Fix: Minor logging uplift for debugging of prompt injection mitigation

[dorien-koelemeijer]

Summary

• Minor logging uplift to make sure we can validate that there is a fallback to pattern-based detection if prompt injection mitigation feature is enabled, but command injection isn't available/misconfigured.
• Datadog metrics uplift

Type of Change

• Feature
• Bug fix
• Refactor / Code quality
• Performance improvement
• Documentation
• Tests
• Security fix
• Build / Release
• Other (specify below)

AI Assistance

• This PR was created or reviewed with AI assistance

Testing

Local/manual testing.

[Copilot]

Pull request overview

This PR updates the prompt-injection scanning internals to surface (via logging) whether pattern-based scanning was used as a fallback when ML-based command injection detection isn’t available or fails.

Changes:

• Add a used_pattern_detection flag to DetailedScanResult to track when pattern-based scanning was used.
• Switch the tracing::info! field has_patterns to report the fallback-path usage rather than presence of pattern matches.
• Propagate used_pattern_detection through intermediate scan results used to build the final explanation/logging.

[Copilot]

Pull request overview

Copilot reviewed 3 out of 3 changed files in this pull request and generated 2 comments.

[Copilot]

scan_conversation always sets ml_confidence: Some(max_confidence) even if every classifier call failed (all scan_with_classifier results were None), which makes downstream logic treat this as a real ML signal (and currently reduces tool_confidence by 10% when the value is 0.0). Track whether any classification succeeded (e.g., fold an Option<f32> or keep a success flag) and return ml_confidence: None when there were no successful results.

[Copilot]

Using monotonic_counter.* = if enabled { 1 } else { 0 } is likely to produce confusing metrics (a counter with value 0 is typically a no-op and the name suggests a gauge); consider logging the booleans as normal fields (e.g. command_classifier_enabled = ...) and emitting a separate monotonic_counter metric with value 1 (or separate enabled/disabled counters) so disabled configurations are still observable.

Suggested change

	monotonic_counter.goose.security_command_classifier_enabled = if command_classifier_enabled { 1 } else { 0 },
	monotonic_counter.goose.security_prompt_classifier_enabled = if prompt_classifier_enabled { 1 } else { 0 },
	monotonic_counter.goose.security_classifier_configuration_logged = 1,
	security_command_classifier_enabled = command_classifier_enabled,
	security_prompt_classifier_enabled = prompt_classifier_enabled,