Research
Security News
Malicious npm Package Targets Solana Developers and Hijacks Funds
A malicious npm package targets Solana developers, rerouting funds in 2% of transactions to a hardcoded address.
@ronomon/hash-table
Advanced tools
Fast, reliable cuckoo hash table for Node.js.
npm install @ronomon/hash-table
Why not use a vanilla Javascript object (or Set or Map) as a hash table?
A vanilla object has no interface to pre-allocate table capacity in advance, and a Set or Map constructor only accepts an iterable. If the Javascript engine's underlying implementation of a vanilla object is a hash table, then a vanilla object must resize multiple times (copying every key and value multiple times) while you insert millions of elements.
A vanilla object has no concept of binary keys. Encoding binary keys as hexadecimal or Base64 strings is slow, and Javascript strings have additional storage overhead.
Extreme GC pause times. Millions of pointers in a vanilla object can block the Node.js event loop every few seconds for tens to hundreds of milliseconds at a time, whenever the GC needs to mark every pointer in the object.
A simple comparison, which you can run yourself:
node vanilla.js
Ignoring any GC implications or per-key memory overhead considerations, which are more serious:
keySize=16 bytes, valueSize=0 bytes
@ronomon/hash-table: Inserting 4000000 elements...
@ronomon/hash-table: 783ms
new Set(): Inserting 4000000 elements...
new Set(): 3695ms
vanilla object: Inserting 4000000 elements...
vanilla object: 5557ms
@ronomon/hash-table
features several design decisions and optimizations:
Each element, a key and corresponding value, can reside in at most 1 of 2 possible buckets, guaranteeing constant lookup time in the worst-case.
Each bucket contains up to 8 elements to support a hash table load factor of
80% or higher, unlike linear or chained hash tables which support a load
factor (elements / capacity
) of at most 50% and which waste the other 50% of
memory. A more efficient load factor means that table resizes are less
frequent.
Each element in a bucket has a tag, which is an 8-bit hash of the key. When searching for an element in a bucket, these 8-bit tags are compared first, eliminating comparisons against most keys in the bucket.
Cache misses across buckets are reduced by an order of magnitude. In the case of a naive cuckoo hash table, if an element is not in its first bucket then its second bucket must be fetched from memory, causing a cache miss, which is slow and why cuckoo hashing is sometimes overlooked in favor of linear probing or double hashing. However, in our design, the first bucket has an 8-byte coarse-grained bloom filter (k=1). If the element is not in this bloom filter, the element is guaranteed not to be in either of its first or second buckets, and a cache miss can be avoided nearly 90% of the time.
The 8-bit tag further contributes to reduced cache misses within buckets when keys or values are large.
Each element is included in its first bucket's bloom filter, regardless of whether the element is in its first or second bucket, so that a negative lookup can be performed in a single branch by testing against a single bit in the bloom filter instead of testing against all 8 tags.
Each bucket has a 1-byte bitmap indicating which of the 8 slots in the bucket contain elements, so that the first empty slot in a bucket can be found with a single branch on a 256-byte precomputed lookup table instead of iterating across all 8 slots.
Each element's key is hashed with 2 independent hash functions to locate its first and second buckets. These hashes are computed by interleaving both hash function lookup tables into a single interleaved hash function lookup table for optimal locality of reference.
The hash function requires keys to be a multiple of 4 bytes and uses an unrolled loop, so that keys are hashed 4 bytes at a time.
The number of buckets in a table is a power of 2 for a fast bitwise mod. While Daniel Lemire's excellent fast alternative to the modulo reduction yields better entropy mixing of all available bits, it is not used since Javascript's 64-bit integer operations are not fast.
Each bucket is padded to a multiple of 64 bytes for optimal cache line alignment.
An unrolled copy method is selected at instantiation to copy the key and value without branching if the key or value is 4, 8, 16, 32, 64, 128, 256 bytes etc. A native copy method is used for larger values.
Methods accept a buffer and a buffer offset to avoid a buffer slice. While a buffer slice may not copy the underlying memory, it adds overhead through allocating an object which must eventually be reclaimed by the GC. This overhead is considerable when inserting millions of elements.
The CLOCK LRU eviction algorithm is supported at an overhead of 2 bits per element, so that the hash table can be used as a fast user-space cache.
