Harden code review protocol

[reactive-firewall]

Problem

@coderabbitai could present a significant security risk if it is able to approve closed or invalid PRs with just a comment command; this essentially defeats the purpose of requiring reviews and/or makes @coderabbitai incompatible with the role and introduces CWE-655

_Originally seen in coderabbitai/coderabbit-docs#274

Risk Mitigation

• fortunately code-signing does allow identification of ai introductions of code by use of a different key identity allowing for repudiation remedies
• AI can not bypass protection on the stable branch with just review approval forgery

Response Plan

• look into disabling this feature of @coderabbitai
• Draft AI policy to communicate impact on project

[reactive-firewall]

Risk Assessment

Despite branch protections requiring PR review with approval (eg. "un-reviewed" PR #390) demonstrating CWE-655.

Namely in the example of PR #390 the AI review was not possible due to the large change set involved (eg. 128 changed files, 107 of which were selected by AI for review) so the AI reported exceeding throttling controls to the user. While the actual commit should be benign and was not performed by a malicious user, the CWE-655 was still demonstrated by the user forcing a meaningless AI approval on PR #390.

---

Caution

THEREFORE reliance on AI approvals is considered insufficient as a gatekeeping mechanism, and equivalent to single user controls (eg.same as if no AI were used).

---

Risk Mitigation

• fortunately code-signing does allow identification of ai introductions of code by use of a different key identity allowing for repudiation remedies
• AI can not bypass protection on the stable branch with just review approval forgery

[reactive-firewall]

Additional Informative references

• see Add command to unapprove then reapprove an already approved PR coderabbitai/coderabbit-docs#266
• see Announce agent chat in changelog coderabbitai/coderabbit-docs#274 (comment)
• https://github.com/coderabbitai

[reactive-firewall]

@coderabbitai please read-up on GHI #367 and then generate a possible project policy for AI usage/integration following best practices and aligning with relevant project conventions and policies.

[coderabbitai]

Tip

For best results, initiate chat on the files or code changes.

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
# Get more details about issue #367
gh issue view 367 --repo reactive-firewall/multicast

# Let's check existing policies or guidelines in the repository
echo "Checking for existing policy files..."
find . -type f -name "*.md" | grep -i -E 'policy|guideline|contribution|security|governance' | xargs ls -la

# Let's look at the structure of the repository
find . -type f -name "*.py" | head -n 5

Length of output: 3516

---

🏁 Script executed:

#!/bin/bash
# Let's check the current AI configuration
cat .coderabbit.yaml

# Look at the relevant security policies and branch protection rules if any
find .github -type f -name "*.md" | xargs cat

# Check issue #367 comments for any additional context
gh issue view 367 --repo reactive-firewall/multicast --comments

# Let's look at the CodeRabbit docs references mentioned in the issue
gh issue view 266 --repo coderabbitai/coderabbit-docs || echo "Unable to access issue"

Length of output: 34769

---

@reactive-firewall Based on my analysis of GHI #367 and the project's current configuration, I've drafted a comprehensive AI usage/integration policy for the Multicast project. This policy addresses the CWE-655 concerns while establishing clear boundaries for AI in the development workflow.

Multicast Project AI Usage Policy

1. Purpose and Scope

This policy governs the use of AI tools, particularly CodeRabbit, within the Multicast project's development workflow. It establishes guidelines for responsible AI integration while maintaining the project's security, quality, and integrity.

2. AI Role Definitions

2.1 Permitted AI Roles

• Assistive Code Review: AI may provide feedback on code quality, style compliance, and potential issues
• Documentation Improvement: AI may suggest improvements to documentation clarity and completeness
• Test Coverage Analysis: AI may identify areas lacking test coverage
• Code Generation Assistance: AI may suggest code implementations when requested

2.2 Prohibited AI Roles

• Sole Approver: AI approval alone is insufficient for merging any PR
• Security Gatekeeper: AI cannot be the only mechanism for security validation
• Unrestricted Auto-Merge: AI cannot trigger auto-merge without human verification

3. PR Review Process

3.1 Required Human Review

• All PRs MUST receive at least one human review from an authorized maintainer
• Human reviews must verify the AI's suggestions before implementation
• For PRs exceeding 75 changed files, at least two human reviews are required

3.2 AI Review Requirements

• AI reviews are supplementary and do not replace human review
• When AI review is triggered but fails (e.g., due to throttling), the PR must be marked as requiring additional attention
• AI approval comments must not be used to bypass branch protection rules

