Proposal: Privacy Analysis Tool + Future ZK Extensions for py-libp2p

[Hany-Almnaem]

Hi everyone 👋

I'd like to propose a privacy analysis tool for py-libp2p with a clear phased approach:

🎯 Phase 1: Privacy Analysis MVP (2-3 months)

Goal: Help developers identify privacy/anonymity leaks in their libp2p applications.

What it would detect:

• Peer ID exposure patterns
• Timing correlation vulnerabilities
  -Traffic volume fingerprinting
• Session linkability risks
• Transport-specific metadata leakage

Proposed Implementation:

• Standalone Python package (for modularity)
• Hooks into py-libp2p node instrumentation
• CLI tool + programmatic API
• Clear privacy reports with actionable recommendations

Proposed Milestones:

1. Design & Scope (Week 1-2): Define measurement targets, Python integration points
2. Instrumentation (Week 3-4): Hook into py-libp2p to log metadata (peer IDs, timestamps, multiaddrs)
3. Analysis & Visualization (Week 5-6): Build privacy reports, connection graphs, timing histograms
4. Tool Release (Week 7-8): Publish findings + tool as standalone package

API sketch:

from libp2p_privacy import PrivacyAnalyzer

analyzer = PrivacyAnalyzer(libp2p_node)
report = analyzer.analyze()
print(report.summary()) # Shows risk levels + recommendations

🚀 Phase 2: ZK-Enhanced Privacy (Future Vision)

Building on Phase 1 findings, explore zero-knowledge proofs for cryptographic privacy guarantees:

• Anonymity set proofs: "I'm one of N peers" without revealing which
• Unlinkability proofs: Cryptographically prove sessions can't be related
• Traffic indistinguishability: ZK proofs that timing/patterns don't leak identity

Python's ZK ecosystem (circom-python, PySnark) makes this feasible for future exploration.

🤔 Questions for the Community

1. Scope: Does Phase 1 align with py-libp2p's priorities?
2. Integration: Start standing alone or build tighter integration from the beginning?
3. APIs: What privacy metrics would be most valuable to developers?
4. ZK Interest: Anyone interested in exploring the Phase 2 vision?

Why This Matters

• Gives developers concrete privacy diagnostics for their apps
• Attracts privacy-critical use cases (healthcare, finance, activism)
• Positions py-libp2p as a leader in privacy-preserving P2P
• Opens path toward privacy certification for distributed systems

Very open to feedback and collaboration! Would love to hear thoughts from maintainers and contributors 🙌

[seetadev]

@Hany-Almnaem : Thank you so much for sharing the discussion proposal. Appreciate it. Reviewing it in details.

Wish to also CC contributors in Py-libp2p, who have expressed interest to pursue certain aspects of this initiative:

CC @Fatumayattani, @Nkovaturient and @acul71

[Hany-Almnaem]

Thanks @seetadev! Really appreciate you taking the time to review it in detail.

[Hany-Almnaem]

Excited to hear from @Fatumayattani, @Nkovaturient, and @acul71 as well - would love to hear your perspectives on the proposal and any areas you'd be particularly interested in exploring.
Looking forward to the feedback and figuring out the best path forward together! 🙌

[Fatumayattani]

I’m interested in contributing to the instrumentation and metrics part, especially how the analyzer can hook into py-libp2p to log and process metadata like peer IDs, timestamps, and multiaddrs. There’s also a strong connection with the network attack simulation framework we’ve been building since the same setup can be extended to capture privacy-related signals like metadata exposure or timing correlations. Linking both efforts can give a more complete picture of network security and privacy in py-libp2p.

[Fatumayattani]

This is a well-structured proposal, @Hany-Almnaem . The focus on practical privacy analysis and the way you’ve structured the phases feels very clear and purposeful. I’m interested in contributing and look forward to being part of the work as it moves ahead.

[Hany-Almnaem]

Hi @Fatumayattani! Thanks so much for the interest and kind words 🙏 Really excited to have you involved! Once we get some feedback from the maintainers on scope and priorities, I'd love to coordinate on how we can work effectively. In the meantime, feel free to share any thoughts. Looking forward to collaborating! 🚀