"InjectOnConstructorOfAbstractClass", // We use abstract injection as a pattern
        "InlineMeSuggester", // Only suppression seems to actually "fix" this, so make it global
        "JavaUtilDate", // We are fine with using Date
        "JavaxInjectOnAbstractMethod", // We use abstract injection as a pattern

물론 공격자들은 이런 작업을 손으로 하지 않습니다. 보통 초당 수천~수백만 번 테스트할 수 있는 프로그램을 작성할 것이고, 한 번에 정답 글자 하나씩 추가로 얻어낼 수 있습니다.

그렇게 하면 몇 분 또는 몇 시간 만에, 응답에 걸린 시간만을 이용해(우리 애플리케이션의 “도움”을 받아) 올바른 사용자명과 비밀번호를 추측할 수 있게 됩니다.

#### `secrets.compare_digest()`로 해결하기 { #fix-it-with-secrets-compare-digest }

하지만 우리 코드는 실제로 `secrets.compare_digest()`를 사용하고 있습니다.

요약하면, `stanleyjobsox`와 `stanleyjobson`을 비교하는 데 걸리는 시간은 `johndoe`와 `stanleyjobson`을 비교하는 데 걸리는 시간과 같아집니다. 비밀번호도 마찬가지입니다.

    }

    /**
     * Tricky case: flat directory structure, but child directory != artifactId.
     * Model interpolation does not give same result when calculated from build or from repo...
     * This is why MNG-5000 fix in code is marked as bad practice (uses file names)
     * @throws IOException Model read problem
     */
    @Test
    void testFlatTrickyUrls() throws IOException {

bazel_dep(name = "pybind11_bazel", version = "2.13.6")
bazel_dep(name = "pybind11_protobuf", version = "0.0.0-20250210-f02a2b7")

# NOTE: This is a newer version compared to what was used in WORKSPACE
# and it breaks wheel tests.
# TODO: Fix the incompatibility with wheel tests.
bazel_dep(name = "pybind11_abseil", version = "202402.0")
bazel_dep(name = "or-tools", version = "9.12", repo_name = "com_google_ortools")

  int nonAlphaRatio; // one non-alpha char per this many chars

  @Param boolean noWorkToDo;

  Random random;
  String testString;

  @BeforeExperiment
  void setUp() {
    random = new Random(0xdeadbeef); // fix the seed so results are comparable across runs

    int nonAlpha = size / nonAlphaRatio;
    int alpha = size - nonAlpha;

    List<Character> chars = Lists.newArrayListWithCapacity(size);

		// ensure it's UTF8 encoded.
		value = string(val)
	case [12]byte:
		// TODO: This is returned for the parquet INT96 type. We just
		// treat it same as []byte (but AWS S3 treats it as a large int)
		// - fix this later.
		value = string(val[:])
	case int32:
		value = int64(val)
		if logicalType := se.GetLogicalType(); logicalType != nil {
			if logicalType.IsSetDATE() {

    }

    @Override
    public String toString() {
        final StringBuilder sb = new StringBuilder();
        String n = this.name;

        // fix MSBROWSE name
        if (n == null) {
            n = "null";
        } else if (n.charAt(0) == 0x01) {
            final char c[] = n.toCharArray();
            c[0] = '.';
            c[1] = '.';

#### **专业**攻击 { #a-professional-attack }

当然，攻击者不用手动操作，而是编写每秒能执行成千上万次测试的攻击程序，每次都会找到更多正确字符。

但是，在您的应用的**帮助**下，攻击者利用时间差，就能在几分钟或几小时内，以这种方式猜出正确的用户名和密码。

#### 使用 `secrets.compare_digest()` 修补 { #fix-it-with-secrets-compare-digest }

在此，代码中使用了 `secrets.compare_digest()`。

简单的说，它使用相同的时间对比 `stanleyjobsox` 和 `stanleyjobson`，还有 `johndoe` 和 `stanleyjobson`。对比密码时也一样。

在代码中使用 `secrets.compare_digest()` ，就可以安全地防御这整类安全攻击。

* Ensure to run enough warmup iterations to get the benchmark into a stable state. If you are unsure, don't change the defaults.
* Avoid CPU migrations by pinning your benchmarks to specific CPU cores. On Linux you can use `taskset`.
* Fix the CPU frequency to avoid Turbo Boost from kicking in and skewing your results. On Linux you can use `cpufreq-set` and the
  `performance` CPU governor.
* Vary the problem input size with `@Param`.

- Fix panic on kubectl api-resources ([#134833](https://github.com/kubernetes/kubernetes/pull/134833), [@rikatz](https://github.com/rikatz)) [SIG CLI]
- Fix setting distinctAttribute=nil when DRAConsumableCapacity is disabled ([#134962](https://github.com/kubernetes/kubernetes/pull/134962), [@sunya-ch](https://github.com/sunya-ch)) [SIG Node]