x5E7ECE76,
+    0x0239FBA3,
+    0x58BDEAD4,
+    0x41671AEF,
+    0x3C8A9189,
+    0x7342ED52,
+    0x19871456,
+    0x573A02C8,
+    0x2EC8AD55,
+    0x09C4A997,
+    0x34B9B63A,
+    0x226DA984,
+    0x6B31D16E,
+    0x458384D2,
+    0x353911E1,
+    0x4CFD1256,
+    0x163C23AF,
+    0x7609C5E0,
+    0x76596C08,
+    0x087ADAC7,
+    0x4FD4B62C,
+    0x3692A037,
+    0x51C54B62,
+    0x133DAF4D,
+    0x0C76F623,
+    0x387D21F3,
+    0x6034ABE5,
+    0x7C982E2B,
+    0x63A266B4,
+    0x4F2B17B8,
+    0x0BD62F1D,
+    0x70E37A7C,
+    0x4F162DA9,
+    0x38F0E527,
+    0x6CE798D7,
+    0x6C74250B,
+    0x606F2FAD,
+    0x212B041D,
+    0x6724FD32,
+    0x73AAF9AF,
+    0x3AE9B76B,
+    0x014FE151,
+    0x37687943,
+    0x36BB7786,
+    0x01DA85EF,
+    0x28C618AE,
+    0x36706580,
+    0x3F5F610D,
+    0x2E0B9391,
+    0x5750E38D,
+    0x00B48D71,
+    0x0F1F1D7A,
+    0x7107C415,
+    0x35C1E287,
+    0x26CCCE2F,
+    0x4E29277A,
+    0x1580EE9D,
+    0x18136F74,
+    0x530F32AD,
+    0x5A19B05D,
+    0x3D38B320,
+    0x6A3BF1E4,
+    0x39E9EDBB,
+    0x2CE6A59E,
+    0x2DF215E1,
+    0x216A17BA,
+    0x3A8F3CFA,
+    0x0A14D990,
+    0x1162E529,
+    0x1213C181,
+    0x3DAA68F5,
+    0x16C570FF,
+    0x1063321C,
+    0x06A2D0E8,
+    0x17C094A4,
+    0x39A5D9C9,
+    0x086D4802,
+    0x67AB7FE3,
+    0x67F51392,
+    0x3649C2AC,
+    0x62AA8CF8,
+    0x55B6FDBB,
+    0x55C3E972,
+    0x2F865724,
+    0x314FA653,
+    0x029F66F1,
+    0x016F80A2,
+    0x4B70E0C2,
+    0x1782F9AB,
+    0x697578EE,
+    0x07B2C8B7,
+    0x123F6681,
+    0x2B78DB24,
+    0x2CD8DB9D,
+    0x302947B1,
+    0x04F4C99A,
+    0x1F8BCBBD,
+    0x61C782EA,
+    0x3459928C,
+    0x3EFEC720,
+    0x24F2B8F6,
+    0x5DEC66B5,
+    0x622386CC,
+    0x26B70002,
+    0x1FA0D640,
+    0x6EDEAA0A,
+    0x670FF3E1,
+    0x18641D8E,
+    0x43B68197,
+    0x315B1707,
+    0x46DB526A,
+    0x02FA5277,
+    0x36F6EDF9,
+    0x31AD912B,
+    0x7D518EBD,
+    0x61DB2EEA,
+    0x0BA28BAD,
+    0x3C839E59,
+    0x7ED007F1,
+    0x74447F8A,
+    0x6B4CE5B7,
+    0x7272E3A4,
+    0x192257D1,
+    0x5F882281,
+    0x5F890768,
+    0x47EEC4CB,
+    0x2EF3E6C8,
+    0x43D6E4E2,
+    0x668CE6BA,
+    0x50679E00,
+    0x24C067A8,
+    0x605BE47C,
+    0x324AC2EC,
+    # Terminal full rounds (4 rounds x 24 constants)
+    0x5883788F,
+    0x7EBA66AF,
+    0x23620F78,
+    0x44492C9A,
+    0x7CC098A4,
+    0x705191FA,
+    0x2F7185E2,
+    0x6EBBB07E,
+    0x23508C3B,
+    0x6CB0F0F4,
+    0x1190A8C0,
+    0x60F8F1D0,
+    0x316C16A1,
+    0x440742C7,
+    0x7643F142,
+    0x642F9668,
+    0x214B7566,
+    0x52A5C469,
+    0x1BFD90DA,
+    0x1D7D8076,
+    0x6E06D1E8,
+    0x7D672E6D,
+    0x6FD2E3E3,
+    0x3257AE18,
+    0x75861A51,
+    0x0E2996FE,
+    0x2BDC228B,
+    0x6879FCB8,
+    0x14CA9B1C,
+    0x29953D92,
+    0x36EE671D,
+    0x31366E47,
+    0x79C4F5F2,
+    0x2B8C8639,
+    0x073A293D,
+    0x32802C31,
+    0x4894D32F,
+    0x06ACC989,
+    0x40D852B1,
+    0x508857C4,
+    0x2FFE504D,
+    0x18BE00C1,
+    0x75A114E9,
+    0x4ED5922A,
+    0x1060EE72,
+    0x2176563C,
+    0x0B91B242,
+    0x6BFBF1A4,
+    0x06F94470,
+    0x694F4383,
+    0x53CADA3E,
+    0x1527BFD8,
+    0x2BDFE868,
+    0x120C2D2C,
+    0x7DFD6309,
+    0x10B619C2,
+    0x0550BC7F,
+    0x488CF3DC,
+    0x4C5454A2,
+    0x00BE2976,
+    0x349C9669,
+    0x2B4EB07D,
+    0x0450BF40,
+    0x58DE7343,
+    0x3495A265,
+    0x2305E3B7,
+    0x661DD781,
+    0x1C183983,
+    0x46992791,
+    0x3EB3751F,
+    0x38F728C8,
+    0x775D0A30,
+    0x7636645A,
+    0x7125AA5D,
+    0x0C3F2DCA,
+    0x13B595CC,
+    0x5A5E9BCE,
+    0x54BB3456,
+    0x069A1A5A,
+    0x7B9F15EE,
+    0x50150189,
+    0x68C9157B,
+    0x07E06E22,
+    0x568AECDB,
+    0x1403F847,
+    0x436CF5DA,
+    0x3F09C026,
+    0x652F7B1B,
+    0x3E8607F3,
+    0x5BB37C57,
+    0x1B1A9ECF,
+    0x39D11CB0,
+    0x1841A51C,
+    0x1251AD48,
+    0x74FB5EDD,
+    0x21FA33C6,
+]
+
+# For width 16 (needs (8 + 20) * 16 = 448 constants).
+ROUND_CONSTANTS_16: list[Fp] = [Fp(value=v) for v in _RAW_CONSTANTS_16]
+
+# For width 24 (needs (8 + 23) * 24 = 744 constants).
+ROUND_CONSTANTS_24: list[Fp] = [Fp(value=v) for v in _RAW_CONSTANTS_24]
diff --git a/src/lean_spec/subspecs/poseidon1/permutation.py b/src/lean_spec/subspecs/poseidon1/permutation.py
new file mode 100644
index 00000000..e7558b7f
--- /dev/null
+++ b/src/lean_spec/subspecs/poseidon1/permutation.py
@@ -0,0 +1,285 @@
+"""
+A minimal Python specification for the Poseidon1 permutation.
+
+Based on "Poseidon: A New Hash Function for Zero-Knowledge Proof Systems".
+See https://eprint.iacr.org/2019/458.
+
+Uses Numba JIT compilation for native-speed permutation.
+"""
+
+from __future__ import annotations
+
+from typing import Self
+
+import numpy as np
+from numba import njit
+from numpy.typing import NDArray
+from pydantic import Field, model_validator
+
+from ...types import StrictBaseModel
+from ..koalabear.field import Fp, P
+from .constants import (
+    ROUND_CONSTANTS_16,
+    ROUND_CONSTANTS_24,
+)
+
+
+def _build_circulant_mds(first_row: list[int], n: int, p: int) -> NDArray[np.int64]:
+    """
+    Expand a circulant matrix from its first row into a dense NxN matrix.
+
+    A circulant matrix C defined by first row [r0, r1, ..., rn-1]:
+    C[i][j] = r[(j - i) mod n]
+    """
+    matrix = np.zeros((n, n), dtype=np.int64)
+    for i in range(n):
+        for j in range(n):
+            matrix[i][j] = first_row[(j - i) % n] % p
+    return matrix
+
+
+@njit(cache=True)
+def _mds_multiply_jit(
+    state: NDArray[np.int64], mds: NDArray[np.int64], p: int
+) -> NDArray[np.int64]:
+    """
+    Dense MDS matrix-vector multiplication.
+
+    Computes y = MDS * x where MDS is the circulant MDS matrix.
+    Each product is reduced mod p before accumulation to prevent overflow.
+    """
+    n = state.shape[0]
+    result = np.empty(n, dtype=np.int64)
+    for i in range(n):
+        s = np.int64(0)
+        for j in range(n):
+            s += mds[i, j] * state[j] % p
+        result[i] = s % p
+    return result
+
+
+@njit(cache=True)
+def _permute_jit(
+    state: NDArray[np.int64],
+    round_constants: NDArray[np.int64],
+    mds: NDArray[np.int64],
+    width: int,
+    half_rounds_f: int,
+    rounds_p: int,
+    p: int,
+) -> None:
+    """
+    Full Poseidon1 permutation, compiled to native code.
+
+    Modifies state array in-place.
+    S-box: x^3 computed as (x*x % p) * x % p to avoid int64 overflow.
+
+    Round structure: AddRoundConstants -> S-box -> MDS multiply.
+    Unlike Poseidon2, there is no initial linear layer.
+    """
+    const_idx = 0
+
+    # 1. First half of full rounds.
+    #
+    # Full rounds apply the S-box to every state element.
+    # Note: for S_BOX_DEGREE=3, state**3 would overflow int64 before modulo.
+    # Expand S-box to `(state*state % P) * state % P` to stay in range.
+    for _ in range(half_rounds_f):
+        # Add round constants to entire state.
+        state[:] = (state + round_constants[const_idx : const_idx + width]) % p
+        const_idx += width
+
+        # Apply S-box (x -> x^d) to full state.
+        state[:] = (state * state % p) * state % p
+
+        # Apply dense MDS multiply for diffusion.
+        state[:] = _mds_multiply_jit(state, mds, p)
+
+    # 2. Partial rounds.
+    #
+    # Partial rounds add constants to ALL state elements but apply
+    # the S-box only to state[0]. The same dense MDS matrix is used.
+    for _ in range(rounds_p):
+        # Add round constants to entire state.
+        state[:] = (state + round_constants[const_idx : const_idx + width]) % p
+        const_idx += width
+
+        # Apply S-box to first element only.
+        # This is the main optimization of the Hades design.
+        state[0] = (state[0] * state[0] % p) * state[0] % p
+
+        # Apply dense MDS multiply.
+        state[:] = _mds_multiply_jit(state, mds, p)
+
+    # 3. Second half of full rounds.
+    for _ in range(half_rounds_f):
+        # Add round constants to entire state.
+        state[:] = (state + round_constants[const_idx : const_idx + width]) % p
+        const_idx += width
+
+        # Apply S-box to full state.
+        state[:] = (state * state % p) * state % p
+
+        # Apply dense MDS multiply for diffusion.
+        state[:] = _mds_multiply_jit(state, mds, p)
+
+
+class Poseidon1Params(StrictBaseModel):
+    """Parameters for a specific Poseidon1 instance."""
+
+    width: int = Field(gt=0, description="The size of the state (t).")
+    rounds_f: int = Field(gt=0, description="Total number of 'full' rounds.")
+    rounds_p: int = Field(ge=0, description="Total number of 'partial' rounds.")
+    mds_first_row: list[Fp] = Field(
+        min_length=1,
+        description="First row of the circulant MDS matrix.",
+    )
+    round_constants: list[Fp] = Field(
+        min_length=1,
+        description="The list of pre-computed constants for all rounds.",
+    )
+
+    @model_validator(mode="after")
+    def check_lengths(self) -> Self:
+        """Ensures vector lengths match the configuration."""
+        if len(self.mds_first_row) != self.width:
+            raise ValueError("Length of mds_first_row must equal width.")
+
+        expected_constants = (self.rounds_f + self.rounds_p) * self.width
+        if len(self.round_constants) != expected_constants:
+            raise ValueError("Incorrect number of round constants provided.")
+
+        return self
+
+
+class Poseidon1:
+    """
+    Optimized execution engine for Poseidon1.
+
+    Pre-processes parameters into numpy arrays during initialization.
+    Minimizes overhead during permute calls.
+    """
+
+    __slots__ = ("_width", "_half_rounds_f", "_rounds_p", "_mds", "_round_constants")
+
+    _width: int
+    """State size (t)."""
+
+    _half_rounds_f: int
+    """Full rounds divided by 2."""
+
+    _rounds_p: int
+    """Number of partial rounds."""
+
+    _mds: NDArray[np.int64]
+    """Dense circulant MDS matrix."""
+
+    _round_constants: NDArray[np.int64]
+    """Flattened array of all round constants."""
+
+    def __init__(self, params: Poseidon1Params) -> None:
+        """
+        Initialize the engine with validated parameters.
+
+        Converts Fp lists to int64 numpy arrays for speed.
+        Builds the dense circulant MDS matrix from the first row.
+        """
+        self._width = params.width
+        self._half_rounds_f = params.rounds_f // 2
+        self._rounds_p = params.rounds_p
+
+        # Build the dense circulant MDS matrix from first row.
+        first_row_ints = [fp.value for fp in params.mds_first_row]
+        self._mds = _build_circulant_mds(first_row_ints, params.width, P)