Surprisingly, the implementation is written in Javascript to avoid the 100-200ns bridging cost of calling into C from Javascript. Even a C implementation making use of SIMD instructions may struggle to regain the cost of being called from Javascript.
@ronomon/hash-table
was designed for billions of elements:
Each hash table instance is partitioned across multiple buffers and scales linearly up to a maximum of 4,294,967,296 elements or 16 TB of memory, whichever comes first.
Exactly 2.5 bytes of overhead per element at 100% load.
The implementation is purely in terms of huge flat buffer instances. Apart from jumping to a huge flat buffer instance, there is no pointer chasing. Most importantly, this sidesteps memory fragmentation issues and is GC friendly. If the GC cannot look into the buffers, the GC has nothing further to do. This places almost zero load on the GC.
Tabulation hashing is used as a fast high-quality hash function instead of more popular hash functions such as MurmurHash etc. Tabulation hashing has excellent proven theoretical properties, guarantees 3-independence, consists solely of table lookups and XOR, is one of the fastest hash functions when evaluating hash functions implemented in Javascript, and is resistant to hash flooding attacks. When compared with hash functions which use magic numbers and attempt avalanche through empirical methods, tabulation hashing is easier to understand and implement, and harder to get wrong.
Each 8-byte bloom filter has a separate 1-byte count of the number of elements in second position, so that bloom filters can be reset without a runaway increase in false positives.
Each 8-byte bloom filter is partitioned into 8 subsidiary filters, so that bloom filters can be reset with minimal latency. Further, this solves the edge case where a key in second position is never removed while other keys are churned repeatedly. Without bloom filter partitioning, the bucket's false positive rate would approach 100%. With bloom filter partitioning, only 1/8th of the bucket's filter would be adversely affected.
A maximum of 16 cuckoo displacements per insert are allowed in order to limit recursion and to keep the algorithm intuitive. If both buckets are full and no element can be displaced into another bucket, the buffer is resized by a factor of 2 to make space for the insert.
Each buffer is resized independently of other buffers so that the resize latency for a massive hash table is bounded per insert. This guarantee does NOT extend to a batch of inserts. For example, subsequent inserts may cause other buffers to resize in close succession. But then again, you can reserve or pre-allocate a massive hash table upfront to eliminate resize latency.
The number of resize attempts per insert is bounded as a precaution against resource exhaustion in the unlikely event that several resizes do not produce an empty slot.
var hashTable = new HashTable(keySize, valueSize, [elementsMin], [elementsMax])
keySize
An integer, must be a multiple of 4 bytes, up to a maximum of 64
bytes (HashTable.KEY_MAX
).valueSize
An integer, from 0 bytes up to a maximum of 1 MB
(HashTable.VALUE_MAX
).elementsMin
An integer, a hint as to the minimum number of elements
expected to be inserted, to avoid unnecessary resizing over the short term.elementsMax
An integer, a hint as to the maximum number of elements
expected to be inserted, to ensure sufficient capacity over the long term.hashTable.set(key, keyOffset, value, valueOffset)
Inserts or updates an element in the hash table.
key
A buffer, contains the key to be inserted or updated.keyOffset
An integer, the offset into key
at which the key begins.value
A buffer, contains the value to be inserted or updated.valueOffset
An integer, the offset into value
at which the value begins.0
if the element was inserted, 1
if the element was
updated.hashTable.get(key, keyOffset, value, valueOffset)
Retrieves an element's value from the hash table.
key
A buffer, contains the key to be retrieved.keyOffset
An integer, the offset into key
at which the key begins.value
A buffer, the element's value will be copied into this buffer if the
element exists.valueOffset
An integer, the offset into value
at which to begin copying.0
if the element was not found, 1
if the element was
found.hashTable.exist(key, keyOffset)
Tests whether an element exists in the hash table.
key
A buffer, contains the key to be tested.keyOffset
An integer, the offset into key
at which the key begins.0
if the element was not found, 1
if the element was
found.hashTable.unset(key, keyOffset)
Removes an element from the hash table.
key
A buffer, contains the key to be removed.keyOffset
An integer, the offset into key
at which the key begins.0
if the element was not found, 1
if the element was
removed.hashTable.cache(key, keyOffset, value, valueOffset)
Similar to set()
but inserts by evicting a least recently used element, rather
than resizing the hash table.
