Calculate a Hash
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Recent Hashes

Value Algorithm Hash
fa4c6b3e4d7fea90b60af46f16c2536e md5 32a6d0580840fda80641acd0c0fb6309
aad3b435b51404eeaad3b435b51404ee:31d6cfe0d16ae931b73c59d7e0c089c0 md5 fa4c6b3e4d7fea90b60af46f16c2536e
c320ac4d071150413bc3e7fd18afbc25e9b9fd704d138c11cff9ae7438d235a2 md5 0450e32dea40e96eab426ddf6d9a41c2
585b9941da6fb30bb23c29da3985a9a8173d8d23633ee82e6b1b517627fd761f md5 ab5f5fa7d68ca0014d02600b922f2180
T9yD14Nj9j7xAB4dbGeiX9h8unkKHxuWwb md5 661d4627bc496870f2937d0890edb5f2
413495CA7427E80C40907D61DD583FC5BB05F0A865 md5 ac661fc5f943806705e580097b1e4ec8
TTSt9n1G9sS77s3KEJ9hg4yjxAjzkUryDy md5 482d9eb4f7e77b9d380ad88fad29ccde
E98381FC91EDD42FBFC41F475F3A83C1AD260071 md5 c71d5c9db48a4b03ea87223b536471ab
E520F25341F5E89E743A6A3A335090CE8EBDDCA1 md5 e9a7214148785cb879cbbbe0e8a0efa1
3316f336a592cec7dad540d86c2ff7ce md5 2cfeb74ece8289c5fcb092a751660f99
686463954 md5 e7ecf730e0308481d6cb5f293210415b
83246130854913d8cce3f7e360cf4b6eabf48074bcc3e1df54ded94b2b059412 md5 39e7320dcc12f7c28b8adb026740cb30
5BA68F35I_%3E%3B%3BG3gdc%3E%3EFF9g5deA82hhh%3F%3Ea%3B22gdh%3Ee%3B%3B%6025%60A682bhddeA82h4IBA68F2gd%60%3E%3B%3B%3B%60g5c%3E%3EFF%60hd%3C%3Ea%3EFbhh_%3Fe8F255g%3EeEG32d%60%3EA83hg5%3C%3EaF2bhhB%3Fa8Gf55g%3Ee%3B%3C32d%60A6FF9g5%3CAA82hhh%3F%3Ea%3B22gd%60%3E%3BEG32d%60A6FGfg5%3CAJ82hh5%3F%3Ea%3B3f55_%3E%3BEG32d%60A682bhddeA82hhh%3F%3Fa8F2gdh%3Ee%3B%3B%60g5c%3EAGF9g5dca8Fhhh_%3Fe8Gfgd%60%3E%3B%3BF%6025%60A682bhd%3CAA82h4I_A%3B8Gfgdh%3EeEG3gdc%3E%3E82bhd%3CAJ%3E2bhh_%3Fe8F255g%3EeEF%60g5c%3EAFF%60hd%3CAA%3E2b4I%3F%3Ea%3B3fgd%3E%3EeEF%60g5cA6FF9g5%3C%3Ea8Fhh5%3F%3Ea%3B22gdh%3EeEG3gdcA683hg5deA%3E2bhh%3F%3Ea%3B22gd%60%3E%3BEG72d%60A682bhd%3C%3Ea%3EFb4I_%3Ee%3B23gdh%3EeEF%6025%60A6FF%60hd%3C%3EaF2bhh%3F%3Ea%3B3f55g%3EeEF%60g5c%3EAFF9g5deA%3E2b4I%3F%3Ea%3B3fgd%3E%3EeEF%6025%60A6FF9g5%3C%3Ea8Fhh5%3F%3Fa8F255g%3EeEG3gdcA683hg5%3CAA%3E2bhh_%3Ee%3B22gd%60%3E%3BEG72d%60%3E%3E82bhddeA82h4I_A%3B8Gf55_%3E%3BEG32d%60%3E%3E82bhd%3CAJ82h4I%3F%3Ea%3B3f55g%3EeEF%60g5c%3EAFF%60hd%3C%3Ea8Fhhh_%3Ee%3B3f5Ig%3EeEG32d%60%3E%3EFF9g5%3C%3 md5 132fa44bab4d4ddae074751b50bcab3c
K68vbdEjh4u md5 1c27505b39a1bf8ac13628a6c0dec6ef
21ff54d0e51d8542ce409b7541bed6b5e853d7e2408507eba3d823f94749d118b69fd3971239a5c35673cc5531b2ed87 md5 866268473816e3bc40fccdd9f7b9ee2e
feather md5 82d65a575279b463b10fbb964ee0f7a9
classroom md5 c756662595bb0948d9bbe352fef1c53a
7e5d6cfa2d2ba44b45ed0629647713b8795644df63838b96183035aa13bfdf7b72e42d9b7a58412d25c4423e6fd8d606 md5 10f032534b23a7d84481db3c74a4a1f3
oscar md5 f156e7995d521f30e6c59a3d6c75e1e5
0e4073ebd4d6a3e159fb5867ba7e30a07c588123dd6042e48aa1dd4284cbf5884b494ee2a0eceaf1b538e73d1aa7cdb2 md5 2b23f3ff03ecd43c817b9551ccedd2c9

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.