Compare
AttackCompass vs PentestGPT
PentestGPT sits in the AI-assisted / autonomous pentesting tooling category (interactive guidance historically; newer agentic modes aim to drive more of the attack loop). AttackCompass is the engagement intelligence layer: ranked next actions from recorded engagement state, with the operator in control of execution — not an autonomous attacker.
Context
What PentestGPT is good at
Category-true framing from public positioning — not an invented feature matrix.
- LLM-assisted planning and next-command suggestions for testers exploring a target
- Agentic / automated pipelines for CTF-style or isolated lab workflows where the product’s own docs say that is appropriate
- Useful when the buyer wants AI to drive more of recon→exploit loops under their own rules of engagement
AttackCompass
What AttackCompass adds
- Ranked next actions from recorded scope, hosts, services, credentials, findings, attempts, and evidence — with reasons
- Core recommendations are deterministic and evidence-aware, not open-ended model improvisation as the source of truth
- Blocked steps show missing prerequisites; priorities change as state changes
- Web product does not autonomously execute attack tools; operator-controlled for authorized pentesting
- Workspace holds engagement objects together; report workflow from captured work
- Not another tool you run; keeps the engagement coherent while you run tools you trust
You can keep AI assistants for ideation or lab automation when authorized. Use AttackCompass to keep live engagement state and next steps coherent for client work. AttackCompass is not marketed as AI-powered or autonomous security testing.
Side by side
Category comparison
Where a cell shows a dash, that product is not built for that job.
| Topic | PentestGPT (category) | AttackCompass |
|---|---|---|
| Primary job | AI-assisted / agentic pentest tooling | Operator-controlled engagement guidance |
| Who executes attacks | Often the agent or the human following AI-suggested commands (varies by mode) | Operator always executes; AttackCompass does not auto-run attacks |
| Source of “what next” | LLM reasoning over session / tool output | Deterministic ranked actions from recorded engagement state |
| Engagement workspace | Session/tool-oriented (category) | Hosts, services, creds, findings, evidence, sessions, routes |
| Reporting | Varies / walkthrough-oriented in agentic flows | Report editor from captured work; PDF; lossy Markdown |
| Best when | You want AI to drive more of the attack loop in authorized/lab contexts | You want coherent state + ranked “what next” without autonomous execution |
FAQ
Common questions
- Is AttackCompass basically PentestGPT?
- No. AttackCompass is an engagement intelligence layer, not an autonomous AI pentester.
- Does AttackCompass run attacks for me?
- No. Recommendations only; you execute.
- Do you use AI to decide scope?
- Core engagement logic is evidence-aware and deterministic. Ask/Ollama-style features are not claimed as shipped.
- Can I use both?
- Yes in principle: keep AI assistants for ideation or lab automation if authorized; use AttackCompass to keep live engagement state and next steps coherent for client work.
- Is this a scanner?
- No.
Try it on a real engagement
Start a 7-day trial — full Founding Operator access, no card to start. Then Founding Operator $49/mo or $399/yr. Team plans: [email protected].