key
A buffer, contains the key to be inserted or updated.keyOffset
An integer, the offset into key
at which the key begins.value
A buffer, contains the value to be inserted or updated.valueOffset
An integer, the offset into value
at which the value begins.0
if the element was inserted, 1
if the element was
updated, 2
if the element was inserted by evicting another element.cache()
will never resize the hash table. Use the same elementsMin
and
elementsMax
arguments to size the hash table appropriately.
cache()
and set()
are mutually exclusive and cannot be used on the same
hash table instance. This restriction is in place to prevent the user from
accidentally evicting elements which were inserted by set()
, and to enable
several caching optimizations. When using cache()
, you can still use get()
,
exist()
and unset()
to retrieve, test and remove cached elements.
hashTable.capacity
An integer, read-only, the current total capacity of the hash table, i.e. the number of elements which the hash table can accommodate at 100% load, which will increase through automatic resizing of the hash table buffers.
hashTable.length
An integer, read-only, the number of elements actually present in the hash table.
hashTable.load
A fraction between 0 and 1, read-only, the length of the hash table divided by the capacity of the hash table.
hashTable.size
An integer, read-only, the total size of all hash table buffers in bytes.
var HashTable = require('@ronomon/hash-table');
var keySize = 16;
var valueSize = 4;
var elementsMin = 1024; // Optional. Reserve space for at least 1,024 elements.
var elementsMax = 65536; // Optional. Expect at most 65,536 elements.
var hashTable = new HashTable(keySize, valueSize, elementsMin, elementsMax);
// set():
var key = Buffer.alloc(keySize);
var keyOffset = 0;
var value = Buffer.alloc(valueSize);
var valueOffset = 0;
var result = hashTable.set(key, keyOffset, value, valueOffset);
if (result === 0) console.log('set(): element was inserted');
if (result === 1) console.log('set(): element was updated');
// get():
var result = hashTable.get(key, keyOffset, value, valueOffset);
if (result === 0) console.log('get(): element does not exist, nothing copied');
if (result === 1) console.log('get(): element exists, copied value to buffer');
// exist():
var result = hashTable.exist(key, keyOffset);
if (result === 0) console.log('exist(): element does not exist');
if (result === 1) console.log('exist(): element exists');
// unset():
var result = hashTable.unset(key, keyOffset);
if (result === 0) console.log('unset(): element does not exist, not removed');
if (result === 1) console.log('unset(): element was removed');
// cache():
// cache() cannot be used on the same instance as set(), reinstantiate:
var hashTable = new HashTable(keySize, valueSize, elementsMin, elementsMax);
var result = hashTable.cache(key, keyOffset, value, valueOffset);
if (result === 0) console.log('cache(): element was inserted');
if (result === 1) console.log('cache(): element was updated');
if (result === 2) console.log('cache(): element evicted another element');
Apart from validation exceptions thrown for programming errors, the following exceptions may be thrown for operating errors:
HashTable.ERROR_MAXIMUM_CAPACITY_EXCEEDED
A hash table buffer could not be further resized due to reaching
HashTable.BUFFER_MAX
or HashTable.BUCKETS_MAX
. Increase elementsMax
when
instantiating the hash table to ensure sufficient capacity.
HashTable.ERROR_SET
An insert failed despite several resize attempts. This should never happen and may indicate weak system entropy.