+
+        # Pre-convert round constants to numpy array.
+        self._round_constants = np.array(
+            [fp.value for fp in params.round_constants], dtype=np.int64
+        )
+
+    def permute(self, current_state: list[Fp]) -> list[Fp]:
+        """
+        Perform the full Poseidon1 permutation.
+
+        Structure:
+
+        1. First half of full rounds
+        2. Partial rounds
+        3. Second half of full rounds
+
+        Args:
+            current_state: List of Fp elements representing the current state.
+
+        Returns:
+            New state after applying the permutation.
+        """
+        if len(current_state) != self._width:
+            raise ValueError(f"Input state must have length {self._width}")
+
+        state = np.array([fp.value for fp in current_state], dtype=np.int64)
+
+        _permute_jit(
+            state,
+            self._round_constants,
+            self._mds,
+            self._width,
+            self._half_rounds_f,
+            self._rounds_p,
+            P,
+        )
+
+        return [Fp(value=int(x)) for x in state]
+
+
+# MDS first row for WIDTH = 16
+#
+# From Plonky3: koala-bear/src/mds.rs
+_MDS_FIRST_ROW_16: list[int] = [1, 1, 51, 1, 11, 17, 2, 1, 101, 63, 15, 2, 67, 22, 13, 3]
+
+# MDS first row for WIDTH = 24
+#
+# From Plonky3: koala-bear/src/mds.rs
+_MDS_FIRST_ROW_24: list[int] = [
+    0x2D0AAAAB,
+    0x64850517,
+    0x17F5551D,
+    0x04ECBEB5,
+    0x6D91A8D5,
+    0x60703026,
+    0x18D6F3CA,
+    0x729601A7,
+    0x77CDA9E2,
+    0x3C0F5038,
+    0x26D52A61,
+    0x0360405D,
+    0x68FC71C8,
+    0x2495A71D,
+    0x5D57AFC2,
+    0x1689DD98,
+    0x3C2C3DBE,
+    0x0C23DC41,
+    0x0524C7F2,
+    0x6BE4DF69,
+    0x0A6E572C,
+    0x5C7790FA,
+    0x17E118F6,
+    0x0878A07F,
+]
+
+# Parameters for WIDTH = 16
+PARAMS_16 = Poseidon1Params(
+    width=16,
+    rounds_f=8,
+    rounds_p=20,
+    mds_first_row=[Fp(value=v) for v in _MDS_FIRST_ROW_16],
+    round_constants=ROUND_CONSTANTS_16,
+)
+
+# Parameters for WIDTH = 24
+PARAMS_24 = Poseidon1Params(
+    width=24,
+    rounds_f=8,
+    rounds_p=23,
+    mds_first_row=[Fp(value=v) for v in _MDS_FIRST_ROW_24],
+    round_constants=ROUND_CONSTANTS_24,
+)
diff --git a/src/lean_spec/subspecs/poseidon2/__init__.py b/src/lean_spec/subspecs/poseidon2/__init__.py
deleted file mode 100644
index 7f7b1f90..00000000
--- a/src/lean_spec/subspecs/poseidon2/__init__.py
+++ /dev/null
@@ -1,15 +0,0 @@
-"""Specification for the Poseidon2 permutation."""
-
-from .permutation import (
-    PARAMS_16,
-    PARAMS_24,
-    Poseidon2,
-    Poseidon2Params,
-)
-
-__all__ = [
-    "Poseidon2",
-    "Poseidon2Params",
-    "PARAMS_16",
-    "PARAMS_24",
-]
diff --git a/src/lean_spec/subspecs/poseidon2/constants.py b/src/lean_spec/subspecs/poseidon2/constants.py
deleted file mode 100644
index bc567662..00000000
--- a/src/lean_spec/subspecs/poseidon2/constants.py
+++ /dev/null
@@ -1,388 +0,0 @@
-"""Round constants for the Poseidon2 permutation over the KoalaBear field."""
-
-from __future__ import annotations
-
-from ..koalabear.field import Fp
-
-# For width 16: 64 external_initial + 20 internal + 64 external_final = 148 constants
-_RAW_CONSTANTS_16: list[int] = [
-    # External initial (4 rounds × 16 = 64 constants)
-    2128964168,
-    288780357,
-    316938561,
-    2126233899,
-    426817493,
-    1714118888,
-    1045008582,
-    1738510837,
-    889721787,
-    8866516,
-    681576474,
-    419059826,
-    1596305521,
-    1583176088,
-    1584387047,
-    1529751136,
-    1863858111,
-    1072044075,
-    517831365,
-    1464274176,
-    1138001621,
-    428001039,
-    245709561,
-    1641420379,
-    1365482496,
-    770454828,
-    693167409,
-    757905735,
-    136670447,
-    436275702,
-    525466355,
-    1559174242,
-    1030087950,
-    869864998,
-    322787870,
-    267688717,
-    948964561,
-    740478015,
-    679816114,
-    113662466,
-    2066544572,
-    1744924186,
-    367094720,
-    1380455578,
-    1842483872,
-    416711434,
-    1342291586,
-    1692058446,
-    1493348999,
-    1113949088,
-    210900530,
-    1071655077,
-    610242121,
-    1136339326,
-    2020858841,
-    1019840479,
-    678147278,
-    1678413261,
-    1361743414,
-    61132629,
-    1209546658,
-    64412292,
-    1936878279,
-    1980661727,
-    # Internal (20 constants)
-    2102596038,
-    1533193853,
-    1436311464,
-    2012303432,
-    839997195,
-    1225781098,
-    2011967775,
-    575084315,
-    1309329169,
-    786393545,
-    995788880,
-    1702925345,
-    1444525226,
-    908073383,
-    1811535085,
-    1531002367,
-    1635653662,
-    1585100155,
-    867006515,
-    879151050,
-    # External final (4 rounds × 16 = 64 constants)
-    1423960925,
-    2101391318,
-    1915532054,
-    275400051,
-    1168624859,
-    1141248885,
-    356546469,
-    1165250474,
-    1320543726,
-    932505663,
-    1204226364,
-    1452576828,
-    1774936729,
-    926808140,
-    1184948056,
-    1186493834,
-    843181003,
-    185193011,
-    452207447,
-    510054082,
-    1139268644,
-    630873441,
-    669538875,
-    462500858,
-    876500520,
-    1214043330,
-    383937013,
-    375087302,
-    636912601,
-    307200505,
-    390279673,
-    1999916485,
-    1518476730,
-    1606686591,
-    1410677749,
-    1581191572,
-    1004269969,
-    143426723,
-    1747283099,
-    1016118214,
-    1749423722,
-    66331533,
-    1177761275,
-    1581069649,
-    1851371119,
-    852520128,
-    1499632627,
-    1820847538,
-    150757557,
-    884787840,
-    619710451,
-    1651711087,
-    505263814,
-    212076987,
-    1482432120,
-    1458130652,
-    382871348,
-    417404007,
-    2066495280,
-    1996518884,
-    902934924,
-    582892981,
-    1337064375,
-    1199354861,
-]
-
-# For width 24: 96 external_initial + 23 internal + 96 external_final = 215 constants
-_RAW_CONSTANTS_24: list[int] = [
-    # External initial (4 rounds × 24 = 96 constants)
-    487143900,
-    1829048205,
-    1652578477,
-    646002781,
-    1044144830,
-    53279448,
-    1519499836,
-    22697702,
-    1768655004,
-    230479744,
-    1484895689,
-    705130286,
-    1429811285,
-    1695785093,
-    1417332623,
-    1115801016,
-    1048199020,
-    878062617,
-    738518649,
-    249004596,
-    1601837737,
-    24601614,
-    245692625,
-    364803730,
-    1857019234,
-    1906668230,
-    1916890890,
-    835590867,
-    557228239,
-    352829675,
-    515301498,
-    973918075,
-    954515249,
-    1142063750,
-    1795549558,
-    608869266,
-    1850421928,
-    2028872854,
-    1197543771,
-    1027240055,
-    1976813168,
-    963257461,
-    652017844,
-    2113212249,
-    213459679,
-    90747280,
-    1540619478,
-    324138382,
-    1377377119,
-    294744504,
-    512472871,
-    668081958,
-    907306515,
-    518526882,
-    1907091534,
-    1152942192,
-    1572881424,
-    720020214,
-    729527057,
-    1762035789,
-    86171731,
-    205890068,
-    453077400,
-    1201344594,
-    986483134,
-    125174298,
-    2050269685,
-    1895332113,
-    749706654,
-    40566555,
-    742540942,
-    1735551813,
-    162985276,
-    1943496073,
-    1469312688,
-    703013107,
-    1979485151,
-    1278193166,
-    548674995,
-    2118718736,
-    749596440,
-    1476142294,
-    1293606474,
-    918523452,
-    890353212,
-    1691895663,
-    1932240646,
-    1180911992,
-    86098300,
-    1592168978,
-    895077289,
-    724819849,
-    1697986774,
-    1608418116,
-    1083269213,
-    691256798,
-    # Internal (23 constants)
-    893435011,
-    403879071,
-    1363789863,
-    1662900517,
-    2043370,
-    2109755796,
-    931751726,
-    2091644718,
-    606977583,
-    185050397,
-    946157136,
-    1350065230,
-    1625860064,
-    122045240,
-    880989921,
-    145137438,
-    1059782436,
-    1477755661,
-    335465138,
-    1640704282,
-    1757946479,
-    1551204074,
-    681266718,
-    # External final (4 rounds × 24 = 96 constants)
-    328586442,
-    1572520009,
-    1375479591,
-    322991001,
-    967600467,
-    1172861548,
-    1973891356,
-    1503625929,
-    1881993531,
-    40601941,
-    1155570620,
-    571547775,
-    1361622243,
-    1495024047,
-    1733254248,
-    964808915,
-    763558040,
-    1887228519,
-    994888261,
-    718330940,
-    213359415,
-    603124968,
-    1038411577,
-    2099454809,
-    949846777,
-    630926956,
-    1168723439,
-    222917504,
-    1527025973,
-    1009157017,
-    2029957881,
-    805977836,
-    1347511739,
-    540019059,
-    589807745,
-    440771316,
-    1530063406,
-    761076336,
-    87974206,
-    1412686751,
-    1230318064,
-    514464425,
-    1469011754,
-    1770970737,
-    1510972858,
-    965357206,
-    209398053,
-    778802532,
-    40567006,
-    1984217577,
-    1545851069,
-    879801839,
-    1611910970,
-    1215591048,
-    330802499,
-    1051639108,
-    321036,
-    511927202,
-    591603098,
-    1775897642,
-    115598532,
-    278200718,
-    233743176,
-    525096211,
-    1335507608,
-    830017835,
-    1380629279,
-    560028578,
-    598425701,
-    302162385,
-    567434115,
-    1859222575,
-    958294793,
-    1582225556,
-    1781487858,
-    1570246000,
-    1067748446,
-    526608119,
-    1666453343,
-    1786918381,
-    348203640,
-    1860035017,
-    1489902626,
-    1904576699,
-    860033965,
-    1954077639,
-    1685771567,
-    971513929,
-    1877873770,
-    137113380,
-    520695829,
-    806829080,
-    1408699405,
-    1613277964,
-    793223662,
-    648443918,
-]
-
-# For width 16 (needs 8*16 + 20 = 148 constants).
-ROUND_CONSTANTS_16: list[Fp] = [Fp(value=v) for v in _RAW_CONSTANTS_16]
-
-# For width 24 (needs 8*24 + 23 = 215 constants).
-ROUND_CONSTANTS_24: list[Fp] = [Fp(value=v) for v in _RAW_CONSTANTS_24]
diff --git a/src/lean_spec/subspecs/poseidon2/permutation.py b/src/lean_spec/subspecs/poseidon2/permutation.py
deleted file mode 100644
index 7db0e654..00000000
--- a/src/lean_spec/subspecs/poseidon2/permutation.py
+++ /dev/null
@@ -1,355 +0,0 @@
-"""
-A minimal Python specification for the Poseidon2 permutation.
-
-Based on "Poseidon2: A Faster Version of the Poseidon Hash Function".
-See https://eprint.iacr.org/2023/323.
-
-Uses Numba JIT compilation for native-speed permutation.
-"""
-
-from __future__ import annotations
-
-from typing import Final, Self
-
-import numpy as np
-from numba import njit
-from numpy.typing import NDArray
-from pydantic import Field, model_validator
-
-from ...types import StrictBaseModel
-from ..koalabear.field import Fp, P
-from .constants import (
