excess := len(hash)*8 - orderBits
	if excess > 0 {
		ret.Rsh(ret, uint(excess))
	}
	return ret
}

var errZeroParam = errors.New("zero parameter")

// Sign signs a hash (which should be the result of hashing a larger message)
// using the private key, priv. If the hash is longer than the bit-length of the
// private key's curve order, the hash will be truncated to that length. It

// license that can be found in the LICENSE file.

package sha3

// This file defines the ShakeHash interface, and provides
// functions for creating SHAKE and cSHAKE instances, as well as utility
// functions for hashing bytes to arbitrary-length output.
//
//
// SHAKE implementation is based on FIPS PUB 202 [1]
// cSHAKE implementations is based on NIST SP 800-185 [2]
//
// [1] https://nvlpubs.nist.gov/nistpubs/FIPS/NIST.FIPS.202.pdf

  // TODO(b/158709815): Add support for batches with padded NMS.
  auto boxes_type =
      mlir::dyn_cast<RankedTensorType>(func_.getFunctionType().getInput(0));
  if (boxes_type == nullptr || !boxes_type.hasRank() ||
      boxes_type.getRank() != 2) {
    return func_.emitWarning() << "TFLite does not support batched input for "
                                  "non_max_suppression_padded";
  }
  return success();
}

* **Sicheres Passwort**-Hashing standardmäßig.
* **JWT-Token**-Authentifizierung.
* **SQLAlchemy**-Modelle (unabhängig von Flask-Erweiterungen, sodass sie direkt mit Celery-Workern verwendet werden können).

		return nil, nil, err
	}
	return c, kyberSharedSecret(ss, c), nil
}

func kyberSharedSecret(K, c []byte) []byte {
	// Package mlkem768 implements ML-KEM, which compared to Kyber removed a
	// final hashing step. Compute SHAKE-256(K || SHA3-256(c), 32) to match Kyber.
	// See https://words.filippo.io/mlkem768/#bonus-track-using-a-ml-kem-implementation-as-kyber-v3.
	h := sha3.NewShake256()
	h.Write(K)
	ch := sha3.Sum256(c)

Guava is a set of core Java libraries from Google that includes new collection
types (such as multimap and multiset), immutable collections, a graph library,
and utilities for concurrency, I/O, hashing, primitives, strings, and more! It
is widely used on most Java projects within Google, and widely used by many
other companies as well.



Guava comes in two flavors:

    Se não souber, você aprenderá o que é uma "senha hash" nos [capítulos de segurança](security/simple-oauth2.md#password-hashing){.internal-link target=_blank}.

## Múltiplos modelos

Aqui está uma ideia geral de como os modelos poderiam parecer com seus campos de senha e os lugares onde são usados:

=== "Python 3.8 and above"

    Speichern Sie niemals das Klartext-Passwort eines Benutzers. Speichern Sie immer den „sicheren Hash“, den Sie verifizieren können.

    Falls Ihnen das nichts sagt, in den [Sicherheits-Kapiteln](security/simple-oauth2.md#passwort-hashing){.internal-link target=_blank} werden Sie lernen, was ein „Passwort-Hash“ ist.

## Mehrere Modelle

!!! danger
    Never store user's plaintext passwords. Always store a "secure hash" that you can then verify.

    If you don't know, you will learn what a "password hash" is in the [security chapters](security/simple-oauth2.md#password-hashing){.internal-link target=_blank}.

## Multiple models

Here's a general idea of how the models could look like with their password fields and the places where they are used:

=== "Python 3.10+"

书接上文，多个关联模型这种情况很常见。

特别是用户模型，因为：

* **输入模型**应该含密码
* **输出模型**不应含密码
* **数据库模型**需要加密的密码

!!! danger "危险"

    千万不要存储用户的明文密码。始终存储可以进行验证的**安全哈希值**。

    如果不了解这方面的知识，请参阅[安全性中的章节](security/simple-oauth2.md#password-hashing){.internal-link target=_blank}，了解什么是**密码哈希**。

## 多个模型

下面的代码展示了不同模型处理密码字段的方式，及使用位置的大致思路：

=== "Python 3.10+"

    ```Python hl_lines="7  9  14  20  22  27-28  31-33  38-39"