CPU=Intel(R) Xeon(R) CPU E3-1230 V2 @ 3.30GHz
===============================================================================
KEY=8 VALUE=0 | KEY=8 VALUE=4
---------------------------------------|---------------------------------------
set() Insert 228ns | set() Insert 269ns
set() Reserve 134ns | set() Reserve 139ns
set() Update 149ns | set() Update 164ns
get() Miss 99ns | get() Miss 100ns
get() Hit 147ns | get() Hit 164ns
exist() Miss 98ns | exist() Miss 99ns
exist() Hit 143ns | exist() Hit 148ns
unset() Miss 98ns | unset() Miss 98ns
unset() Hit 196ns | unset() Hit 200ns
cache() Insert 122ns | cache() Insert 139ns
cache() Evict 153ns | cache() Evict 174ns
cache() Miss 120ns | cache() Miss 133ns
cache() Hit 133ns | cache() Hit 136ns
===============================================================================
KEY=8 VALUE=8 | KEY=8 VALUE=16
---------------------------------------|---------------------------------------
set() Insert 299ns | set() Insert 346ns
set() Reserve 158ns | set() Reserve 172ns
set() Update 175ns | set() Update 195ns
get() Miss 96ns | get() Miss 103ns
get() Hit 174ns | get() Hit 191ns
exist() Miss 94ns | exist() Miss 102ns
exist() Hit 148ns | exist() Hit 160ns
unset() Miss 93ns | unset() Miss 101ns
unset() Hit 204ns | unset() Hit 224ns
cache() Insert 151ns | cache() Insert 165ns
cache() Evict 189ns | cache() Evict 207ns
cache() Miss 150ns | cache() Miss 158ns
cache() Hit 146ns | cache() Hit 166ns
===============================================================================
KEY=8 VALUE=32 | KEY=8 VALUE=64
---------------------------------------|---------------------------------------
set() Insert 418ns | set() Insert 631ns
set() Reserve 190ns | set() Reserve 275ns
set() Update 225ns | set() Update 280ns
get() Miss 104ns | get() Miss 111ns
get() Hit 223ns | get() Hit 277ns
exist() Miss 103ns | exist() Miss 109ns
exist() Hit 172ns | exist() Hit 183ns
unset() Miss 103ns | unset() Miss 110ns
unset() Hit 251ns | unset() Hit 295ns
cache() Insert 192ns | cache() Insert 244ns
cache() Evict 229ns | cache() Evict 286ns
cache() Miss 167ns | cache() Miss 179ns
cache() Hit 181ns | cache() Hit 191ns
===============================================================================
KEY=8 VALUE=4096 | KEY=8 VALUE=65536
---------------------------------------|---------------------------------------
set() Insert 6436ns | set() Insert 79601ns
set() Reserve 2178ns | set() Reserve 24260ns
set() Update 1518ns | set() Update 20550ns
get() Miss 135ns | get() Miss 181ns
get() Hit 828ns | get() Hit 7904ns
exist() Miss 127ns | exist() Miss 171ns
exist() Hit 232ns | exist() Hit 269ns
unset() Miss 104ns | unset() Miss 63ns
unset() Hit 1088ns | unset() Hit 13284ns
cache() Insert 1746ns | cache() Insert 20381ns
cache() Evict 1471ns | cache() Evict 20526ns
cache() Miss 180ns | cache() Miss 224ns
cache() Hit 231ns | cache() Hit 283ns
===============================================================================
KEY=16 VALUE=0 | KEY=16 VALUE=4
---------------------------------------|---------------------------------------
set() Insert 339ns | set() Insert 389ns
set() Reserve 161ns | set() Reserve 182ns
set() Update 197ns | set() Update 211ns
get() Miss 114ns | get() Miss 115ns
get() Hit 194ns | get() Hit 208ns
exist() Miss 113ns | exist() Miss 112ns
exist() Hit 197ns | exist() Hit 189ns
unset() Miss 112ns | unset() Miss 111ns
unset() Hit 250ns | unset() Hit 423ns
cache() Insert 164ns | cache() Insert 184ns
cache() Evict 206ns | cache() Evict 225ns
cache() Miss 163ns | cache() Miss 166ns
cache() Hit 183ns | cache() Hit 189ns
===============================================================================
KEY=16 VALUE=8 | KEY=16 VALUE=16
---------------------------------------|---------------------------------------
set() Insert 416ns | set() Insert 444ns
set() Reserve 189ns | set() Reserve 192ns
set() Update 225ns | set() Update 240ns
get() Miss 124ns | get() Miss 120ns
get() Hit 221ns | get() Hit 238ns
exist() Miss 122ns | exist() Miss 119ns
exist() Hit 199ns | exist() Hit 205ns