-    ROUND_CONSTANTS_16,
-    ROUND_CONSTANTS_24,
-)
-
-_M4_T: Final[NDArray[np.int64]] = np.array(
-    [
-        [2, 3, 1, 1],
-        [1, 2, 3, 1],
-        [1, 1, 2, 3],
-        [3, 1, 1, 2],
-    ],
-    dtype=np.int64,
-).T
-"""
-Base 4x4 MDS matrix, pre-transposed.
-
-Pre-transposition enables efficient row-vector multiplication: `v @ M.T`.
-"""
-
-
-@njit(cache=True)
-def _m4_multiply(chunks: NDArray[np.int64], m4t: NDArray[np.int64], p: int) -> NDArray[np.int64]:
-    """
-    Multiply each row of `chunks` by the M4 matrix.
-
-    Equivalent to `chunks @ m4t % p`.
-    Numba's `@` operator requires scipy and float arrays,
-    so we use an explicit loop instead. Numba unrolls these
-    small fixed-size loops, so overhead is ~12% vs native matmul.
-    """
-    result = np.empty_like(chunks)
-    for c in range(chunks.shape[0]):
-        for j in range(4):
-            s = np.int64(0)
-            for k in range(4):
-                s += chunks[c, k] * m4t[k, j]
-            result[c, j] = s % p
-    return result
-
-
-@njit(cache=True)
-def _external_linear_layer_jit(
-    state: NDArray[np.int64], m4t: NDArray[np.int64], p: int
-) -> NDArray[np.int64]:
-    """
-    Apply the external linear layer (M_E).
-
-    Provides strong diffusion across the entire state.
-    Used in full rounds.
-
-    For state size t=4k, constructed from M4 to form a circulant-like matrix.
-    Efficient while ensuring any single element change affects all others.
-
-    See Appendix B of the paper.
-    """
-    # Apply M4 to each 4-element chunk.
-    # Provides strong local diffusion within each block.
-    chunks = state.reshape(-1, 4)
-    chunks = _m4_multiply(chunks, m4t, p)
-
-    # Apply outer circulant structure for global diffusion.
-    # Equivalent to multiplying by circ(2*I, I, ..., I) after M4 stage.
-    sums = np.zeros(4, dtype=np.int64)
-    for c in range(chunks.shape[0]):
-        for i in range(4):
-            sums[i] += chunks[c, i]
-
-    # Add corresponding sum to each element.
-    return (chunks + sums).reshape(-1) % p
-
-
-@njit(cache=True)
-def _internal_linear_layer_jit(
-    state: NDArray[np.int64], diag_vector: NDArray[np.int64], p: int
-) -> NDArray[np.int64]:
-    """
-    Apply the internal linear layer (M_I).
-
-    Used during partial rounds.
-    Optimized for speed.
-
-    Matrix structure: M_I = J + D
-
-    - J is the all-ones matrix
-    - D is a diagonal matrix
-
-    This allows O(t) computation instead of O(t^2):
-
-        M_I * s = J*s + D*s
-
-    J*s is a vector where each element equals the sum of all elements in s.
-    """
-    # J*state: sum of all elements (broadcast to vector).
-    # D*state: element-wise multiplication with diagonal.
-    state_sum = state.sum()
-
-    # new_state[i] = state_sum + diag_vector[i] * state[i]
-    return (state_sum + (diag_vector * state)) % p
-
-
-@njit(cache=True)
-def _permute_jit(
-    state: NDArray[np.int64],
-    round_constants: NDArray[np.int64],
-    diag_vector: NDArray[np.int64],
-    m4t: NDArray[np.int64],
-    width: int,
-    half_rounds_f: int,
-    rounds_p: int,
-    p: int,
-) -> None:
-    """
-    Full Poseidon2 permutation, compiled to native code.
-
-    Modifies state array in-place.
-    S-box: x^3 computed as (x*x % p) * x % p to avoid int64 overflow.
-    """
-    const_idx = 0
-
-    # 1. Initial linear layer.
-    #
-    # Prevents certain algebraic attacks.
-    # Ensures the permutation begins with a diffusion layer.
-    state[:] = _external_linear_layer_jit(state, m4t, p)
-
-    # 2. First half of full rounds.
-    #
-    # Note: for S_BOX_DEGREE=3, state**3 would overflow int64 before modulo.
-    # Values reach up to 2^93, but int64 max is 2^63.
-    # Expand S-box to `(state*state % P) * state % P` to stay in range.
-    for _ in range(half_rounds_f):
-        # Add round constants to entire state.
-        state[:] = (state + round_constants[const_idx : const_idx + width]) % p
-        const_idx += width
-
-        # Apply S-box (x -> x^d) to full state.
-        state[:] = (state * state % p) * state % p
-
-        # Apply external linear layer for diffusion.
-        state[:] = _external_linear_layer_jit(state, m4t, p)
-
-    # 3. Partial rounds.
-    for _ in range(rounds_p):
-        # Add single round constant to first element.
-        state[0] = (state[0] + round_constants[const_idx]) % p
-        const_idx += 1
-
-        # Apply S-box to first element only.
-        # This is the main optimization of the Hades design.
-        state[0] = (state[0] * state[0] % p) * state[0] % p
-
-        # Apply internal linear layer.
-        state[:] = _internal_linear_layer_jit(state, diag_vector, p)
-
-    # 4. Second half of full rounds.
-    for _ in range(half_rounds_f):
-        # Add round constants to entire state.
-        state[:] = (state + round_constants[const_idx : const_idx + width]) % p
-        const_idx += width
-
-        # Apply S-box to full state.
-        state[:] = (state * state % p) * state % p
-
-        # Apply external linear layer for diffusion.
-        state[:] = _external_linear_layer_jit(state, m4t, p)
-
-
-class Poseidon2Params(StrictBaseModel):
-    """Parameters for a specific Poseidon2 instance."""
-
-    width: int = Field(gt=0, description="The size of the state (t).")
-    rounds_f: int = Field(gt=0, description="Total number of 'full' rounds.")
-    rounds_p: int = Field(ge=0, description="Total number of 'partial' rounds.")
-    internal_diag_vectors: list[Fp] = Field(
-        min_length=1,
-        description=("Diagonal vectors for the efficient internal linear layer matrix (M_I)."),
-    )
-    round_constants: list[Fp] = Field(
-        min_length=1,
-        description="The list of pre-computed constants for all rounds.",
-    )
-
-    @model_validator(mode="after")
-    def check_lengths(self) -> Self:
-        """Ensures vector lengths match the configuration."""
-        if len(self.internal_diag_vectors) != self.width:
-            raise ValueError("Length of internal_diag_vectors must equal width.")
-
-        expected_constants = (self.rounds_f * self.width) + self.rounds_p
-        if len(self.round_constants) != expected_constants:
-            raise ValueError("Incorrect number of round constants provided.")
-
-        return self
-
-
-class Poseidon2:
-    """
-    Optimized execution engine for Poseidon2.
-
-    Pre-processes parameters into numpy arrays during initialization.
-    Minimizes overhead during permute calls.
-    """
-
-    __slots__ = ("_width", "_half_rounds_f", "_rounds_p", "_diag_vector", "_round_constants")
-
-    _width: int
-    """State size (t)."""
-
-    _half_rounds_f: int
-    """Full rounds divided by 2."""
-
-    _rounds_p: int
-    """Number of partial rounds."""
-
-    _diag_vector: NDArray[np.int64]
-    """Diagonal vector for internal linear layer (M_I)."""
-
-    _round_constants: NDArray[np.int64]
-    """Flattened array of all round constants."""
-
-    def __init__(self, params: Poseidon2Params) -> None:
-        """
-        Initialize the engine with validated parameters.
-
-        Converts Fp lists to int64 numpy arrays for speed.
-        """
-        self._width = params.width
-        self._half_rounds_f = params.rounds_f // 2
-        self._rounds_p = params.rounds_p
-
-        # Pre-convert to numpy arrays.
-        # Avoids overhead in the hot loop.
-        self._diag_vector = np.array(
-            [fp.value for fp in params.internal_diag_vectors], dtype=np.int64
-        )
-        self._round_constants = np.array(
-            [fp.value for fp in params.round_constants], dtype=np.int64
-        )
-
-    def permute(self, current_state: list[Fp]) -> list[Fp]:
-        """
-        Perform the full Poseidon2 permutation.
-
-        Structure:
-
-        1. Initial linear layer
-        2. First half of full rounds
-        3. Partial rounds
-        4. Second half of full rounds
-
-        Args:
-            current_state: List of Fp elements representing the current state.
-
-        Returns:
-            New state after applying the permutation.
-        """
-        if len(current_state) != self._width:
-            raise ValueError(f"Input state must have length {self._width}")
-
-        state = np.array([fp.value for fp in current_state], dtype=np.int64)
-
-        _permute_jit(
-            state,
-            self._round_constants,
-            self._diag_vector,
-            _M4_T,
-            self._width,
-            self._half_rounds_f,
-            self._rounds_p,
-            P,
-        )
-
-        return [Fp(value=int(x)) for x in state]
-
-
-# Parameters for WIDTH = 16
-PARAMS_16 = Poseidon2Params(
-    width=16,
-    rounds_f=8,
-    rounds_p=20,
-    internal_diag_vectors=[
-        Fp(value=-2),
-        Fp(value=1),
-        Fp(value=2),
-        Fp(value=1) / Fp(value=2),
-        Fp(value=3),
-        Fp(value=4),
-        Fp(value=-1) / Fp(value=2),
-        Fp(value=-3),
-        Fp(value=-4),
-        Fp(value=1) / Fp(value=2**8),
-        Fp(value=1) / Fp(value=8),
-        Fp(value=1) / Fp(value=2**24),
-        Fp(value=-1) / Fp(value=2**8),
-        Fp(value=-1) / Fp(value=8),
-        Fp(value=-1) / Fp(value=16),
-        Fp(value=-1) / Fp(value=2**24),
-    ],
-    round_constants=ROUND_CONSTANTS_16,
-)
-
-# Parameters for WIDTH = 24
-PARAMS_24 = Poseidon2Params(
-    width=24,
-    rounds_f=8,
-    rounds_p=23,
-    internal_diag_vectors=[
-        Fp(value=-2),
-        Fp(value=1),
-        Fp(value=2),
-        Fp(value=1) / Fp(value=2),
-        Fp(value=3),
-        Fp(value=4),
-        Fp(value=-1) / Fp(value=2),
-        Fp(value=-3),
-        Fp(value=-4),
-        Fp(value=1) / Fp(value=2**8),
-        Fp(value=1) / Fp(value=4),
-        Fp(value=1) / Fp(value=8),
-        Fp(value=1) / Fp(value=16),
-        Fp(value=1) / Fp(value=32),
-        Fp(value=1) / Fp(value=64),
-        Fp(value=1) / Fp(value=2**24),
-        Fp(value=-1) / Fp(value=2**8),
-        Fp(value=-1) / Fp(value=8),
-        Fp(value=-1) / Fp(value=16),
-        Fp(value=-1) / Fp(value=32),
-        Fp(value=-1) / Fp(value=64),
-        Fp(value=-1) / Fp(value=2**7),
-        Fp(value=-1) / Fp(value=2**9),
-        Fp(value=-1) / Fp(value=2**24),
-    ],
-    round_constants=ROUND_CONSTANTS_24,
-)
diff --git a/src/lean_spec/subspecs/validator/registry.py b/src/lean_spec/subspecs/validator/registry.py
index 0b8e4215..feb66cdc 100644
--- a/src/lean_spec/subspecs/validator/registry.py
+++ b/src/lean_spec/subspecs/validator/registry.py
@@ -15,7 +15,7 @@
 2. **validator-keys-manifest.yaml** - Contains key metadata and file paths:
 
