Additionally, we create a `secret_name` for the hero, but so far, we are returning it everywhere, that's not very **secret**... 😅

We'll fix these things by adding a few **extra models**. Here's where SQLModel will shine. ✨

### Create Multiple Models { #create-multiple-models }

다음과 같은 사용자 인터페이스를 볼 수 있습니다:

<img src="/img/tutorial/security/image07.png">

이전과 같은 방법으로 애플리케이션에 인증하십시오.

다음 인증 정보를 사용하십시오:

Username: `johndoe`
Password: `secret`

/// check

코드 어디에도 평문 패스워드 "`secret`" 이 없다는 점에 유의하십시오. 해시된 버전만 있습니다.

///

<img src="/img/tutorial/security/image08.png">

`/users/me/` 를 호출하면 다음과 같은 응답을 얻을 수 있습니다:

```JSON
{
  "username": "johndoe",

	exit_1
fi

./mc admin user svcacct add minio2 foobar --access-key testsvc --secret-key testsvc123
if [ $? -ne 0 ]; then
	echo "adding svc account failed, exiting.."
	exit_1
fi

./mc admin user svcacct add minio2 minio --access-key testsvc2 --secret-key testsvc123
if [ $? -ne 0 ]; then
	echo "adding root svc account testsvc2 failed, exiting.."
	exit_1
fi

sleep 10

```
cat ${HADOOP_CONF_DIR}/core-site.xml | kv-pairify | grep "s3a"

fs.s3a.access.key=minio
fs.s3a.secret.key=minio123
fs.s3a.path.style.access=true
fs.s3a.block.size=512M
fs.s3a.buffer.dir=${hadoop.tmp.dir}/s3a
fs.s3a.committer.magic.enabled=false
fs.s3a.committer.name=directory

 *
 * <p>This client requires the following initialization parameters:
 * <ul>
 *   <li>endpoint - The URL of the MinIO server</li>
 *   <li>accessKey - The access key for authentication</li>
 *   <li>secretKey - The secret key for authentication</li>
 *   <li>connectTimeout - Connection timeout in milliseconds (default: 10000)</li>
 *   <li>writeTimeout - Write timeout in milliseconds (default: 10000)</li>

### Authentifizieren { #authenticate }

Klicken Sie auf den Button „Authorize“.

Verwenden Sie die Anmeldedaten:

Benutzer: `johndoe`

Passwort: `secret`.

<img src="/img/tutorial/security/image04.png">

Nach der Authentifizierung im System sehen Sie Folgendes:

<img src="/img/tutorial/security/image05.png">

# Using TensorFlow Securely

This document discusses the TensorFlow security model. It describes the security
risks to consider when using models, checkpoints or input data for training or
serving. We also provide guidelines on what constitutes a vulnerability in
TensorFlow and how to report them.

This document applies to other repositories in the TensorFlow organization,
covering security practices for the entirety of the TensorFlow ecosystem.

func (r *Config) PopulatePublicKey(arn arn.ARN) error {
	pCfg := r.arnProviderCfgsMap[arn]
	if pCfg.JWKS.URL == nil || pCfg.JWKS.URL.String() == "" {
		return nil
	}

	// Add client secret for the client ID for HMAC based signature.
	r.pubKeys.add(pCfg.ClientID, []byte(pCfg.ClientSecret))

	client := &http.Client{
		Transport: r.transport,
	}

	resp, err := client.Get(pCfg.JWKS.URL.String())

        UniAddress dc;
        String msg;
        NtlmPasswordAuthentication ntlm = null;
        msg = req.getHeader("Authorization");
        final boolean offerBasic = enableBasic && (insecureBasic || req.isSecure());

        if (msg != null && (msg.startsWith("NTLM ") || offerBasic && msg.startsWith("Basic "))) {
            if (msg.startsWith("NTLM ")) {
                final HttpSession ssn = req.getSession();

            }
        } finally {
            correctAuth.close();
            wrongAuth.close();
        }
    }

    /**
     * Test that null and empty password comparisons are handled securely.
     */
    @Test
    public void testNullAndEmptyPasswordSecurity() {
        NtlmPasswordAuthenticator auth1 = new NtlmPasswordAuthenticator("domain", "user", (String) null);