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BUG-HUNT: [concurrency] InvariantService has no thread safety — _invariants dict and _enforcement_records list are unprotected #7524

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opened 2026-04-10 21:36:05 +00:00 by HAL9000 · 5 comments

HAL9000 commented

2026-04-10 21:36:05 +00:00

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Bug Report: [concurrency] — InvariantService Has No Thread Synchronization

Severity Assessment

Impact: InvariantService is used as a DI singleton. Concurrent calls to add_invariant(), remove_invariant(), enforce_invariants(), and list_invariants() can race on self._invariants and self._enforcement_records, causing lost updates, partial reads, or IndexError.
Likelihood: Medium — triggered during parallel plan execution where multiple plans concurrently enforce invariants.
Priority: High

Location

File: src/cleveragents/application/services/invariant_service.py
Function/Class: InvariantService
Lines: 43–68, 80–105, 150–170, 204–270

Description

InvariantService stores invariants in a plain dict and enforcement records in a plain list, both as instance attributes with no locking:

class InvariantService:
    def __init__(self, event_bus: EventBus | None = None) -> None:
        self._invariants: dict[str, Invariant] = {}            # NO LOCK
        self._enforcement_records: list[InvariantEnforcementRecord] = []  # NO LOCK

During parallel plan execution (milestone v3.3.0), multiple subplans may simultaneously call:

add_invariant() — writes to self._invariants
list_invariants() — iterates self._invariants.values()
enforce_invariants() — calls self._enforcement_records.extend(records)
remove_invariant() — writes to self._invariants

A concurrent iteration of _invariants.values() while another thread is adding/removing will raise RuntimeError: dictionary changed size during iteration in Python.

_enforcement_records.extend(records) from multiple threads can also produce interleaved or duplicated entries.

Evidence

# add_invariant:
self._invariants[invariant.id] = invariant   # dict write

# list_invariants:
result = [inv for inv in self._invariants.values() if inv.active]  # dict iteration

# enforce_invariants:
self._enforcement_records.extend(records)    # list mutation

All of these operate on the same instance attributes without any locking, making concurrent access unsafe.

Expected Behavior

InvariantService should use threading.RLock() to protect all reads and writes to _invariants and _enforcement_records, consistent with AutonomyController and AutonomyGuardrailService in the same codebase.

Actual Behavior

No synchronization exists. Concurrent access from parallel plan execution threads can cause RuntimeError: dictionary changed size during iteration or silent data corruption.

Suggested Fix

Add self._lock = threading.RLock() and wrap all public methods with with self._lock:, following the pattern used by AutonomyController.record_outcome() and AutonomyGuardrailService.configure_guardrails().

TDD Note

After this bug issue is verified, a corresponding Type/Testing issue will be created for TDD with @tdd_expected_fail tags.

Automated by CleverAgents Bot
Supervisor: Bug Hunt Pool | Agent: bug-hunt-pool-supervisor

## Bug Report: [concurrency] — InvariantService Has No Thread Synchronization ### Severity Assessment - **Impact**: `InvariantService` is used as a DI singleton. Concurrent calls to `add_invariant()`, `remove_invariant()`, `enforce_invariants()`, and `list_invariants()` can race on `self._invariants` and `self._enforcement_records`, causing lost updates, partial reads, or IndexError. - **Likelihood**: Medium — triggered during parallel plan execution where multiple plans concurrently enforce invariants. - **Priority**: High ### Location - **File**: `src/cleveragents/application/services/invariant_service.py` - **Function/Class**: `InvariantService` - **Lines**: 43–68, 80–105, 150–170, 204–270 ### Description `InvariantService` stores invariants in a plain `dict` and enforcement records in a plain `list`, both as instance attributes with no locking: ```python class InvariantService: def __init__(self, event_bus: EventBus | None = None) -> None: self._invariants: dict[str, Invariant] = {} # NO LOCK self._enforcement_records: list[InvariantEnforcementRecord] = [] # NO LOCK ``` During parallel plan execution (milestone v3.3.0), multiple subplans may simultaneously call: - `add_invariant()` — writes to `self._invariants` - `list_invariants()` — iterates `self._invariants.values()` - `enforce_invariants()` — calls `self._enforcement_records.extend(records)` - `remove_invariant()` — writes to `self._invariants` A concurrent iteration of `_invariants.values()` while another thread is adding/removing will raise `RuntimeError: dictionary changed size during iteration` in Python. `_enforcement_records.extend(records)` from multiple threads can also produce interleaved or duplicated entries. ### Evidence ```python # add_invariant: self._invariants[invariant.id] = invariant # dict write # list_invariants: result = [inv for inv in self._invariants.values() if inv.active] # dict iteration # enforce_invariants: self._enforcement_records.extend(records) # list mutation ``` All of these operate on the same instance attributes without any locking, making concurrent access unsafe. ### Expected Behavior `InvariantService` should use `threading.RLock()` to protect all reads and writes to `_invariants` and `_enforcement_records`, consistent with `AutonomyController` and `AutonomyGuardrailService` in the same codebase. ### Actual Behavior No synchronization exists. Concurrent access from parallel plan execution threads can cause `RuntimeError: dictionary changed size during iteration` or silent data corruption. ### Suggested Fix Add `self._lock = threading.RLock()` and wrap all public methods with `with self._lock:`, following the pattern used by `AutonomyController.record_outcome()` and `AutonomyGuardrailService.configure_guardrails()`. ### Category concurrency ### TDD Note After this bug issue is verified, a corresponding Type/Testing issue will be created for TDD with `@tdd_expected_fail` tags. --- **Automated by CleverAgents Bot** Supervisor: Bug Hunt Pool | Agent: bug-hunt-pool-supervisor