        key_scheme: SIGTopLevelTargetSumLifetime32Dim64Base8
-       hash_function: Poseidon2
+       hash_function: Poseidon1
        num_validators: 3
        validators:
        - index: 0
@@ -85,7 +85,7 @@ class ValidatorManifest(BaseModel):
     """Signature scheme identifier (e.g., SIGTopLevelTargetSumLifetime32Dim64Base8)."""
 
     hash_function: str
-    """Hash function used (e.g., Poseidon2)."""
+    """Hash function used (e.g., Poseidon1)."""
 
     encoding: str
     """Encoding type (e.g., TargetSum)."""
diff --git a/src/lean_spec/subspecs/xmss/constants.py b/src/lean_spec/subspecs/xmss/constants.py
index 3c391827..f239cbcb 100644
--- a/src/lean_spec/subspecs/xmss/constants.py
+++ b/src/lean_spec/subspecs/xmss/constants.py
@@ -11,13 +11,16 @@
 
 from __future__ import annotations
 
+import math
 from typing import Final
 
+from pydantic import model_validator
+
 from lean_spec.config import LEAN_ENV
 from lean_spec.types import StrictBaseModel, Uint64
 from lean_spec.types.constants import OFFSET_BYTE_LENGTH
 
-from ..koalabear import P_BYTES, Fp
+from ..koalabear import P_BYTES, Fp, P
 
 
 class XmssConfig(StrictBaseModel):
@@ -45,8 +48,11 @@ def LIFETIME(self) -> Uint64:  # noqa: N802
     BASE: int
     """The alphabet size for the digits of the encoded message."""
 
-    FINAL_LAYER: int
-    """Number of top layers of the hypercube to map the hash output into."""
+    Z: int
+    """Number of base-`BASE` digits extracted from each field element."""
+
+    Q: int
+    """Quotient such that `Q * BASE^Z == P - 1`."""
 
     TARGET_SUM: int
     """The required sum of all codeword chunks for a signature to be valid."""
@@ -79,18 +85,19 @@ def LIFETIME(self) -> Uint64:  # noqa: N802
     """The output length of the main tweakable hash function."""
 
     CAPACITY: int
-    """The capacity of the Poseidon2 sponge, defining its security level."""
-
-    POS_OUTPUT_LEN_PER_INV_FE: int
-    """Output length per invocation for the message hash."""
+    """The capacity of the Poseidon1 sponge, defining its security level."""
 
-    POS_INVOCATIONS: int
-    """Number of invocations for the message hash."""
+    @model_validator(mode="after")
+    def _validate_decomposition(self) -> XmssConfig:
+        """Verify that Q * BASE^Z == P - 1."""
+        if self.Q * self.BASE**self.Z != P - 1:
+            raise ValueError(f"Q * BASE^Z must equal P-1={P - 1}")
+        return self
 
     @property
-    def POS_OUTPUT_LEN_FE(self) -> int:  # noqa: N802
-        """Total output length for the message hash."""
-        return self.POS_OUTPUT_LEN_PER_INV_FE * self.POS_INVOCATIONS
+    def MH_HASH_LEN_FE(self) -> int:  # noqa: N802
+        """Number of Poseidon output field elements needed for the aborting decode."""
+        return math.ceil(self.DIMENSION / self.Z)
 
     @property
     def PUBLIC_KEY_LEN_BYTES(self) -> int:  # noqa: N802
@@ -121,10 +128,11 @@ def SIGNATURE_LEN_BYTES(self) -> int:  # noqa: N802
 PROD_CONFIG: Final = XmssConfig(
     MESSAGE_LENGTH=32,
     LOG_LIFETIME=32,
-    DIMENSION=64,
+    DIMENSION=46,
     BASE=8,
-    FINAL_LAYER=77,
-    TARGET_SUM=375,
+    Z=8,
+    Q=127,
+    TARGET_SUM=200,
     MAX_TRIES=100_000,
     PARAMETER_LEN=5,
     TWEAK_LEN_FE=2,
@@ -132,8 +140,6 @@ def SIGNATURE_LEN_BYTES(self) -> int:  # noqa: N802
     RAND_LEN_FE=7,
     HASH_LEN_FE=8,
     CAPACITY=9,
-    POS_OUTPUT_LEN_PER_INV_FE=15,
-    POS_INVOCATIONS=1,
 )
 
 
@@ -142,7 +148,8 @@ def SIGNATURE_LEN_BYTES(self) -> int:  # noqa: N802
     LOG_LIFETIME=8,
     DIMENSION=4,
     BASE=4,
-    FINAL_LAYER=6,
+    Z=2,
+    Q=133169152,
     TARGET_SUM=6,
     MAX_TRIES=100_000,
     PARAMETER_LEN=5,
@@ -151,8 +158,6 @@ def SIGNATURE_LEN_BYTES(self) -> int:  # noqa: N802
     RAND_LEN_FE=7,
     HASH_LEN_FE=8,
     CAPACITY=9,
-    POS_OUTPUT_LEN_PER_INV_FE=15,
-    POS_INVOCATIONS=1,
 )
 
 
diff --git a/src/lean_spec/subspecs/xmss/message_hash.py b/src/lean_spec/subspecs/xmss/message_hash.py
index 13deb074..16956351 100644
--- a/src/lean_spec/subspecs/xmss/message_hash.py
+++ b/src/lean_spec/subspecs/xmss/message_hash.py
@@ -1,30 +1,30 @@
 """
-Defines the "Top Level" message hashing for the signature scheme.
+Defines the message hashing for the signature scheme using aborting hypercube encoding.
 
-### The Challenge: Efficiently Finding a Valid Codeword
+### The Challenge: Efficiently Encoding a Message as a Codeword
 
 The "Target Sum" signature scheme requires the signer to find a `codeword` whose
-digits sum to a specific value. This is equivalent to hashing a message and hoping the
-output is on a single, specific "layer" of a high-dimensional hypercube. The
-probability of this can be low, forcing the signer to try many times with different
-randomness (`rho`).
-
-### The Solution: "Top Level" Hashing
-
-This module implements a more efficient approach. Instead of targeting a single layer,
-we define a valid codeword as any vertex that lies within the **top `D` layers** of the
-hypercube (where `D` is `FINAL_LAYER` in the configuration). This significantly
-increases the target space, drastically reducing the number of retries the signer needs.
-
-This process involves three main stages:
-1.  **Input Preparation**: All inputs (message, epoch, randomness, etc.) are
-    unambiguously encoded into a uniform format (lists of field elements).
-2.  **Extended Hashing**: Poseidon2 is called iteratively to generate a long,
-    pseudorandom output digest, effectively behaving like an eXtendable-Output
-    Function (XOF).
-3.  **Mapping to Hypercube**: The long digest is treated as a large number, which
-    is then safely and deterministically mapped to a unique vertex within the
-    allowed top layers of the hypercube.
+digits sum to a specific value. This requires hashing a message and mapping the
+output to a vertex in a high-dimensional hypercube.
+
+### The Solution: Aborting Hypercube Encoding
+
+This module implements a circuit-friendly encoding based on rejection sampling of
+individual field elements, eliminating all big-integer arithmetic.
+
+For KoalaBear (`P = 2^31 - 2^24 + 1`), `P - 1 = Q * BASE^Z`, so each field element
+can be decomposed into `Z` base-`BASE` digits after dividing by `Q`. The only reject
+case is `A_i == P - 1` (probability ~4.7e-10 per FE — essentially never aborts).
+
+This is backed by the "Aborting Random Oracles" paper which proves
+indifferentiability from a theta-aborting random oracle when modeling Poseidon as a
+standard random oracle.
+
+The encoding proceeds in two stages:
+
+1. **Input Preparation**: All inputs are encoded into field elements.
+2. **Poseidon Hashing + Aborting Decode**: Poseidon1 produces `ceil(DIMENSION/Z)`
+   field elements, each decoded into `Z` base-`BASE` digits via rejection sampling.
 """
 
 from __future__ import annotations
@@ -38,7 +38,7 @@
 )
 from lean_spec.types import Bytes32, StrictBaseModel, Uint64
 
-from ..koalabear import Fp, P
+from ..koalabear import Fp
 from ._validation import enforce_strict_types
 from .constants import (
     PROD_CONFIG,
@@ -46,17 +46,12 @@
     TWEAK_PREFIX_MESSAGE,
     XmssConfig,
 )
-from .hypercube import (
-    hypercube_find_layer,
-    hypercube_part_size,
-    map_to_vertex,
-)
 from .types import Parameter, Randomness
 from .utils import int_to_base_p
 
 
 class MessageHasher(StrictBaseModel):
-    """An instance of the "Top Level" message hasher for a given config."""
+    """An instance of the message hasher using aborting hypercube encoding."""
 
     config: XmssConfig
     """Configuration parameters for the hasher."""
@@ -77,7 +72,7 @@ def encode_message(self, message: Bytes32) -> list[Fp]:
         The message bytes are interpreted as a single little-endian integer,
         which is then decomposed into its base-`P` representation, where `P`
         is the field prime. This provides a canonical mapping from bytes to
-        the algebraic structure required by Poseidon2.
+        the algebraic structure required by Poseidon1.
         """
         # Interpret the 32 little-endian bytes as a single large integer.
         acc = int.from_bytes(message, "little")
@@ -99,46 +94,39 @@ def encode_epoch(self, epoch: Uint64) -> list[Fp]:
         # Decompose the integer into its base-P representation.
         return int_to_base_p(acc, self.config.TWEAK_LEN_FE)
 
-    def _map_into_hypercube_part(self, field_elements: list[Fp]) -> list[int]:
+    def _aborting_decode(self, field_elements: list[Fp]) -> list[int] | None:
         """
-        Maps a long, pseudorandom digest to a unique vertex within the top layers
-        of the signature hypercube.
+        Decodes Poseidon output field elements into base-`BASE` digits via rejection sampling.
 
