AI tool comparison
AutoProber vs Shannon
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Security
AutoProber
AI-driven hardware hacking arm — CNC-controlled PCB probing with an LLM agent
50%
Panel ship
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Community
Paid
Entry
AutoProber is an open-source hardware security research platform that puts an LLM agent in control of a physical CNC machine to autonomously probe circuit boards. The build uses off-the-shelf parts: a webcam, a USB microscope, a cheap CNC frame, and a probe tip. The agent handles the full hacking workflow — target PCB discovery, microscope-assisted mapping of test points, CNC motion planning with safety bounds checking, and controlled pin probing for UART/JTAG/SWD interfaces. The software stack is pure Python. The agent generates motion commands in a DSL, validates them against hardware safety constraints before execution, and updates an exploration map as it discovers new test points. GainSec posted a demo video showing the arm autonomously locating and probing a router PCB's debug interface without human intervention after initial setup. What makes this genuinely novel isn't the individual components — hobbyists have built CNC probers before — but the LLM-in-the-loop architecture that turns the whole process from a manual expert skill into a semi-automated one. Security researchers who previously needed 15 years of experience to read a PCB layout now have a tutor and co-pilot on the physical bench.
Security
Shannon
Autonomous AI that finds your vulnerabilities and exploits them — for you
75%
Panel ship
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Community
Free
Entry
Shannon is an autonomous AI security research agent from Keygraph that takes a target (web app, API, or codebase) and runs a full offensive security workflow: static analysis, attack surface mapping across OWASP Top 10, and then actual proof-of-concept exploit execution — all without manual intervention. It orchestrates real security tools (Nmap, Subfinder, SQLMap, Playwright) under the hood, not just generating reports. The Lite tier (AGPL-3.0) handles web apps and API endpoints, running browser automation and fuzzing attacks autonomously. Shannon Pro (commercial) adds SAST/SCA integration, CI/CD pipeline hooks for PR scanning, and team-level finding management. The model layer is pluggable — defaults to GPT-4o for planning with Claude Sonnet for exploit reasoning, but can be pointed at local models. What sets Shannon apart from tools like Burp Suite or ZAP is the agentic loop: it doesn't just surface a list of potential issues, it attempts exploitation and logs what worked. For small security teams and solo founders doing pre-launch security checks, this compresses days of pentesting work into a single automated run. The open-source Lite tier is the real news here — genuine autonomous exploitation capability, freely available.
Reviewer scorecard
“The safety constraint validation layer before any CNC motion is the right call and shows the author understands what goes wrong when you mix LLMs with physical actuators. The DSL for motion commands is clean. This is a real research tool, not a toy.”
“I've been paying $400/month for a pentesting retainer for pre-launch checks. Shannon Lite ran against my staging environment and surfaced an actual SQLi vulnerability in 20 minutes that my last manual audit missed. The AGPL license means I can self-host it in my CI pipeline without worrying about data leaving my network.”
“The agent hallucinates PCB pin assignments in about 20% of cases based on the demo, which in a physical system means a bent probe or a shorted component. The hardware cost to build a reliable version is non-trivial, and you still need domain expertise to validate what the agent decides.”
“Autonomous exploitation tools have serious dual-use liability. The AGPL license doesn't prevent anyone from running Shannon against systems they don't own — and AI-generated PoC exploits at this speed are a real threat multiplier for less-sophisticated attackers. I'd want to see proper authorization checks and rate limiting baked into the Lite tier before recommending this broadly.”
“This is physical AI applied to the supply chain security problem. AI-assisted hardware auditing could eventually make it practical to spot tampered firmware chips or backdoored components at scale — a national security capability currently gated behind a tiny pool of expert humans.”
“Security tooling is going through the same shift coding did with Copilot — autonomous agents are going to make pentesting accessible to every small team that currently can't afford it. Shannon is an early version of what eventually becomes a background daemon watching your entire attack surface 24/7.”
“Not my domain, but the demo video is one of the coolest things I've seen this week. The moment the arm autonomously repositions based on the microscope view is genuinely impressive. Niche hardware security tool, but an inspiring proof of concept for physical AI.”
“Less relevant to my workflow directly, but I've started including 'ran Shannon against my portfolio site' in client pitches as a trust signal. The fact that indie creators can now point a professional-grade security tool at their own work without a $5K budget is a shift worth noting.”
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