Calculate a Hash
Decrypt (search for a match)

Recent Hashes

Value Algorithm Hash
reallychel md5 61e00b0d68031d0b9f09b4a69114b523
ortspoon md5 a95f6501960c33ee0be25b1ecf6898a0
interestec md5 06dfd95e518528114dffcbc69390265e
immersivelabs md5 60d755e5b8cdd36509e5426e5190e240
1111111111111111111114oLvT2 md5 04ed3a57b8c60109770cca36c2d2cab2
3f20363f292023205d202f706f6f6c696e2e636f6d2ffabe6d6db446223f3fb57e203c3f3f20273f3f3f2041 fa3f203955dcb525203f3f20a32066e8b3203f3f20543f202a3f20ae75207e20e1203d20605c2055 3f20417d202c3f202320e93f20ae md5 6bc5439a0d0001009110e8a9adeb26da
b73fdaa1fb7669da760b49600c45d9be md5 2c37f358f131e68d1e3ee5678881950b
16fae0f822f42cb4073441aa71fb1a805383d0ecee8bfb725585dda031b0640d md5 c7916dfbe15d150f8f24197388a59de4
18KsfuHuzQaBTNLASyj15hy4LuqPUo1FNB md5 ca0bce9f1d4cba68606ebba3c8780983
483045022100f5c26eee36e47b5ac824254398e1b82e2baaf53c645366bdd0b359e2cd01c010022067d6e273e289285360d49961152d599581446bbda5286e912073ac5f27ef266e0121024b0faa9624763002e963816b2f6774df0dedd770896a9511cb5c9d90f674ecda md5 9ce692e870cbea451a95478db5e5665b
000000000000000000000000000000000000000AF55FC59C335C8EC67ED24826 md5 cd3a83c49fbbe6a0ce359ccab8b34beb
b295ab91a74ae7048c0ba523c03511e3 md5 c2bb258cb8793d12affd4da96f66002d
4730440220665c124a98122568bfa32075cf154c2247260e525a75c43c5041128d06c0a8b9022023bca9f1260c2d3b361251b9ced6808330a807e28072ce14ad31eeea29720d6301210309976ba5570966bf889196b7fdf5a0f9a1e9ab340556ec29f8bb60599616167d md5 9020cc8c278e6d15dceafe0f501fcd8a
483045022100bc4c97ae15e1ad54710af9b446ab4759a66ec06b79687c73066516944eed34530220719557ce013ab808edde3f835f55dec31ad5b4c78fe6090e3c5ac7d8e010ef3d0141047a0e5ead1210acebb8bcc1243cdc4d0d8bd3080116a1785af87dc064050f6aeb960d49694b1230854a84f9a8d51756aa3d53346717081d5ec6d59326b9eecb77 md5 a7f66ccab1be048874052277366c3364
b962049694b1230854a84f9a8d51756aa3d53346717081d5ec6d59326b9eecb77 md5 24475a2101f990cb029d6893925e89f7
0311569442e870326ceec0de24eb5478c19e146ecd9d15e4666440f2f638875f42 md5 c8585ab2466959b94a87a30d8ee4ea8f
00000000000000000000000000000000000000000000000002C675B852189A21 md5 f03e421e7bcaa8de2e4b2533504ab970
00000000000000000000000000000000000000000527A792B183C7F64A0E8B1F4 md5 bf63d8cfeed7384131c9cc0aebce1c71
19eVSDuizydXxhohGh8Ki9WY9KsHdSwoQC md5 bdf4d1729ce9df7d2c6bd3252388c3fb
02967a5905d6f3b420959a02789f96ab4c3223a2c4d2762f817b7895c5bc88a045 md5 c951f617be176a53a9862cebfab054e0

About Hash function

A hash function is any algorithm that maps data of a variable length to data of a fixed length. The values returned by a hash function are called hash values, hash codes, hash sums, checksums or simply hashes.

Hash functions are primarily used to generate fixed-length output data that acts as a shortened reference to the original data. This is useful when the original data is too cumbersome to use in its entirety.

One practical use is a data structure called a hash table where the data is stored associatively. Searching for a person's name in a list is slow, but the hashed value can be used to store a reference to the original data and retrieve constant time (barring collisions). Another use is in cryptography, the science of encoding and safeguarding data. It is easy to generate hash values from input data and easy to verify that the data matches the hash, but hard to 'fake' a hash value to hide malicious data. This is the principle behind the Pretty Good Privacy algorithm for data validation.

Hash functions are also used to accelerate table lookup or data comparison tasks such as finding items in a database, detecting duplicated or similar records in a large file, finding similar stretches in DNA sequences, and so on.

A hash function should be deterministic: when it is invoked twice on pieces of data that should be considered equal (e.g., two strings containing exactly the same characters), the function should produce the same value. This is crucial to the correctness of virtually all algorithms based on hashing. In the case of a hash table, the lookup operation should look at the slot where the insertion algorithm actually stored the data that is being sought for, so it needs the same hash value.

Hash functions are typically not invertible, meaning that it is not possible to reconstruct the input datum x from its hash value h(x) alone. In many applications, it is common that several values hash to the same value, a condition called a hash collision. Since collisions cause "confusion" of objects, which can make exact hash-based algorithm slower approximate ones less precise, hash functions are designed to minimize the probability of collisions. For cryptographic uses, hash functions are engineered in such a way that is impossible to reconstruct any input from the hash alone without expending great amounts of computing time (see also One-way function).

Hash functions are related to (and often confused with) checksums, check digits, fingerprints, randomization functions, error-correcting codes, and cryptographic. Although these concepts overlap to some extent, each has its own uses and requirements and is designed and optimized differently. The Hash Keeper database maintained by the American National Drug Intelligence Center, for instance, is more aptly described as a catalog of file fingerprints than of hash values.