-        This is the core of the "Top Level" strategy. It takes a large, uniformly
-        random number and maps it to a point in a smaller, highly structured set.
+        For each field element `A_i`:
 
-        ### Mapping Algorithm
+        1. If `A_i >= Q * BASE^Z` (i.e. `A_i == P - 1`), abort and return `None`.
+        2. Compute `d_i = A_i // Q`, an integer in `[0, BASE^Z - 1]`.
+        3. Decompose `d_i` into `Z` base-`BASE` digits, least significant first.
 
-        1.  **Integer Reconstruction**: The input list of field elements is
-            interpreted as the base-P representation of a single, very large integer.
-
-        2.  **Modular Reduction**: This integer is reduced modulo the `domain_size`,
-            which is the total number of vertices in the target top layers. This
-            step maps the large random value to a unique index within the target set.
-
-        3.  **Index to Vertex**: This unique index is then deterministically
-            converted first into a `(layer, offset)` pair, and finally into the
-            specific coordinates of the corresponding hypercube vertex.
+        Collect all digits and return the first `DIMENSION` of them.
         """
-        # Get the config for this scheme.
         config = self.config
+        threshold = config.Q * config.BASE**config.Z
 
-        # Combine field elements into one large integer (big-endian, base-P).
-        acc = 0
+        digits: list[int] = []
         for fe in field_elements:
-            acc = acc * P + fe.value
+            a = fe.value
+
+            # Rejection: the only failing case is A_i == P - 1.
+            if a >= threshold:
+                return None
 
-        # Reduce this integer modulo the size of the target domain.
-        #
-        # The target domain is the set of all vertices in layers 0..FINAL_LAYER.
-        domain_size = hypercube_part_size(config.BASE, config.DIMENSION, config.FINAL_LAYER)
-        acc %= domain_size
+            # Integer quotient removes the Q-residue, leaving a uniform value in [0, BASE^Z - 1].
+            d = a // config.Q
 
-        # Find which layer the resulting index falls into, and its offset.
-        layer, offset = hypercube_find_layer(config.BASE, config.DIMENSION, acc)
+            # Decompose d into Z base-BASE digits, least significant first.
+            for _ in range(config.Z):
+                digits.append(d % config.BASE)
+                d //= config.BASE
 
-        # Map the offset within the layer to a unique vertex.
-        return map_to_vertex(config.BASE, config.DIMENSION, layer, offset)
+        # Take exactly DIMENSION digits.
+        return digits[: config.DIMENSION]
 
     def apply(
         self,
@@ -146,21 +134,12 @@ def apply(
         epoch: Uint64,
         rho: Randomness,
         message: Bytes32,
-    ) -> list[int]:
+    ) -> list[int] | None:
         """
-        Applies the full "Top Level" message hash and mapping procedure.
+        Applies message hashing followed by aborting hypercube decode.
 
-        This function generates a long pseudorandom digest by iteratively calling
-        Poseidon2 and then maps this digest to a candidate codeword (a vertex in
-        the hypercube).
-
-        ### Hashing with Extended Output
-
-        A single Poseidon2 compression call produces a relatively short output. To
-        generate a sufficiently large random number for the hypercube mapping, this
-        function calls Poseidon2 multiple times in a loop. The iteration number `i`
-        is used as a domain separator for each call, effectively creating a simple
-        eXtendable-Output Function (XOF) from the fixed-output hash.
+        Hashes the inputs with Poseidon1 to produce `MH_HASH_LEN_FE` field elements,
+        then decodes them into a candidate codeword via rejection sampling.
 
         Args:
             parameter: The public parameter `P`.
@@ -169,27 +148,19 @@ def apply(
             message: The 32-byte message to be hashed.
 
         Returns:
-            A candidate codeword, represented as a list of `DIMENSION` integers
-            (the coordinates of a vertex in the hypercube).
+            A candidate codeword (list of `DIMENSION` digits in `[0, BASE-1]`),
+            or `None` if the aborting decode rejects.
         """
         # Encode the message and epoch as field elements.
         message_fe = self.encode_message(message)
         epoch_fe = self.encode_epoch(epoch)
 
-        # Iteratively call Poseidon2 to generate a long hash output.
-        #
-        # The base input (rho || P || epoch || message) is reused each iteration.
+        # Call Poseidon1 once to produce the required number of output field elements.
         base_input = list(rho.data) + list(parameter.data) + epoch_fe + message_fe
-        poseidon_outputs: list[Fp] = []
-        output_len = self.config.POS_OUTPUT_LEN_PER_INV_FE
-        for i in range(self.config.POS_INVOCATIONS):
-            # Append iteration number as domain separator and hash.
-            poseidon_outputs.extend(
-                self.poseidon.compress(base_input + [Fp(value=i)], 24, output_len)
-            )
-
-        # Map the final aggregated list of field elements into a hypercube vertex.
-        return self._map_into_hypercube_part(poseidon_outputs)
+        poseidon_output = self.poseidon.compress(base_input, 24, self.config.MH_HASH_LEN_FE)
+
+        # Decode the field elements into base-BASE digits via rejection sampling.
+        return self._aborting_decode(poseidon_output)
 
 
 PROD_MESSAGE_HASHER = MessageHasher(config=PROD_CONFIG, poseidon=PROD_POSEIDON)
diff --git a/src/lean_spec/subspecs/xmss/poseidon.py b/src/lean_spec/subspecs/xmss/poseidon.py
index cbe0ccf0..d5f645d6 100644
--- a/src/lean_spec/subspecs/xmss/poseidon.py
+++ b/src/lean_spec/subspecs/xmss/poseidon.py
@@ -1,18 +1,18 @@
 """
-Defines the Poseidon2 hash functions for the Generalized XMSS scheme.
+Defines the Poseidon1 hash functions for the Generalized XMSS scheme.
 
-### The Cryptographic Engine: Why Poseidon2?
+### The Cryptographic Engine: Why Poseidon1?
 
 This module provides the low-level cryptographic engine for all internal hashing
-operations. It is built on **Poseidon2** hash function.
+operations. It is built on **Poseidon1** hash function.
 
-The choice of Poseidon2 is deliberate and critical for the scheme's ultimate goal.
-Unlike traditional hashes like SHA-3, Poseidon2 is an **arithmetization-friendly**
+The choice of Poseidon1 is deliberate and critical for the scheme's ultimate goal.
+Unlike traditional hashes like SHA-3, Poseidon1 is an **arithmetization-friendly**
 (or **SNARK-friendly**) hash function. Its algebraic structure is simple, making it
 exponentially faster to prove and verify inside a zero-knowledge proof system,
 which is essential for aggregating many signatures into a single, compact proof.
 
-This file provides wrappers for the two primary ways Poseidon2 is used:
+This file provides wrappers for the two primary ways Poseidon1 is used:
 
 1.  **Compression Mode**: A fast, fixed-input-size mode for hashing small,
     predictable data structures like a single hash digest or a pair of them.
@@ -27,37 +27,37 @@
 from lean_spec.types import StrictBaseModel
 
 from ..koalabear import Fp
-from ..poseidon2.permutation import (
+from ..poseidon1.permutation import (
     PARAMS_16,
     PARAMS_24,
-    Poseidon2,
-    Poseidon2Params,
+    Poseidon1,
+    Poseidon1Params,
 )
 from ._validation import enforce_strict_types
 from .utils import int_to_base_p
 
 
 class PoseidonXmss(StrictBaseModel):
-    """An instance of the Poseidon2 hash engine for the XMSS scheme."""
+    """An instance of the Poseidon1 hash engine for the XMSS scheme."""
 
-    params16: Poseidon2Params
-    """Poseidon2 parameters for 16-width permutation."""
+    params16: Poseidon1Params
+    """Poseidon1 parameters for 16-width permutation."""
 
-    params24: Poseidon2Params
-    """Poseidon2 parameters for 24-width permutation."""
+    params24: Poseidon1Params
+    """Poseidon1 parameters for 24-width permutation."""
 
     @model_validator(mode="after")
     def _validate_strict_types(self) -> PoseidonXmss:
         """Reject subclasses to prevent type confusion attacks."""
-        enforce_strict_types(self, params16=Poseidon2Params, params24=Poseidon2Params)
+        enforce_strict_types(self, params16=Poseidon1Params, params24=Poseidon1Params)
         return self
 
     def compress(self, input_vec: list[Fp], width: int, output_len: int) -> list[Fp]:
         """
-        Implements the Poseidon2 hash in **compression mode**.
+        Implements the Poseidon1 hash in **compression mode**.
 
         This mode is used for hashing fixed-size inputs and is the most efficient
-        way to use Poseidon2. It is used for traversing hash chains and building
+        way to use Poseidon1. It is used for traversing hash chains and building
         the internal nodes of the Merkle tree.
 
         ### Compression Algorithm
@@ -66,13 +66,13 @@ def compress(self, input_vec: list[Fp], width: int, output_len: int) -> list[Fp]
         1.  **Padding**: The `input_vec` is padded with zeros to match the full state `width`.
         2.  **Permutation**: The core cryptographic permutation is applied to the padded state.
         3.  **Feed-Forward**: The original padded input is added element-wise to the
-            permuted state. This is a key feature of the Poseidon2 design that
+            permuted state. This is a key feature of the Poseidon1 design that
             provides security against certain attacks.
         4.  **Truncation**: The result is truncated to the desired `output_len`.
 
         Args:
             input_vec: The list of field elements to be hashed.
-            width: The state width of the Poseidon2 permutation (16 or 24).
+            width: The state width of the Poseidon1 permutation (16 or 24).
             output_len: The number of field elements in the output digest.
 
         Returns:
@@ -90,8 +90,8 @@ def compress(self, input_vec: list[Fp], width: int, output_len: int) -> list[Fp]
         # Create a padded input by extending with zeros to match the state width.
         padded_input = list(input_vec) + [Fp(value=0)] * (width - len(input_vec))
 
-        # Apply the Poseidon2 permutation.
-        permuted_state = Poseidon2(params).permute(padded_input)
+        # Apply the Poseidon1 permutation.
+        permuted_state = Poseidon1(params).permute(padded_input)
 
         # Apply the feed-forward step, adding the input back element-wise.
         final_state = [p + i for p, i in zip(permuted_state, padded_input, strict=True)]
@@ -138,7 +138,7 @@ def sponge(
         width: int,
     ) -> list[Fp]:
         """
-        Implements the Poseidon2 hash using the **sponge construction**.
+        Implements the Poseidon1 hash using the **sponge construction**.
 
         This mode is used for hashing large or variable-length inputs. In this scheme,
         it is specifically used to hash the Merkle tree leaves, which consist of many
@@ -162,7 +162,7 @@ def sponge(
             input_vec: The input data of arbitrary length.
             capacity_value: The domain-separating value from `safe_domain_separator`.
             output_len: The number of field elements in the final output digest.
-            width: The width of the Poseidon2 permutation.
+            width: The width of the Poseidon1 permutation.
 
         Returns:
             A hash digest of `output_len` field elements.
@@ -188,7 +188,7 @@ def sponge(
         state[rate:] = capacity_value
 
         # Create the engine once for efficiency.
-        engine = Poseidon2(params)
+        engine = Poseidon1(params)
 
         # Absorb the input in rate-sized chunks.
         for i in range(0, len(padded_input), rate):
diff --git a/src/lean_spec/subspecs/xmss/target_sum.py b/src/lean_spec/subspecs/xmss/target_sum.py
index b6a80f77..fc94cc24 100644
--- a/src/lean_spec/subspecs/xmss/target_sum.py
+++ b/src/lean_spec/subspecs/xmss/target_sum.py
@@ -75,6 +75,10 @@ def encode(
         # Hash the inputs to map them to a potential codeword (a vertex in the hypercube).
         codeword_candidate = self.message_hasher.apply(parameter, epoch, rho, message)
 
+        # The aborting decode may reject if a field element equals P - 1.
+        if codeword_candidate is None:
+            return None
+
         # A codeword is valid only if it lies on the predefined hypercube layer.
         #
         # This is verified by checking if the sum of its coordinates equals TARGET_SUM.
diff --git a/src/lean_spec/subspecs/xmss/tweak_hash.py b/src/lean_spec/subspecs/xmss/tweak_hash.py
index 3657f051..60717190 100644
--- a/src/lean_spec/subspecs/xmss/tweak_hash.py
+++ b/src/lean_spec/subspecs/xmss/tweak_hash.py
@@ -1,9 +1,9 @@
 """
-Defines the Tweakable Hash function using Poseidon2.
+Defines the Tweakable Hash function using Poseidon1.
 