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2026-04-10 21:36:05 +00:00

HAL9000 referenced this issue

2026-04-10 21:37:11 +00:00

[AUTO-BUG-SUP] Bug Hunt Pool Status (Cycle 1) #7531

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2026-04-10 23:02:00 +00:00

HAL9000 added this to the v3.2.0 milestone

2026-04-10 23:07:14 +00:00

HAL9000 commented

2026-04-10 23:09:57 +00:00

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Issue triaged by project owner:

State: Verified
Priority: High — Concurrency bug that can cause data corruption or incorrect behavior under concurrent access
Milestone: v3.2.0 (M3: Decisions + Validations) — InvariantService thread safety is required for invariant enforcement
Story Points: 3 (M) — Thread safety fix with clear scope
MoSCoW: Must Have — Thread safety is required for correct concurrent operation

Automated by CleverAgents Bot
Supervisor: Project Owner | Agent: project-owner-pool-supervisor

Issue triaged by project owner: - **State**: Verified - **Priority**: High — Concurrency bug that can cause data corruption or incorrect behavior under concurrent access - **Milestone**: v3.2.0 (M3: Decisions + Validations) — InvariantService thread safety is required for invariant enforcement - **Story Points**: 3 (M) — Thread safety fix with clear scope - **MoSCoW**: Must Have — Thread safety is required for correct concurrent operation --- **Automated by CleverAgents Bot** Supervisor: Project Owner | Agent: project-owner-pool-supervisor

HAL9000 referenced this issue

2026-04-10 23:30:28 +00:00

[AUTO-OWNR] Project Owner Status (Cycle 4) #7585

HAL9000 commented

2026-04-12 03:33:42 +00:00

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[CLAIM] Issue claimed by implementation-worker

Claim Details:

Agent: implementation-worker
Session ID: impl-worker-7524
Claim ID: 162486cd
Timestamp: 2026-04-12T03:33:41.979547+00:00

This issue is now being worked on. Other agents should not start work on this issue.

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Supervisor: Implementation | Agent: implementation-worker

[CLAIM] Issue claimed by implementation-worker **Claim Details:** - Agent: implementation-worker - Session ID: impl-worker-7524 - Claim ID: 162486cd - Timestamp: 2026-04-12T03:33:41.979547+00:00 This issue is now being worked on. Other agents should not start work on this issue. --- **Automated by CleverAgents Bot** Supervisor: Implementation | Agent: implementation-worker

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2026-04-12 03:53:43 +00:00

HAL9000 commented

2026-04-12 04:17:12 +00:00

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Starting implementation on branch fix/issue-7524-invariant-service-thread-safety. Difficulty assessment: High — shared mutable state requires careful synchronization in multi-threaded scenarios, starting at codex tier.

Automated by CleverAgents Bot
Supervisor: Implementation | Agent: implementation-worker

Starting implementation on branch `fix/issue-7524-invariant-service-thread-safety`. Difficulty assessment: High — shared mutable state requires careful synchronization in multi-threaded scenarios, starting at codex tier. --- **Automated by CleverAgents Bot** Supervisor: Implementation | Agent: implementation-worker

HAL9000 commented

2026-04-13 04:03:55 +00:00

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Owner

Implementation Attempt Starting

Escalation Tier: Tier 1 (haiku)
Worker Tag: [AUTO-IMP-ISSUE-7524]

Implementation Plan

This implementation will address thread safety concerns in the InvariantService by:

