rollout: persist turn permission profiles (#18281)

## Why

Resume and reconstruction need to preserve the permissions that were
active for each user turn. If rollouts only keep legacy sandbox fields,
replay cannot faithfully represent profile-shaped overrides introduced
earlier in the stack.

## What changed

This records `permission_profile` on user-turn rollout events,
reconstructs it through history/state extraction, and updates rollout
reconstruction and related fixtures to keep the field explicit.

## Verification

- `cargo test -p codex-core --test all permissions_messages --
--nocapture`
- `cargo test -p codex-core --test all request_permissions --
--nocapture`











































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[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/18281).
* #18288
* #18287
* #18286
* #18285
* #18284
* #18283
* #18282
* __->__ #18281

codex-rs/state/src/extract.rs

@@ -301,6 +301,7 @@ mod tests {
                 timezone: None,
                 approval_policy: AskForApproval::Never,
                 sandbox_policy: SandboxPolicy::DangerFullAccess,
+                permission_profile: None,
                 network: None,
                 file_system_sandbox_policy: None,
                 model: "gpt-5".to_string(),
@@ -340,6 +341,7 @@ mod tests {
                 timezone: None,
                 approval_policy: AskForApproval::OnRequest,
                 sandbox_policy: SandboxPolicy::new_read_only_policy(),
+                permission_profile: None,
                 network: None,
                 file_system_sandbox_policy: None,
                 model: "gpt-5".to_string(),
@@ -373,6 +375,7 @@ mod tests {
                 timezone: None,
                 approval_policy: AskForApproval::OnRequest,
                 sandbox_policy: SandboxPolicy::new_read_only_policy(),
+                permission_profile: None,
                 network: None,
                 file_system_sandbox_policy: None,
                 model: "gpt-5".to_string(),