 ### The Problem: Hash Function Overload
 
-In a complex cryptographic scheme like XMSS, a single hash function (like Poseidon2)
+In a complex cryptographic scheme like XMSS, a single hash function (like Poseidon1)
 is used for many different purposes:
 1.  Hashing iteratively to form **hash chains**.
 2.  Hashing pairs of nodes to build the **Merkle tree**.
@@ -97,7 +97,7 @@ def _encode_tweak(self, tweak: TreeTweak | ChainTweak, length: int) -> list[Fp]:
         Encodes a structured tweak object into a list of field elements.
 
         It converts a high-level tweak context (like "Merkle tree, level 5, index 3")
-        into a low-level format that can be consumed by the Poseidon2 hash function.
+        into a low-level format that can be consumed by the Poseidon1 hash function.
 
         ### Encoding Algorithm
 
@@ -144,10 +144,10 @@ def apply(
         message_parts: list[HashDigestVector],
     ) -> HashDigestVector:
         """
-        Applies the tweakable Poseidon2 hash function to a message.
+        Applies the tweakable Poseidon1 hash function to a message.
 
         This is the main entry point for all internal hashing operations. It prepares
-        the inputs and routes them to the appropriate Poseidon2 function based on
+        the inputs and routes them to the appropriate Poseidon1 function based on
         the input size, ensuring optimal performance and security.
 
         ### Hashing Algorithm
@@ -157,7 +157,7 @@ def apply(
 
         2.  **Mode Selection**:
             - For small inputs (1 or 2 `HashDigest` parts), it uses the highly
-                efficient **compression mode** of Poseidon2.
+                efficient **compression mode** of Poseidon1.
             - For large inputs (many `HashDigest` parts, like a Merkle leaf),
                 it uses the more flexible **sponge mode**.
 
@@ -175,7 +175,7 @@ def apply(
         # Encode the high-level tweak structure into a list of field elements.
         encoded_tweak = self._encode_tweak(tweak, config.TWEAK_LEN_FE)
 
-        # Route to the correct Poseidon2 mode based on the input size.
+        # Route to the correct Poseidon1 mode based on the input size.
         if len(message_parts) == 1:
             # Case 1: Hashing a single digest (used in hash chains).
             #
diff --git a/src/lean_spec/subspecs/xmss/types.py b/src/lean_spec/subspecs/xmss/types.py
index 99ac8178..41fe7fc0 100644
--- a/src/lean_spec/subspecs/xmss/types.py
+++ b/src/lean_spec/subspecs/xmss/types.py
@@ -27,7 +27,7 @@ class PRFKey(BaseBytes):
 The fixed length of a hash digest in field elements.
 
 Derived from `TARGET_CONFIG.HASH_LEN_FE`. This corresponds to the output length
-of the Poseidon2 hash function used in the XMSS scheme.
+of the Poseidon1 hash function used in the XMSS scheme.
 """
 
 # Calculate the maximum number of nodes in a sparse Merkle tree layer:
@@ -49,7 +49,7 @@ class HashDigestVector(SSZVector[Fp]):
     """
     A single hash digest represented as a fixed-size vector of field elements.
 
-    This is the SSZ-compliant representation of a Poseidon2 hash output.
+    This is the SSZ-compliant representation of a Poseidon1 hash output.
     In SSZ notation: `Vector[Fp, HASH_DIGEST_LENGTH]`
 
     The fixed size enables efficient serialization when used in collections,
diff --git a/tests/lean_spec/subspecs/poseidon1/test_permutation.py b/tests/lean_spec/subspecs/poseidon1/test_permutation.py
new file mode 100644
index 00000000..45b0119b
--- /dev/null
+++ b/tests/lean_spec/subspecs/poseidon1/test_permutation.py
@@ -0,0 +1,101 @@
+"""Tests for the Poseidon1 permutation for widths 16 and 24.
+
+Test vectors are taken from Plonky3 (koala-bear/src/poseidon1.rs).
+To verify independently, run `cargo test` in the Plonky3 koala-bear crate.
+"""
+
+import pytest
+
+from lean_spec.subspecs.koalabear.field import Fp
+from lean_spec.subspecs.poseidon1.permutation import (
+    PARAMS_16,
+    PARAMS_24,
+    Poseidon1,
+    Poseidon1Params,
+)
+
+# --- Test Vectors (from Plonky3 koala-bear/src/poseidon1.rs) ---
+
+# Input vector for width 16: [0, 1, 2, ..., 15]
+INPUT_16 = [Fp(value=i) for i in range(16)]
+
+# Expected output for width 16.
+#
+# From Plonky3.
+EXPECTED_16 = [
+    Fp(value=610090613),
+    Fp(value=935319874),
+    Fp(value=1893335292),
+    Fp(value=796792199),
+    Fp(value=356405232),
+    Fp(value=552237741),
+    Fp(value=55134556),
+    Fp(value=1215104204),
+    Fp(value=1823723405),
+    Fp(value=1133298033),
+    Fp(value=1780633798),
+    Fp(value=1453946561),
+    Fp(value=710069176),
+    Fp(value=1128629550),
+    Fp(value=1917333254),
+    Fp(value=1175481618),
+]
+
+# Input vector for width 24: [0, 1, 2, ..., 23]
+INPUT_24 = [Fp(value=i) for i in range(24)]
+
+# Expected output for width 24.
+#
+# From Plonky3.
+EXPECTED_24 = [
+    Fp(value=511672087),
+    Fp(value=215882318),
+    Fp(value=237782537),
+    Fp(value=740528428),
+    Fp(value=712760904),
+    Fp(value=54615367),
+    Fp(value=751514671),
+    Fp(value=110231969),
+    Fp(value=1905276435),
+    Fp(value=992525666),
+    Fp(value=918312360),
+    Fp(value=18628693),
+    Fp(value=749929200),
+    Fp(value=1916418953),
+    Fp(value=691276896),
+    Fp(value=1112901727),
+    Fp(value=1163558623),
+    Fp(value=882867603),
+    Fp(value=673396520),
+    Fp(value=1480278156),
+    Fp(value=1402044758),
+    Fp(value=1693467175),
+    Fp(value=1766273044),
+    Fp(value=433841551),
+]
+
+
+@pytest.mark.parametrize(
+    "params, input_state, expected_output",
+    [
+        (PARAMS_16, INPUT_16, EXPECTED_16),
+        (PARAMS_24, INPUT_24, EXPECTED_24),
+    ],
+    ids=["width_16", "width_24"],
+)
+def test_permutation_vector(
+    params: Poseidon1Params, input_state: list[Fp], expected_output: list[Fp]
+) -> None:
+    """
+    Test the Poseidon1 permutation against known answer vectors.
+
+    Serves as a regression test to ensure logic consistency.
+    Reference: Plonky3 koala-bear/src/poseidon1.rs tests.
+    """
+    engine = Poseidon1(params)
+    output_state = engine.permute(input_state)
+
+    assert len(output_state) == params.width
+    assert output_state == expected_output, (
+        f"Permutation output for width {params.width} did not match."
+    )
diff --git a/tests/lean_spec/subspecs/poseidon2/test_permutation.py b/tests/lean_spec/subspecs/poseidon2/test_permutation.py
deleted file mode 100644
index f141d82e..00000000
--- a/tests/lean_spec/subspecs/poseidon2/test_permutation.py
+++ /dev/null
@@ -1,132 +0,0 @@
-"""Tests for the Poseidon2 permutation for widths 16 and 24."""
-
-import pytest
-
-from lean_spec.subspecs.koalabear.field import Fp
-from lean_spec.subspecs.poseidon2.permutation import (
-    PARAMS_16,
-    PARAMS_24,
-    Poseidon2,
-    Poseidon2Params,
-)
-
-# --- Test Vectors ---
-
-# Input vector for width 16
-INPUT_16 = [
-    Fp(value=894848333),
-    Fp(value=1437655012),
-    Fp(value=1200606629),
-    Fp(value=1690012884),
-    Fp(value=71131202),
-    Fp(value=1749206695),
-    Fp(value=1717947831),
-    Fp(value=120589055),
-    Fp(value=19776022),
-    Fp(value=42382981),
-    Fp(value=1831865506),
-    Fp(value=724844064),
-    Fp(value=171220207),
-    Fp(value=1299207443),
-    Fp(value=227047920),
-    Fp(value=1783754913),
-]
-# Expected output for width 16.
-EXPECTED_16 = [
-    Fp(value=190453639),
-    Fp(value=458899855),
-    Fp(value=383789123),
-    Fp(value=1958965770),
-    Fp(value=1470307143),
-    Fp(value=135446903),
-    Fp(value=1980271247),
-    Fp(value=26609194),
-    Fp(value=337889870),
-    Fp(value=543343594),
-    Fp(value=900082402),
-    Fp(value=1267415354),
-    Fp(value=1018710090),
-    Fp(value=902823573),
-    Fp(value=1161524658),
-    Fp(value=1483653556),
-]
-
-# Input vector for width 24
-INPUT_24 = [
-    Fp(value=886409618),
-    Fp(value=1327899896),
-    Fp(value=1902407911),
-    Fp(value=591953491),
-    Fp(value=648428576),
-    Fp(value=1844789031),
-    Fp(value=1198336108),
-    Fp(value=355597330),
-    Fp(value=1799586834),
-    Fp(value=59617783),
-    Fp(value=790334801),
-    Fp(value=1968791836),
-    Fp(value=559272107),
-    Fp(value=31054313),
-    Fp(value=1042221543),
-    Fp(value=474748436),
-    Fp(value=135686258),
-    Fp(value=263665994),
-    Fp(value=1962340735),
-    Fp(value=1741539604),
-    Fp(value=2026927696),
-    Fp(value=449439011),
-    Fp(value=1131357108),
-    Fp(value=50869465),
-]
-# Expected output for width 24.
-EXPECTED_24 = [
-    Fp(value=556605495),
-    Fp(value=885256863),
-    Fp(value=899046610),
-    Fp(value=1365261647),
-    Fp(value=799824470),
-    Fp(value=1363091631),
-    Fp(value=588658632),
-    Fp(value=173515151),
-    Fp(value=783308499),
-    Fp(value=1346358755),
-    Fp(value=1865380489),
-    Fp(value=1166148328),
-    Fp(value=1402826941),
-    Fp(value=434428806),
-    Fp(value=928050984),
-    Fp(value=1402941053),
-    Fp(value=201160368),
-    Fp(value=1850628943),
-    Fp(value=651578331),
-    Fp(value=12196116),
-    Fp(value=759351756),
-    Fp(value=948448587),
-    Fp(value=1529251366),
-    Fp(value=456048743),
-]
-
-
-@pytest.mark.parametrize(
-    "params, input_state, expected_output",
-    [
-        (PARAMS_16, INPUT_16, EXPECTED_16),
-        (PARAMS_24, INPUT_24, EXPECTED_24),
-    ],
-    ids=["width_16", "width_24"],
-)
-def test_permutation_vector(
-    params: Poseidon2Params, input_state: list[Fp], expected_output: list[Fp]
-) -> None:
-    """
-    Test the Poseidon2 permutation against known answer vectors.
-
-    Serves as a regression test to ensure logic consistency.
-    """
-    engine = Poseidon2(params)
-    output_state = engine.permute(input_state)
-
-    assert len(output_state) == params.width
-    assert output_state == expected_output, (
-        f"Permutation output for width {params.width} did not match."
-    )
diff --git a/tests/lean_spec/subspecs/validator/test_registry.py b/tests/lean_spec/subspecs/validator/test_registry.py
index df19872c..eb7cfd0b 100644
--- a/tests/lean_spec/subspecs/validator/test_registry.py
+++ b/tests/lean_spec/subspecs/validator/test_registry.py
@@ -155,7 +155,7 @@ def test_from_yaml_loads_assigned_validators(self, tmp_path: Path) -> None:
             yaml.dump(
                 {
                     "key_scheme": "SIGTopLevelTargetSumLifetime32Dim64Base8",
-                    "hash_function": "Poseidon2",
+                    "hash_function": "Poseidon1",
                     "encoding": "TargetSum",
                     "lifetime": 32,
                     "log_num_active_epochs": 5,
@@ -224,7 +224,7 @@ def test_from_yaml_unknown_node_returns_empty(self, tmp_path: Path) -> None:
             yaml.dump(
                 {
                     "key_scheme": "SIGTopLevelTargetSumLifetime32Dim64Base8",
-                    "hash_function": "Poseidon2",
+                    "hash_function": "Poseidon1",
                     "encoding": "TargetSum",
                     "lifetime": 32,
                     "log_num_active_epochs": 5,
@@ -253,7 +253,7 @@ def test_from_yaml_skips_missing_manifest_entries(self, tmp_path: Path) -> None:
             yaml.dump(
                 {
                     "key_scheme": "SIGTopLevelTargetSumLifetime32Dim64Base8",
-                    "hash_function": "Poseidon2",
+                    "hash_function": "Poseidon1",
                     "encoding": "TargetSum",
                     "lifetime": 32,
                     "log_num_active_epochs": 5,
@@ -300,7 +300,7 @@ def test_from_yaml_empty_file_returns_empty(self, tmp_path: Path) -> None:
             yaml.dump(
                 {
                     "key_scheme": "SIGTopLevelTargetSumLifetime32Dim64Base8",
-                    "hash_function": "Poseidon2",
+                    "hash_function": "Poseidon1",
                     "encoding": "TargetSum",
                     "lifetime": 32,
                     "log_num_active_epochs": 5,
@@ -329,7 +329,7 @@ def test_from_yaml_missing_key_file_raises(self, tmp_path: Path) -> None:
             yaml.dump(
                 {
                     "key_scheme": "SIGTopLevelTargetSumLifetime32Dim64Base8",
-                    "hash_function": "Poseidon2",
+                    "hash_function": "Poseidon1",
                     "encoding": "TargetSum",
                     "lifetime": 32,
                     "log_num_active_epochs": 5,
@@ -365,7 +365,7 @@ def test_from_yaml_invalid_key_file_raises(self, tmp_path: Path) -> None:
             yaml.dump(
                 {
                     "key_scheme": "SIGTopLevelTargetSumLifetime32Dim64Base8",
-                    "hash_function": "Poseidon2",
+                    "hash_function": "Poseidon1",
                     "encoding": "TargetSum",
                     "lifetime": 32,
                     "log_num_active_epochs": 5,
diff --git a/tests/lean_spec/subspecs/xmss/test_message_hash.py b/tests/lean_spec/subspecs/xmss/test_message_hash.py
index f5d0175d..d3fb56f7 100644
--- a/tests/lean_spec/subspecs/xmss/test_message_hash.py
+++ b/tests/lean_spec/subspecs/xmss/test_message_hash.py
@@ -1,8 +1,8 @@
 """
-Tests for the "Top Level" message hashing and encoding logic.
+Tests for the message hashing and aborting hypercube encoding logic.
 """
 