3.3 Large PR Handling

• PRs with more than 100 changed files should be split into smaller PRs when possible
• When splitting is not feasible, PR authors must provide a summary highlighting the most critical changes for human reviewers

4. Security Considerations

4.1 Verification and Validation

• All AI-suggested code changes must be verified by a human maintainer
• Code signing with different keys for human vs. AI contributions is required
• AI-suggested security fixes must undergo additional human security review

4.2 Branch Protection

• Stable and master branches must maintain protection rules requiring:
  • Minimum of one human approval
  • Signed commits
  • Passing CI checks
• Force-pushing to protected branches is prohibited

4.3 CWE-655 Mitigation

• The project implements a dual-approval system to prevent single points of failure
• AI approvals are tracked separately from human approvals in the review process
• "Meaningless" AI approvals (where AI didn't actually review code) must be invalidated

5. Implementation and Compliance

5.1 Configuration Management

• The .coderabbit.yaml file is the source of truth for AI configuration
• Changes to this configuration require PR approval from at least one core maintainer
• Regular audits of AI configuration will be conducted to ensure alignment with this policy

5.2 Monitoring and Reporting

• Periodic audits of PR approvals will verify compliance with this policy
• Security incidents related to AI usage must be reported via project security channels
• Documentation of AI usage patterns will be maintained to improve future policy iterations

5.3 Developer Training

• Contributors should understand the limitations of AI tools in the review process
• Clear communication about when and how to utilize AI assistance will be provided
• New contributors will be directed to this policy as part of onboarding

6. Exceptions

Exceptions to this policy require:

• Documented justification
• Approval from at least two core maintainers
• Time-limited scope with defined expiration
• Post-implementation security review

7. Policy Review

This policy will be reviewed:

• At minimum every 6 months
• After any security incident involving AI tools
• When significant changes to project AI integration are proposed

---

This policy follows the principle of "Avoid Hasty Abstraction" by providing clear boundaries without unnecessary complexity, while addressing the specific security concerns raised in issue #367.

Would you like me to make any adjustments to this draft policy?

---

🧠 Learnings used

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#115
File: multicast/hear.py:180-180
Timestamp: 2024-09-19T03:43:24.037Z
Learning: Reactive-firewall prefers to re-use already loaded modules to keep memory overhead low when possible.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#115
File: multicast/hear.py:180-180
Timestamp: 2024-10-08T21:59:30.537Z
Learning: Reactive-firewall prefers to re-use already loaded modules to keep memory overhead low when possible.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#379
File: .ast-grep/utils/python/structure/multicast-mtool-subclass-definitions/undecorated_function_definition.yml:8-12
Timestamp: 2025-04-23T04:07:24.393Z
Learning: Reactive-firewall follows the "Avoid Hasty Abstraction" principle, being cautious about changes that might introduce unnecessary abstractions or alter existing behavior, particularly in configuration files like ast-grep rule definitions.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#139
File: tests/test_fuzz.py:73-73
Timestamp: 2024-10-08T21:59:27.171Z
Learning: Reactive-firewall prefers not to introduce new dependencies into the codebase when writing test functions.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#235
File: .github/workflows/makefile-lint.yml:41-52
Timestamp: 2024-12-06T08:21:21.876Z
Learning: Reactive-firewall prefers to suppress errors in `apt-get install` commands when individual checks of the installed packages are performed afterwards, to allow for more granular error handling.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#118
File: tests/check_pip:92-197
Timestamp: 2024-10-08T21:59:30.537Z
Learning: Reactive-firewall prefers defining functions before they are called in Bash scripts to avoid errors due to Bash's sequential interpretation.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#373
File: docs/utils.py:30-39
Timestamp: 2025-04-21T23:37:00.037Z
Learning: Reactive-firewall prefers explicit domain allowlists (adding specific domains/subdomains individually) over pattern-based domain validation for security reasons, following the "Avoid Hasty Abstraction" principle for security implementations.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#184
File: tests/test_hear_keyboard_interrupt.py:70-70
Timestamp: 2024-11-14T02:25:25.684Z
Learning: Reactive-firewall prefers to include suggested code changes or fixes in the issue's description when requested.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#148
File: tests/MulticastUDPClient.py:83-84
Timestamp: 2024-10-05T09:05:28.234Z
Learning: Reactive-firewall prefers to assign to `__module__` at the module level in their Python test modules.

---

Learnt from: reactive-firewall
PR: reactive-firewall/multicast#184
File: LICENSE.md:36-43
Timestamp: 2024-11-14T07:03:35.207Z
Learning: Reactive-firewall prefers that I verify URLs before suggesting changes, and avoid raising hypothetical issues without verification.