unset() Miss 122ns | unset() Miss 119ns
unset() Hit 458ns | unset() Hit 509ns
cache() Insert 185ns | cache() Insert 197ns
cache() Evict 232ns | cache() Evict 243ns
cache() Miss 176ns | cache() Miss 179ns
cache() Hit 195ns | cache() Hit 202ns
===============================================================================
KEY=16 VALUE=32 | KEY=16 VALUE=64
---------------------------------------|---------------------------------------
set() Insert 527ns | set() Insert 521ns
set() Reserve 242ns | set() Reserve 324ns
set() Update 268ns | set() Update 331ns
get() Miss 125ns | get() Miss 122ns
get() Hit 265ns | get() Hit 328ns
exist() Miss 125ns | exist() Miss 120ns
exist() Hit 217ns | exist() Hit 234ns
unset() Miss 128ns | unset() Miss 121ns
unset() Hit 619ns | unset() Hit 484ns
cache() Insert 226ns | cache() Insert 279ns
cache() Evict 263ns | cache() Evict 316ns
cache() Miss 185ns | cache() Miss 206ns
cache() Hit 212ns | cache() Hit 224ns
===============================================================================
KEY=16 VALUE=4096 | KEY=16 VALUE=65536
---------------------------------------|---------------------------------------
set() Insert 6264ns | set() Insert 80181ns
set() Reserve 2172ns | set() Reserve 23874ns
set() Update 1535ns | set() Update 20602ns
get() Miss 155ns | get() Miss 204ns
get() Hit 863ns | get() Hit 7758ns
exist() Miss 148ns | exist() Miss 186ns
exist() Hit 272ns | exist() Hit 343ns
unset() Miss 130ns | unset() Miss 150ns
unset() Hit 1228ns | unset() Hit 13332ns
cache() Insert 1767ns | cache() Insert 20791ns
cache() Evict 1486ns | cache() Evict 20552ns
cache() Miss 201ns | cache() Miss 243ns
cache() Hit 266ns | cache() Hit 318ns
===============================================================================
KEY=32 VALUE=0 | KEY=32 VALUE=4
---------------------------------------|---------------------------------------
set() Insert 526ns | set() Insert 549ns
set() Reserve 239ns | set() Reserve 251ns
set() Update 295ns | set() Update 302ns
get() Miss 160ns | get() Miss 161ns
get() Hit 293ns | get() Hit 302ns
exist() Miss 158ns | exist() Miss 158ns
exist() Hit 281ns | exist() Hit 282ns
unset() Miss 159ns | unset() Miss 158ns
unset() Hit 590ns | unset() Hit 616ns
cache() Insert 239ns | cache() Insert 249ns
cache() Evict 272ns | cache() Evict 282ns
cache() Miss 217ns | cache() Miss 224ns
cache() Hit 271ns | cache() Hit 277ns
===============================================================================
KEY=32 VALUE=8 | KEY=32 VALUE=16
---------------------------------------|---------------------------------------
set() Insert 562ns | set() Insert 625ns
set() Reserve 244ns | set() Reserve 277ns
set() Update 316ns | set() Update 325ns
get() Miss 164ns | get() Miss 162ns
get() Hit 314ns | get() Hit 325ns
exist() Miss 161ns | exist() Miss 159ns
exist() Hit 290ns | exist() Hit 291ns
unset() Miss 162ns | unset() Miss 159ns
unset() Hit 646ns | unset() Hit 693ns
cache() Insert 243ns | cache() Insert 261ns
cache() Evict 290ns | cache() Evict 301ns
cache() Miss 227ns | cache() Miss 226ns
cache() Hit 277ns | cache() Hit 283ns
===============================================================================
KEY=32 VALUE=32 | KEY=32 VALUE=64
---------------------------------------|---------------------------------------
set() Insert 685ns | set() Insert 739ns
set() Reserve 308ns | set() Reserve 356ns
set() Update 348ns | set() Update 399ns
get() Miss 161ns | get() Miss 154ns
get() Hit 347ns | get() Hit 398ns
exist() Miss 163ns | exist() Miss 154ns
exist() Hit 296ns | exist() Hit 304ns
unset() Miss 162ns | unset() Miss 155ns
unset() Hit 799ns | unset() Hit 662ns
cache() Insert 276ns | cache() Insert 360ns
cache() Evict 322ns | cache() Evict 376ns
cache() Miss 231ns | cache() Miss 272ns
cache() Hit 289ns | cache() Hit 299ns
===============================================================================
KEY=32 VALUE=4096 | KEY=32 VALUE=65536
---------------------------------------|---------------------------------------
set() Insert 6761ns | set() Insert 78095ns
set() Reserve 2309ns | set() Reserve 23743ns
