Send raw response bodies to the waf

[estringana]

Description

AppSec: Raw HTTP response body WAF inspection

Implements support for the server.response.body.raw WAF address, allowing the WAF to inspect the raw (unparsed) HTTP response body for attack patterns.

APPSEC-69453

Reviewer checklist

• Test coverage seems ok.
• Appropriate labels assigned.

[datadog-official]

 

⚠️ Warnings

🚦 5 Pipeline jobs failed

DataDog/apm-reliability/dd-trace-php | test_extension_ci: [8.0]     

DataDog/apm-reliability/dd-trace-php | test_web_custom: [8.3, cgi-fcgi]     

DataDog/apm-reliability/dd-trace-php | ASAN test_c: [8.0, arm64]     

View all 5 failed jobs.

❄️ 1 New flaky test detected

WAF matches against raw JSON response body() from com.datadog.appsec.php.integration.RawResponseBodyTests  

java.lang.AssertionError: Expected WAF to fire on server.response.body.raw. Expression: (appsecJson != null). Values: appsecJson = null

java.lang.AssertionError: Expected WAF to fire on server.response.body.raw. Expression: (appsecJson != null). Values: appsecJson = null
	at org.codehaus.groovy.runtime.InvokerHelper.createAssertError(InvokerHelper.java:416)
	at com.datadog.appsec.php.integration.RawResponseBodyTests.WAF matches against raw JSON response body(RawResponseBodyTests.groovy:52)
	at java.base/java.lang.reflect.Method.invoke(Method.java:569)
	at java.base/java.util.ArrayList.forEach(ArrayList.java:1511)
	at java.base/java.util.ArrayList.forEach(ArrayList.java:1511)

New test introduced in this PR is flaky.

View in Flaky Test Management

ℹ️ Info

No other issues found (see more)

🧪 All tests passed

🎯 Code Coverage (details)
• Patch Coverage: 82.76%
• Overall Coverage: 60.63% (-0.07%)

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[pr-commenter]

Benchmarks [ appsec ]

Benchmark execution time: 2026-08-03 11:07:05

Comparing candidate commit 1dcb1c6 in PR branch estringana/send-raw-response-bodies with baseline commit e3b075e in branch master.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 12 metrics, 0 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

• 🟩 = significantly better candidate vs. baseline
• 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

[pr-commenter]

Benchmarks [ tracer ]

Benchmark execution time: 2026-08-03 11:41:32

Comparing candidate commit 1dcb1c6 in PR branch estringana/send-raw-response-bodies with baseline commit e3b075e in branch master.

Found 2 performance improvements and 2 performance regressions! Performance is the same for 189 metrics, 1 unstable metrics.

Explanation

This is an A/B test comparing a candidate commit's performance against that of a baseline commit. Performance changes are noted in the tables below as:

• 🟩 = significantly better candidate vs. baseline
• 🟥 = significantly worse candidate vs. baseline

We compute a confidence interval (CI) over the relative difference of means between metrics from the candidate and baseline commits, considering the baseline as the reference.

If the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD), the change is considered significant.

Feel free to reach out to #apm-benchmarking-platform on Slack if you have any questions.

More details about the CI and significant changes

You can imagine this CI as a range of values that is likely to contain the true difference of means between the candidate and baseline commits.

CIs of the difference of means are often centered around 0%, because often changes are not that big:

---------------------------------(------|---^--------)-------------------------------->
                              -0.6%    0%  0.3%     +1.2%
                                 |          |        |
         lower bound of the CI --'          |        |
sample mean (center of the CI) -------------'        |
         upper bound of the CI ----------------------'

As described above, a change is considered significant if the CI is entirely outside the configured SIGNIFICANT_IMPACT_THRESHOLD (or the deprecated UNCONFIDENCE_THRESHOLD).

For instance, for an execution time metric, this confidence interval indicates a significantly worse performance:

----------------------------------------|---------|---(---------^---------)---------->
                                       0%        1%  1.3%      2.2%      3.1%
                                                  |   |         |         |
       significant impact threshold --------------'   |         |         |
                      lower bound of CI --------------'         |         |
       sample mean (center of the CI) --------------------------'         |
                      upper bound of CI ----------------------------------'

scenario:HookBench/benchHookOverheadTraceFunction

• 🟥 execution_time [+5.343µs; +8.735µs] or [+2.640%; +4.316%]

scenario:MessagePackSerializationBench/benchMessagePackSerialization

• 🟩 execution_time [-11.097µs; -8.023µs] or [-9.869%; -7.136%]

scenario:MessagePackSerializationBench/benchMessagePackSerialization-opcache

• 🟩 execution_time [-8.259µs; -6.281µs] or [-7.250%; -5.514%]

scenario:PHPRedisBench/benchRedisOverhead

• 🟥 execution_time [+41.807µs; +58.597µs] or [+4.121%; +5.776%]

[chatgpt-codex-connector]

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