-from lean_spec.subspecs.koalabear import Fp
+from lean_spec.subspecs.koalabear import Fp, P
 from lean_spec.subspecs.xmss.constants import (
     TEST_CONFIG,
     TWEAK_PREFIX_MESSAGE,
@@ -57,10 +57,45 @@ def test_encode_epoch() -> None:
         seen_encodings.add(encoding)
 
 
-def test_apply_output_is_in_correct_hypercube_part() -> None:
+def test_aborting_decode_known_decomposition() -> None:
+    """Verifies aborting decode with a hand-computed example."""
+    hasher = TEST_MESSAGE_HASHER
+    config = TEST_CONFIG
+
+    # For TEST_CONFIG: Q=133169152, BASE=4, Z=2
+    # If A_i = Q * 5 = 665845760, then d_i = 5, digits = [5 % 4, 5 // 4] = [1, 1]
+    # If A_i = Q * 0 = 0, then d_i = 0, digits = [0, 0]
+    fe_list = [Fp(value=config.Q * 5), Fp(value=0)]
+    result = hasher._aborting_decode(fe_list)
+    assert result is not None
+    # First FE: d=5, digits (LSB first) = [1, 1]
+    # Second FE: d=0, digits (LSB first) = [0, 0]
+    # Take first DIMENSION=4 digits
+    assert result == [1, 1, 0, 0]
+
+
+def test_aborting_decode_boundary() -> None:
+    """Tests that FE = P-2 succeeds and FE = P-1 aborts."""
+    hasher = TEST_MESSAGE_HASHER
+    config = TEST_CONFIG
+
+    # P - 2 is the largest valid value (just below Q * BASE^Z = P - 1).
+    fe_valid = [Fp(value=P - 2)] * hasher.config.MH_HASH_LEN_FE
+    result = hasher._aborting_decode(fe_valid)
+    assert result is not None
+    assert len(result) == config.DIMENSION
+    assert all(0 <= d < config.BASE for d in result)
+
+    # P - 1 triggers the abort (A_i >= Q * BASE^Z).
+    fe_abort = [Fp(value=P - 1)]
+    result = hasher._aborting_decode(fe_abort)
+    assert result is None
+
+
+def test_apply_output_is_valid_codeword() -> None:
     """
-    Tests that the output of `apply` is a valid vertex that lies within
-    the top `FINAL_LAYER` layers of the hypercube.
+    Tests that the output of `apply` is `None` or a valid codeword with
+    DIMENSION digits each in `[0, BASE-1]`.
     """
     config = TEST_CONFIG
     hasher = TEST_MESSAGE_HASHER
@@ -73,23 +108,11 @@ def test_apply_output_is_in_correct_hypercube_part() -> None:
     message = Bytes32(b"\xaa" * 32)
 