set() Update 1611ns | set() Update 20693ns
get() Miss 202ns | get() Miss 250ns
get() Hit 952ns | get() Hit 7802ns
exist() Miss 190ns | exist() Miss 227ns
exist() Hit 354ns | exist() Hit 444ns
unset() Miss 174ns | unset() Miss 199ns
unset() Hit 1383ns | unset() Hit 13594ns
cache() Insert 1868ns | cache() Insert 20883ns
cache() Evict 1530ns | cache() Evict 20565ns
cache() Miss 246ns | cache() Miss 295ns
cache() Hit 339ns | cache() Hit 401ns
===============================================================================
KEY=64 VALUE=0 | KEY=64 VALUE=4
---------------------------------------|---------------------------------------
set() Insert 947ns | set() Insert 961ns
set() Reserve 378ns | set() Reserve 370ns
set() Update 463ns | set() Update 471ns
get() Miss 240ns | get() Miss 236ns
get() Hit 465ns | get() Hit 471ns
exist() Miss 239ns | exist() Miss 236ns
exist() Hit 452ns | exist() Hit 452ns
unset() Miss 240ns | unset() Miss 237ns
unset() Hit 628ns | unset() Hit 650ns
cache() Insert 386ns | cache() Insert 383ns
cache() Evict 407ns | cache() Evict 412ns
cache() Miss 315ns | cache() Miss 323ns
cache() Hit 432ns | cache() Hit 437ns
===============================================================================
KEY=64 VALUE=8 | KEY=64 VALUE=16
---------------------------------------|---------------------------------------
set() Insert 1008ns | set() Insert 837ns
set() Reserve 378ns | set() Reserve 439ns
set() Update 478ns | set() Update 501ns
get() Miss 235ns | get() Miss 231ns
get() Hit 475ns | get() Hit 498ns
exist() Miss 235ns | exist() Miss 230ns
exist() Hit 451ns | exist() Hit 466ns
unset() Miss 236ns | unset() Miss 230ns
unset() Hit 674ns | unset() Hit 720ns
cache() Insert 376ns | cache() Insert 390ns
cache() Evict 421ns | cache() Evict 434ns
cache() Miss 338ns | cache() Miss 353ns
cache() Hit 444ns | cache() Hit 448ns
===============================================================================
KEY=64 VALUE=32 | KEY=64 VALUE=64
---------------------------------------|---------------------------------------
set() Insert 929ns | set() Insert 1293ns
set() Reserve 438ns | set() Reserve 516ns
set() Update 511ns | set() Update 555ns
get() Miss 227ns | get() Miss 231ns
get() Hit 507ns | get() Hit 553ns
exist() Miss 227ns | exist() Miss 227ns
exist() Hit 459ns | exist() Hit 457ns
unset() Miss 227ns | unset() Miss 229ns
unset() Hit 821ns | unset() Hit 688ns
cache() Insert 440ns | cache() Insert 479ns
cache() Evict 460ns | cache() Evict 485ns
cache() Miss 386ns | cache() Miss 302ns
cache() Hit 454ns | cache() Hit 435ns
===============================================================================
KEY=64 VALUE=4096 | KEY=64 VALUE=65536
---------------------------------------|---------------------------------------
set() Insert 7004ns | set() Insert 81742ns
set() Reserve 2502ns | set() Reserve 24197ns
set() Update 1776ns | set() Update 20955ns
get() Miss 268ns | get() Miss 326ns
get() Hit 1166ns | get() Hit 8035ns
exist() Miss 259ns | exist() Miss 297ns
exist() Hit 515ns | exist() Hit 592ns
unset() Miss 249ns | unset() Miss 266ns
unset() Hit 1490ns | unset() Hit 13617ns
cache() Insert 2004ns | cache() Insert 21043ns
cache() Evict 1671ns | cache() Evict 20711ns
cache() Miss 336ns | cache() Miss 383ns
cache() Hit 492ns | cache() Hit 551ns
@ronomon/hash-table
ships with extensive tests, including a fuzz test:
node test.js
node benchmark.js
FAQs
Fast, reliable cuckoo hash table for Node.js
We found that @ronomon/hash-table demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
Security News
A malicious npm package targets Solana developers, rerouting funds in 2% of transactions to a hardcoded address.
Security News
Research
Socket researchers have discovered malicious npm packages targeting crypto developers, stealing credentials and wallet data using spyware delivered through typosquats of popular cryptographic libraries.
Security News
Socket's package search now displays weekly downloads for npm packages, helping developers quickly assess popularity and make more informed decisions.