}
	if err := r.Encryption.Validate(); err != nil {
		return err
	}

	for _, tag := range r.Flags.Filter.Tags {
		if err := tag.Validate(); err != nil {
			return err
		}
	}

	for _, meta := range r.Flags.Filter.Metadata {
		if err := meta.Validate(); err != nil {
			return err
		}
	}

	return r.Flags.Retry.Validate()

                .replace(CACHE_AND_SESSION_INVALIDATE_STATEMENT, "<% }catch(Exception e){session.invalidate();} %>");
    }

    public static String encodeJsp(final String value) {
        return value.replace("<% try{ %>", TRY_STATEMENT).replace("<% }catch(Exception e){session.invalidate();} %>",
                CACHE_AND_SESSION_INVALIDATE_STATEMENT);
    }

	}
	return madmin.BatchJobType("unknown")
}

// Validate validates the current job, used by 'save()' before
// persisting the job request
func (j BatchJobRequest) Validate(ctx context.Context, o ObjectLayer) error {
	switch {
	case j.Replicate != nil:
		return j.Replicate.Validate(ctx, j, o)
	case j.KeyRotate != nil:
		return j.KeyRotate.Validate(ctx, j, o)
	case j.Expire != nil:

			jwtgo.ValidationErrorClaimsInvalid)
	}

	// Signature is valid, lets validate the claims for
	// other fields such as expiry etc.
	return claims.Valid()
}

// ParseUnverifiedStandardClaims - WARNING: Don't use this method unless you know what you're doing
//
// This method parses the token but doesn't validate the signature. It's only
// ever useful in cases where you know the signature is valid (because it has

			}
		}
	}
	return nil
}

// IsEmpty returns true if Filter is not specified in the XML
func (f Filter) IsEmpty() bool {
	return !f.set
}

// Validate - validates the filter element
func (f Filter) Validate() error {
	if f.IsEmpty() {
		return errXMLNotWellFormed
	}
	// A Filter must have exactly one of Prefix, Tag,
	// ObjectSize{LessThan,GreaterThan} or And specified.

```

////

/// info

In Pydantic version 1 the method to parse and validate an object was `Item.parse_obj()`, in Pydantic version 2, the method is called `Item.model_validate()`.

///

/// tip

Here we reuse the same Pydantic model.

But the same way, we could have validated it in some other way.

	claims := xjwt.NewMapClaims()
	return claims.Map(), ErrNone
}

// Check request auth type verifies the incoming http request
//   - validates the request signature
//   - validates the policy action if anonymous tests bucket policies if any,
//     for authenticated requests validates IAM policies.
//
// returns APIErrorCode if any to be replied to the client.

							reqType, bucketName, test.objectName, err)
					}
					// Validate whether the error has occurred for the expected reason.
					if want.Code != errXML.Code {
						t.Errorf("%s, Expected to fail with error \"%s\", but received \"%s\": %q.",
							reqType, want.Code, errXML.Code, errXML.Message)
					}
					// Validate the HTTP response status code  with the expected one.
					if want.HTTPStatusCode != rec.Code {

	claims["exp"] = time.Now().UTC().Add(defaultExpiryDuration).Unix() // update with new expiry.
	return nil
}

const (
	audClaim = "aud"
	azpClaim = "azp"
)

// Validate - validates the id_token.
func (r *Config) Validate(ctx context.Context, arn arn.ARN, token, accessToken, dsecs string, claims map[string]interface{}) error {
	jp := new(jwtgo.Parser)
	jp.ValidMethods = []string{
		"RS256", "RS384", "RS512",

		entityKeysInStorage.Add(k)
		return true
	})

	return entityKeysInStorage
}

// NormalizeLDAPMappingImport - validates the LDAP policy mappings. Keys in the
// given map may not correspond to LDAP DNs - these keys are ignored.
//
// For validated mappings, it updates the key in the given map to be in
// normalized form.
func (sys *IAMSys) NormalizeLDAPMappingImport(ctx context.Context, isGroup bool,