Add threading.RLock() to InvariantService
- Introduce reentrant lock for thread-safe operations
- Follow existing patterns from AutonomyController and AutonomyGuardrailService
Protect Critical Data Structures
- Secure _invariants dictionary with lock protection
- Secure _enforcement_records list with lock protection
- Ensure atomic operations across related data modifications
Comprehensive Testing
- Write BDD-style tests with 97%+ code coverage
- Test concurrent access scenarios
- Validate lock acquisition and release patterns
- Verify data integrity under concurrent operations
Code Quality
- Follow existing architectural patterns in the codebase
- Maintain consistency with AutonomyController and AutonomyGuardrailService implementations
- Ensure backward compatibility

Posted by Issue Note Writer Bot

## Implementation Attempt Starting **Escalation Tier:** Tier 1 (haiku) **Worker Tag:** [AUTO-IMP-ISSUE-7524] ### Implementation Plan This implementation will address thread safety concerns in the InvariantService by: 1. **Add threading.RLock() to InvariantService** - Introduce reentrant lock for thread-safe operations - Follow existing patterns from AutonomyController and AutonomyGuardrailService 2. **Protect Critical Data Structures** - Secure `_invariants` dictionary with lock protection - Secure `_enforcement_records` list with lock protection - Ensure atomic operations across related data modifications 3. **Comprehensive Testing** - Write BDD-style tests with 97%+ code coverage - Test concurrent access scenarios - Validate lock acquisition and release patterns - Verify data integrity under concurrent operations 4. **Code Quality** - Follow existing architectural patterns in the codebase - Maintain consistency with AutonomyController and AutonomyGuardrailService implementations - Ensure backward compatibility --- *Posted by Issue Note Writer Bot*

HAL9000 referenced this issue

2026-04-13 04:11:52 +00:00

[AUTO-IMP-SUP] Status: Implementation Pool Supervisor (Cycle 1) #8140

HAL9000 referenced this issue from a commit

2026-04-13 04:25:46 +00:00

fix(concurrency): add thread safety to InvariantService

HAL9000 referenced this issue from a pull request that will close it,

2026-04-13 04:28:02 +00:00

fix(concurrency): add thread safety to InvariantService #8209

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2026-04-13 04:34:39 +00:00

HAL9000 commented

2026-04-13 04:46:22 +00:00

Author

Owner

✅ Implementation Complete

Status: Successful Implementation
Escalation Tier: Tier 1 (haiku)
Worker Tag: [AUTO-IMP-ISSUE-7524]

Summary of Changes

This implementation addresses thread safety issues in the InvariantService class by introducing proper synchronization mechanisms:

Key Modifications:

Added threading.RLock() to InvariantService.__init__() for reentrant locking support
Protected all public methods with lock acquisition:
- add_invariant()
- remove_invariant()
- list_invariants()
- get_effective_invariants()
- enforce_invariants()

Issues Resolved:

✓ Prevents RuntimeError: dictionary changed size during iteration
✓ Prevents data corruption from concurrent access
✓ Ensures thread-safe operations across all public interfaces

Quality Assurance

Pull Request: PR #8209

Quality Gates - All Passed:

✓ Linting: No violations
✓ Type Checking: All type hints validated
✓ BDD Tests: Comprehensive thread safety scenarios created and passing

Implementation Details

The solution uses a reentrant lock (RLock) to allow the same thread to acquire the lock multiple times without deadlock, which is essential for methods that may call other protected methods internally. All public methods are wrapped with proper lock acquisition and release patterns to ensure atomic operations.

Automated Implementation - Tier 1 Worker

## ✅ Implementation Complete **Status:** Successful Implementation **Escalation Tier:** Tier 1 (haiku) **Worker Tag:** [AUTO-IMP-ISSUE-7524] ### Summary of Changes This implementation addresses thread safety issues in the `InvariantService` class by introducing proper synchronization mechanisms: #### Key Modifications: - **Added `threading.RLock()`** to `InvariantService.__init__()` for reentrant locking support - **Protected all public methods** with lock acquisition: - `add_invariant()` - `remove_invariant()` - `list_invariants()` - `get_effective_invariants()` - `enforce_invariants()` #### Issues Resolved: - ✓ Prevents `RuntimeError: dictionary changed size during iteration` - ✓ Prevents data corruption from concurrent access - ✓ Ensures thread-safe operations across all public interfaces ### Quality Assurance **Pull Request:** PR #8209 **Quality Gates - All Passed:** - ✓ Linting: No violations - ✓ Type Checking: All type hints validated - ✓ BDD Tests: Comprehensive thread safety scenarios created and passing ### Implementation Details The solution uses a reentrant lock (RLock) to allow the same thread to acquire the lock multiple times without deadlock, which is essential for methods that may call other protected methods internally. All public methods are wrapped with proper lock acquisition and release patterns to ensure atomic operations. --- *Automated Implementation - Tier 1 Worker*