FireCompass vs Horizon3#1 on HackerOne*
Start free test ↓Finding a bug is only half the job. NodeZero pentests your network. FireCompass AI proves web app and API flaws, chains them into attack paths, gives you the fix, and retests, free.
Autonomous AI agents test your web apps and APIs like a real attacker, prove what is exploitable, and chain findings into full attack paths.
“The platform helps identify potential attack paths and highlight those that are exploitable. It significantly reduces the time required for attack-surface discovery, initial testing, and evidence collection.”
FireCompass on HackerOne
* #1, #2, #3 in multiple HackerOne leaderboards during Q2 & Q3 2026. Source: hackerone.com/leaderboard
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Put the #1 AI hacker to the test. See the attack paths it can chain.
How it works in 60 seconds
- Submit the form. Use your work email and the app you want tested.
- A short kickoff call, then access. We agree on scope, understand your success criteria, and initiate AI agent access.
- AI agents run. Nothing to install. Proven findings, each with exploit proof and a fix, in about a day.
FireCompass vs Horizon3 across key areas.
Both run autonomous attacks and prove what is exploitable. The difference is the layer each one was built for.
| Capability | FireCompass | Horizon3 |
|---|---|---|
| Built for | Web applications and APIs first,then the infrastructure behind them, in one run. | |
| Business logic | Reasons about how your app is supposed to work,so it finds business logic flaws, IDOR, BOLA and broken access control. | |
| Web app validation | Proof of exploit on every web finding,with under 2% false positives. | |
| Attack-path chaining | Chains from app to API to infrastructure,the way a real attacker moves. | Strong attack paths across networks and identity. |
| Public results | #1, #2, #3 in multiple HackerOne leaderboards*and 100% on XBEN, Acuart and DVWA. | Check their latest published results. |
| Where they are strong | Deep web app and API testing that carries through to infrastructure. | Genuinely strong here: proven NodeZero infrastructure and network pentesting. |
* #1, #2, #3 in multiple HackerOne leaderboards during Q2 & Q3 2026.
Horizon3 details are based on Horizon3’s public materials and third-party comparisons as of October 2026. If anything here is out of date, tell us and we will correct it.
Trusted by Avid Technology
Maker of tools used across Hollywood, broadcast and music
“The platform helps identify potential attack paths and highlight those that are exploitable.”
“FireCompass AI Agents have been valuable in supporting our continuous security assessment program. The platform helps identify potential attack paths and highlight those that are exploitable. It significantly reduces the time required for attack-surface discovery, initial testing, and evidence collection compared with a manual penetration-testing approach. This gives our Application Security team more time to focus on fixing and retesting. The FireCompass team has also been collaborative and responsive throughout the process.”
Curious what attack paths exist in your apps? Book a 20-minute walkthrough with our team
Exploit-validated findings, benchmarked in the open.
$5,000 to under $1,000 per app. 2 weeks to 1 day.
Before: manual consulting
- About $5,000 per app, two consultant-days
- 2+ weeks lead time per engagement
- 200 of 2,000+ apps covered, roughly 10 percent
- Isolated findings, no attack chains
After: FireCompass agents
- Under $1,000 per app, about 11x lower
- 1 day lead time, continuous cadence
- 2,000+ apps, about 99 percent of the surface
- Chained attack paths, under 2 percent false positives
What you get from your free AI pen test.
- OWASP Top 10: 2025 plus business logic, authenticated and unauthenticated paths.
- A full pen test report you can share with your team, your auditors, and your customers.
- Access to the FireCompass portal to explore every finding and attack path in one place.
- A working proof-of-concept exploit validated live by an AI agent, not a theoretical flag.
- Evidence, steps to reproduce, and ready-to-run Python for every finding.
Case Study of Agentic Attack Chaining: Combining Low and Medium Vulnerabilities To Exploit A Database
No human steering. No predefined playbook.
- Exposed .git. The agent reconstructed the repo and pulled database credentials from config files.
- Direct DB access blocked. The port was not externally exposed. A scanner stops here.
- Credential reuse to SSH root. The agent tested the same creds against SSH and gained root.
- Internal pivot to data exfiltration. It found private keys, pivoted, and dumped the database.
Autonomous only works if it is safe to run in production.
An attacker inside your environment, even your own, needs rules. We built the controls before we built the demo, because the reliability concerns raised about unsupervised adversarial testing are correct.
- Scope enforcementAgents act only on authorized assets; out-of-scope hosts are discovered, never touched.
- Production-safe exploitationImpact is demonstrated, not caused. Rate limits and safe payloads by default.
- Forensic audit trailEvery request and decision logged and replayable for your auditor.
- Human approval gatesHigh-impact actions wait for a human, if you want them to.
- Kill switchesStop any run, any agent, instantly.
The #1 AI hacker, recognized by analysts and trusted by the Fortune 500.
Compare FireCompass and Horizon3 on your own app, free
Watch an AI agent discover, exploit, and chain across your own web apps and APIs, with a working exploit on every finding.
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- Proof of exploit on every finding
- Production-safe, scope-enforced agents