Project ideas from Hacker News discussions.

We hid backdoors in ~40MB binaries and asked AI + Ghidra to find them

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

Three prevailing themes in the discussion

Theme	Key points	Supporting quotes
1. Open‑source binary‑audit tooling & benchmarking	Participants highlight the availability of a public benchmark and the corresponding GitHub repo, underscoring the community’s push for measurable, reproducible security analysis.	“See direct benchmark link: https://quesma.com/benchmarks/binaryaudit/” – jakozaur
2. AI’s potential to spot distributed back‑doors	The conversation turns to whether machine‑learning models can detect subtle, coordinated weaknesses that individually appear benign but together grant unauthorized access.	“Along this line can AI's find backdoors spread across multiple pieces of code and/or services? i.e. by themselves they are not back‑doors, advanced penetration testers would not suspect anything is afoot but when used together they provide access.” – Bender
3. The danger of compounded, low‑impact vulnerabilities	Users illustrate how seemingly innocuous flaws in separate components (e.g., systemd, udev, binfmt) can combine to bypass authentication or mandatory access controls.	“e.g. an intentional weakness in systemd + udev + binfmt magic when used together == authentication and mandatory access control bypass. Each weakness reviewed individually just looks like benign sub‑optimal code.” – Bender

These themes capture the discussion’s focus on tooling, AI‑driven threat detection, and the hidden risks of combined, low‑impact vulnerabilities.

🚀 Project Ideas

BackdoorFinder AI

Summary

AI‑driven platform that scans source code, binaries, and system configurations to detect distributed backdoors that only become apparent when multiple components interact.
Provides automated alerts, risk scoring, and remediation guidance for developers and security teams.

Details

Key	Value
Target Audience	Security engineers, DevOps teams, open‑source maintainers
Core Feature	Multi‑component backdoor detection using NLP + graph analysis
Tech Stack	Python, PyTorch, Graph Neural Networks, Docker, CI/CD integration
Difficulty	High
Monetization	Revenue‑ready: subscription (tiered per‑project usage)

Notes

HN commenters ask: “can AI’s find backdoors spread across multiple pieces of code and/or services?” This tool directly answers that question.
Practical utility: integrates into CI pipelines, reduces manual code review effort, and surfaces hidden privilege‑escalation paths.

BinaryAudit Benchmark Hub

Summary

Web‑based platform that aggregates, standardizes, and visualizes benchmark results for binary audit tools (e.g., BinaryAudit, Quesma, etc.).
Enables researchers and practitioners to compare tool performance on a common dataset and contribute new benchmarks.

Details

Key	Value
Target Audience	Security researchers, tool developers, academia
Core Feature	Unified benchmark repository, automated result ingestion, leaderboard
Tech Stack	Node.js, PostgreSQL, Docker, React, CI/CD pipelines
Difficulty	Medium
Monetization	Revenue‑ready: freemium (free public data, paid analytics & API)

Notes

The discussion references a benchmark link: “See direct benchmark link: https://quesma.com/benchmarks/binaryaudit/”. This hub consolidates such links and adds community‑driven tests.
Encourages open discussion on tool efficacy and fosters reproducible research.

Component Interaction Vulnerability Analyzer (CIVA)

Summary

Static and dynamic analysis engine that models interactions between system components (systemd, udev, binfmt, etc.) to uncover combined privilege‑escalation or bypass vectors.
Generates dependency graphs and simulates attack chains across components.

Details

Key	Value
Target Audience	Kernel developers, OS maintainers, security auditors
Core Feature	Cross‑component interaction modeling, attack‑chain simulation
Tech Stack	Rust, LLVM, eBPF, Go, WebAssembly for sandboxing
Difficulty	High
Monetization	Hobby

Notes

Addresses the pain point highlighted: “Each weakness reviewed individually just looks like benign sub‑optimal code.” CIVA surfaces the hidden synergy.
Provides a practical utility for kernel security teams to pre‑empt multi‑component backdoors before release.