Fix protocol failures caused by empty appsec data

[cataphract]

Description

Error seen in the wild (telemetry).

Reviewer checklist

• Test coverage seems ok.
• Appropriate labels assigned.

[chatgpt-codex-connector]

Codex Review Summary

This comment shows the latest Codex review activity on this pull request.

Review	Status	Commit	Review trigger
📝 Code Review	✅ Completed 2026-09-18T12:50:25.476764Z	2842fc5	PR opened
🔒 Security Review	✅ Completed 2026-09-18T12:51:46.401907Z	2842fc5	PR opened

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[datadog-prod-us1-6]

 

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❌ Errors

Your PR has failed checks. Please review the issues below and take necessary action before merging.

🚦 21 Pipeline jobs failed

DataDog/apm-reliability/dd-trace-php | check libxml2 version — 🔧 Needs a code fix, caused by this PR

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DataDog/apm-reliability/dd-trace-php | test_extension_ci: [7.1, valgrind] — 🔧 Needs a code fix, caused by this PR

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DataDog/apm-reliability/dd-trace-php | Extension Tea Tests: [7.0, debug-zts] — 🔄 Retry may pass, looks flaky

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ℹ️ Info

No other issues found (see more)

🧪 All tests passed
❄️ No new flaky tests detected

🎯 Code Coverage (details)
• Patch Coverage: 100.00%
• Overall Coverage: 67.47% (-0.02%)

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[pr-commenter]

Benchmarks [ appsec ]

Benchmark execution time: 2026-09-18 13:18:15

Comparing candidate commit 2842fc5 in PR branch glopes/empty-data-appsec with baseline commit 8097433 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 ----------------------------------'