     # Call the message hash function.
-    vertex = hasher.apply(parameter, epoch, randomness, message)
-
-    # Verify the properties of the output vertex.
-    #
-    # The length of the vertex must be equal to the hypercube's dimension.
-    assert len(vertex) == config.DIMENSION
-    # Each coordinate must be smaller than the base `w`.
-    assert all(0 <= coord < config.BASE for coord in vertex)
-
-    # Check that the vertex lies in the correct set of layers.
-    #
-    # By definition, a vertex is in layer `d` if `d = v*(w-1) - sum(coords)`.
-    #
-    # We require `d <= FINAL_LAYER`.
-    #
-    # This is equivalent to `sum(coords) >= v*(w-1) - FINAL_LAYER`.
-    coord_sum = sum(vertex)
-    min_required_sum = (config.BASE - 1) * config.DIMENSION - config.FINAL_LAYER
-
-    assert coord_sum >= min_required_sum, "Vertex is not in the top layers"
+    result = hasher.apply(parameter, epoch, randomness, message)
+
+    # The aborting decode may return None, but in practice it almost never does.
+    assert result is not None
+
+    # Verify the properties of the output codeword.
+    assert len(result) == config.DIMENSION
+    assert all(0 <= coord < config.BASE for coord in result)
diff --git a/tests/lean_spec/subspecs/xmss/test_security_levels.py b/tests/lean_spec/subspecs/xmss/test_security_levels.py
new file mode 100644
index 00000000..9f1c14ed
--- /dev/null
+++ b/tests/lean_spec/subspecs/xmss/test_security_levels.py
@@ -0,0 +1,294 @@
+"""
+Validates that XMSS parameter choices achieve adequate classical and quantum security.
+
+Based on:
+
+- [DKKW25c] "Hash-Based Multi-Signatures for Post-Quantum Ethereum"
+  (https://eprint.iacr.org/2025/055.pdf)
+- [HKKTW26] "Aborting Random Oracles"
+  (https://eprint.iacr.org/2026/016)
+
+The security analysis follows the framework of [DKKW25c] Section 6. Theorem 1
+gives an advantage bound as the sum of five terms. Each term divided by attacker
+running time must be at most `2^{-(k + log5)}`, yielding four independent
+constraints (Parameter Requirements 2 and 3):
+
+1. Digest (SM-UD/SM-PRE via Eq 8-9 / Eq 15)
+2. Public parameter (SM-TCR via Eq 6-7 / Eq 16)
+3. Message hash (SM-rTCR via Eq 10 / Eq 13)
+4. Randomness (SM-rTCR via Eq 10 / Eq 14)
+
+The abort correction from [HKKTW26] Corollary 1 and Remark 14 adjusts the
+message hash bound: the aborting decode effectively enlarges the output space
+to `|H|/(1 - theta)`, where `theta` is the abort probability.
+"""
+
+import math
+
+import pytest
+
+from lean_spec.subspecs.koalabear import P
+from lean_spec.subspecs.xmss.constants import PROD_CONFIG, XmssConfig
+from lean_spec.subspecs.xmss.hypercube import _calculate_layer_size
+
+
+def _compute_security_levels(config: XmssConfig) -> dict[str, float]:
+    """
+    Computes classical and quantum security levels for an XMSS configuration.
+
+    Returns a dict with keys:
+
+    - `k_classical`: effective classical security (bits)
+    - `k_quantum`: effective quantum security (bits)
+    - `expected_attempts`: expected signing attempts per message
+    - `signing_failure_log2`: log2 of probability that all MAX_TRIES attempts fail
+    """
+    v = config.DIMENSION
+    w_bits = int(math.log2(config.BASE))
+    base = config.BASE
+
+    # Bit sizes of the parameter spaces.
+    #
+    # Each KoalaBear field element contributes floor(log2(P)) = 31 bits.
+    fe_bits = 31
+    bits_digest = config.HASH_LEN_FE * fe_bits
+    bits_param = config.PARAMETER_LEN * fe_bits
+    bits_rand = config.RAND_LEN_FE * fe_bits
+
+    # Raw message hash output: v chunks of w bits each.
+    bits_msg = v * w_bits
+
+    # Abort correction from [HKKTW26] Corollary 1, Remark 14.
+    #
+    # Each field element aborts iff A_i >= Q * BASE^Z (i.e., A_i == P - 1).
+    # The non-abort probability per FE is (Q * BASE^Z) / P = (P - 1) / P.
+    # Over ell = ceil(v / Z) field elements, the total non-abort probability is:
+    #   (1 - theta) = ((P - 1) / P) ^ ell
+    #
+    # The aborting rTCR bound ([HKKTW26] Corollary 1) gains a factor (1 - theta),
+    # which is equivalent to hashing into a space of size |H| / (1 - theta).
+    # This adds -log2(1 - theta) bits to the effective message hash output.
+    wz = base**config.Z
+    q = config.Q
+    ell = math.ceil(v / config.Z)
+
+    non_abort_total = ((q * wz) / P) ** ell
+    abort_correction_bits = -math.log2(non_abort_total)
+
+    bits_msg_eff = bits_msg + abort_correction_bits
+
+    # Useful logarithmic constants.
+    log5 = math.log2(5)
+    log12 = math.log2(12)
+    log3 = math.log2(3)
+    log_lifetime = math.log2(config.LIFETIME)
+    logv = math.log2(v)
+    log_max_tries = math.log2(config.MAX_TRIES)
+    logqs = math.log2(config.LIFETIME)
+
+    # Classical security: minimum over four attack surfaces.
+    #
+    # Each bound derives from the requirement that each of the five terms in
+    # Theorem 1 satisfies Adv_i / T(A) <= 2^{-(k_C + log5)}.
+    k_classical = min(
+        # [DKKW25c] Eq (15): SM-UD + SM-PRE on the digest hash Th.
+        bits_digest - log5 - 2 * w_bits - log_lifetime - logv,
+        # [DKKW25c] Eq (16): SM-TCR on the public parameter space.
+        bits_param - log5 - 3,
+        # [DKKW25c] Eq (13) + [HKKTW26] Corollary 1: SM-rTCR on message hash.
+        bits_msg_eff - log5 - 1,
+        # [DKKW25c] Eq (14): SM-rTCR randomness reprogramming.
+        bits_rand - log5 - logqs - log_max_tries - 1,
+    )
+
+    # Quantum security: minimum over four attack surfaces.
+    #
+    # Uses quantum ROM bounds from [DKKW25c] Table 1.
+    k_quantum = min(
+        # [DKKW25c] Eq (15), quantum: digest hash.
+        bits_digest / 2 - log5 - 2 * w_bits - log_lifetime - logv - log12,
+        # [DKKW25c] Eq (16), quantum: public parameter.
+        (bits_param - 5) / 2 - log5 - 2,
+        # [DKKW25c] Eq (13) + [HKKTW26] Corollary 1, quantum: message hash.
+        (bits_msg_eff - 3) / 2 - log5 - 1,
+        # [DKKW25c] Eq (14), quantum: randomness reprogramming.
+        (bits_rand - logqs) / 2 - log5 - log3 - log_max_tries,
+    )
+
+    # Expected signing attempts for target-sum encoding.
+    #
+    # [DKKW25c] Construction 6, Lemma 7: the number of valid codewords is
+    # |C| = #{x in Z_W^v : sum(x_i) = T}, the layer size at distance
+    # d = v*(W-1) - T from the sink vertex. The inclusion-exclusion formula
+    # from _calculate_layer_size gives |C|.
+    #
+    # Success probability per attempt = P(no abort) * P(target layer | no abort).
+    d = v * (base - 1) - config.TARGET_SUM
+    layer_size = _calculate_layer_size(base, v, d)
+    layer_prob = layer_size / base**v
+    success_prob = non_abort_total * layer_prob
+    expected_attempts = 1 / success_prob
+
+    # [DKKW25c] Lemma 3: correctness error is delta^K where delta = 1 - success_prob.
+    signing_failure_log2 = config.MAX_TRIES * math.log2(1 - success_prob)
+
+    return {
+        "k_classical": k_classical,
+        "k_quantum": k_quantum,
+        "expected_attempts": expected_attempts,
+        "signing_failure_log2": signing_failure_log2,
+    }
+
+
+def test_prod_classical_security() -> None:
+    """Production parameters must achieve at least 128-bit classical security."""
+    levels = _compute_security_levels(PROD_CONFIG)
+    assert levels["k_classical"] >= 128, (
+        f"Classical security {levels['k_classical']:.2f} bits is below 128"
+    )
+
+
+def test_prod_quantum_security() -> None:
+    """Production parameters must achieve at least 64-bit quantum security."""
+    levels = _compute_security_levels(PROD_CONFIG)
+    assert levels["k_quantum"] >= 64, f"Quantum security {levels['k_quantum']:.2f} bits is below 64"
+
+
+def test_prod_signing_efficiency() -> None:
+    """Signing must succeed within a reasonable number of attempts on average."""
+    levels = _compute_security_levels(PROD_CONFIG)
+
+    # Expected attempts should be manageable (< 1000).
+    assert levels["expected_attempts"] < 1000, (
+        f"Expected {levels['expected_attempts']:.2f} signing attempts is too high"
+    )
+
+    # The probability of MAX_TRIES consecutive failures must be astronomically small.
+    # log2(failure_prob) < -128 means failure probability < 2^{-128}.
+    assert levels["signing_failure_log2"] < -128, (
+        f"Signing failure probability 2^{levels['signing_failure_log2']:.2f} is too high"
+    )
+
+
+def test_prod_abort_probability_is_negligible() -> None:
+    """
+    The aborting decode rejection probability must be negligible.
+
+    From [HKKTW26] Section 6.1: each FE has abort probability 1/P.
+    Over `ceil(v/Z)` FEs, the total abort probability is approximately
+    `ceil(v/Z) / P`.
+    """
+    config = PROD_CONFIG
+    ell = math.ceil(config.DIMENSION / config.Z)
+
+    # Per-FE non-abort probability: (Q * BASE^Z) / P = (P - 1) / P.
+    non_abort_per_fe = (config.Q * config.BASE**config.Z) / P
+    total_non_abort = non_abort_per_fe**ell
+
+    # The abort probability should be less than 2^{-28} (~3.7e-9).
+    abort_prob = 1 - total_non_abort
+    assert abort_prob < 2**-28, f"Abort probability {abort_prob:.2e} is not negligible"
+
+
+def test_prod_decomposition_invariant() -> None:
+    """
+    Validates the fundamental relationship Q * BASE^Z == P - 1.
+
+    From [HKKTW26] Section 6.1: for KoalaBear, P - 1 = 2^24 * 127.
+    With BASE = 2^w, the decomposition requires w | 24 so that
+    Z = 24 / w digits can be extracted from each field element.
+    """
+    config = PROD_CONFIG
+
+    # Core decomposition invariant (also checked at config construction time).
+    assert config.Q * config.BASE**config.Z == P - 1
+
+    # w must divide 24 for the rejection sampling to work with KoalaBear.
+    #
+    # P - 1 = 2^24 * 127, and BASE = 2^w, so we need w | 24.
+    w_bits = int(math.log2(config.BASE))
+    assert config.BASE == 2**w_bits, "BASE must be a power of 2"
+    assert 24 % w_bits == 0, f"w={w_bits} must divide 24"
+
+    # Z must equal 24 / w for the optimal decomposition (alpha = 1).
+    assert config.Z == 24 // w_bits, f"Z={config.Z} must equal 24/w={24 // w_bits}"
+
+
+def test_prod_mh_hash_len_is_consistent() -> None:
+    """
+    The Poseidon output length must produce enough digits to cover DIMENSION.
+
+    From [HKKTW26] Section 6.1: ell = ceil(v / z) field elements produce
+    ell * z >= v base-w digits.
+    """
+    config = PROD_CONFIG
+    assert config.MH_HASH_LEN_FE * config.Z >= config.DIMENSION
+
+
+def test_prod_binding_constraint_is_message_hash() -> None:
+    """
+    Verify the binding (smallest) constraint is the message hash for both
+    classical and quantum security, matching the design intent from [DKKW25c].
+    """
+    config = PROD_CONFIG
+    v = config.DIMENSION
+    w_bits = int(math.log2(config.BASE))
+    fe_bits = 31
+
+    bits_digest = config.HASH_LEN_FE * fe_bits
+    bits_param = config.PARAMETER_LEN * fe_bits
+    bits_rand = config.RAND_LEN_FE * fe_bits
+    bits_msg = v * w_bits
+
+    log5 = math.log2(5)
+    log_lifetime = math.log2(config.LIFETIME)
+    logv = math.log2(v)
+    log_max_tries = math.log2(config.MAX_TRIES)
+
+    # Classical: the message hash bound v*w - log5 - 1 should be the tightest.
+    classical_bounds = [
+        bits_digest - log5 - 2 * w_bits - log_lifetime - logv,
+        bits_param - log5 - 3,
+        bits_msg - log5 - 1,
+        bits_rand - log5 - log_lifetime - log_max_tries - 1,
+    ]
+    assert classical_bounds.index(min(classical_bounds)) == 2, (
+        "Classical binding constraint should be message hash (index 2)"
+    )
+
+
+@pytest.mark.parametrize(
+    "param_name, value",
+    [
+        ("DIMENSION", 46),
+        ("BASE", 8),
+        ("Z", 8),
+        ("Q", 127),
+        ("TARGET_SUM", 200),
+        ("LOG_LIFETIME", 32),
+        ("PARAMETER_LEN", 5),
+        ("TWEAK_LEN_FE", 2),
+        ("MSG_LEN_FE", 9),
+        ("RAND_LEN_FE", 7),
+        ("HASH_LEN_FE", 8),
+        ("CAPACITY", 9),
+    ],
+)
+def test_prod_config_matches_reference(param_name: str, value: int) -> None:
+    """
+    Guards against accidental parameter drift.
+
+    These values must match the canonical Rust implementation (leanSig).
+    """
+    assert getattr(PROD_CONFIG, param_name) == value
+
+
+def test_print_security_summary(capsys: pytest.CaptureFixture[str]) -> None:
+    """Prints a human-readable summary of the security analysis (informational)."""
+    levels = _compute_security_levels(PROD_CONFIG)
+    print("\n--- XMSS Production Security Summary ---")
+    print(f"Classical security:       {levels['k_classical']:.2f} bits")
+    print(f"Quantum security:         {levels['k_quantum']:.2f} bits")
+    print(f"Expected sign attempts:   {levels['expected_attempts']:.2f}")
+    print(f"Signing failure (log2):   {levels['signing_failure_log2']:.2f}")
+    print("----------------------------------------")
diff --git a/tests/lean_spec/subspecs/xmss/test_strict_types.py b/tests/lean_spec/subspecs/xmss/test_strict_types.py
index a0e45af4..ac27014e 100644
--- a/tests/lean_spec/subspecs/xmss/test_strict_types.py
+++ b/tests/lean_spec/subspecs/xmss/test_strict_types.py
@@ -8,7 +8,7 @@
 import pytest
 from pydantic import ValidationError
 
-from lean_spec.subspecs.poseidon2.permutation import Poseidon2Params
+from lean_spec.subspecs.poseidon1.permutation import Poseidon1Params
 from lean_spec.subspecs.xmss.constants import PROD_CONFIG, TEST_CONFIG, XmssConfig
 from lean_spec.subspecs.xmss.interface import GeneralizedXmssScheme
 from lean_spec.subspecs.xmss.message_hash import PROD_MESSAGE_HASHER, MessageHasher
@@ -327,27 +327,27 @@ def test_poseidon_accepts_exact_types(self) -> None:
         assert poseidon.params16 == PROD_POSEIDON.params16
 
     def test_poseidon_rejects_subclass_params16(self) -> None:
-        """PoseidonXmss rejects Poseidon2Params subclass for params16."""
+        """PoseidonXmss rejects Poseidon1Params subclass for params16."""
 
-        class CustomParams(Poseidon2Params):
+        class CustomParams(Poseidon1Params):
             pass
 
-        custom_params = Poseidon2Params.__new__(CustomParams)
+        custom_params = Poseidon1Params.__new__(CustomParams)
         custom_params.__dict__.update(PROD_POSEIDON.params16.__dict__)
 
-        with pytest.raises(TypeError, match="params16 must be exactly Poseidon2Params"):
+        with pytest.raises(TypeError, match="params16 must be exactly Poseidon1Params"):
             PoseidonXmss(params16=custom_params, params24=PROD_POSEIDON.params24)
 
     def test_poseidon_rejects_subclass_params24(self) -> None:
-        """PoseidonXmss rejects Poseidon2Params subclass for params24."""
+        """PoseidonXmss rejects Poseidon1Params subclass for params24."""
 
-        class CustomParams(Poseidon2Params):
+        class CustomParams(Poseidon1Params):
             pass
 
-        custom_params = Poseidon2Params.__new__(CustomParams)
+        custom_params = Poseidon1Params.__new__(CustomParams)
         custom_params.__dict__.update(PROD_POSEIDON.params24.__dict__)
 
-        with pytest.raises(TypeError, match="params24 must be exactly Poseidon2Params"):
+        with pytest.raises(TypeError, match="params24 must be exactly Poseidon1Params"):
             PoseidonXmss(params16=PROD_POSEIDON.params16, params24=custom_params)
 
     def test_poseidon_rejects_wrong_type_params16(self) -> None: