FireCompass alternative: breadth or depth on the external surface

TL;DR

FireCompass is a continuous automated red teaming and attack surface management platform, founded in 2019 and headquartered in Bengaluru, India. It raised a $20 million strategic round in September 2025 led by EC-Council's Cybersecurity Innovation Fund, taking total funding to roughly $30 million. The category it sells is breadth: discover the surface, then attack all of it, continuously.

For an EU mid-market buyer weighing it against a specialist:

• Pick FireCompass if you cannot yet draw your own attack surface. Discovery-led coverage of an unmapped estate is worth more than depth on a surface you have not finished finding.
• Pick Fleuret AI if the surface is known and the open question is whether it is actually exploitable, with evidence an auditor will accept.
• Pick both if you have real sprawl and a critical web tier. Discovery and depth are not substitutes for one another.

The honest summary is that "FireCompass alternative" is rarely a like-for-like search. It is usually a buyer discovering that one platform is answering a different question than the one they have.

Why buyers search "FireCompass alternative"

Three profiles turn up on this query.

1. Scope mismatch. A team buys a platform that discovers and tests everything, then finds the depth on their revenue-critical web application is thinner than a focused engagement would produce. Broad coverage and deep exploitation are different engineering problems and very few platforms are excellent at both.
2. Evidence mismatch. The output is a prioritised risk view. What the auditor asked for is a report mapped to a regulatory article, with a reproducible proof for each finding. Those are not the same artifact, and the gap usually surfaces about three weeks before an audit.
3. Data residency review. A DORA-regulated entity reaches the Article 28 third-party risk step and starts asking where processing happens. This is not a judgement about any vendor's security. It is a paperwork question that gets asked earlier every year.

FireCompass: the reference, in one paragraph

FireCompass indexes the surface, deep and dark web included, using reconnaissance techniques borrowed from attackers, then runs multi-stage adversary emulation against what it finds. Its own framing for the category is Continuous Automated Red Teaming. SecurityWeek reports the platform combines attack surface management, continuous threat exposure management, network and application penetration testing, PTaaS and red teaming, that the emulation is aligned to MITRE ATT&CK, and that the company says it can identify vulnerability exposure within 24 hours of a new CVE being disclosed. The company also claims validation at machine scale without false positives. That last one is a vendor claim and we flag it as such, not least because we make a similar claim and readers should discount both until they see a proof of concept they can re-run themselves.

Side-by-side: Fleuret AI vs FireCompass

Axis	Fleuret AI	FireCompass
Headquarters	France	Bengaluru, India
Founded	2024	2019
Category	Agentic AI pentest, specialist	Continuous automated red teaming plus attack surface management
Primary scope	External web app, REST and GraphQL API, external infrastructure	Whole discovered surface, network included
Starting move	Test a scope you already know	Discover the scope first, including unknown assets
Internal network and Active Directory	Not covered in 2026	Covered
Evidence per finding	Reproducible proof of concept, zero false positives tolerated	Risk validation at machine scale, vendor states no false positives
Regulatory deliverable	DORA Article 24 and NIS2 Annex I mapped PDF, shipped by default	Reporting oriented to exposure management
Data residency	EU only, open-weight models on Scaleway France, no US API in the data path	Not published; ask directly
Pricing transparency	Public per test, €4,000 and €8,000, continuous on scope	Not published
Best-fit buyer	EU regulated mid-market with a known, critical web and API surface	Organisations with sprawl or an unmapped estate

Three reading notes.

Breadth and depth are a real trade, not marketing positioning. A platform that discovers thousands of assets and tests all of them continuously is solving a coverage problem. A platform that spends an engagement chaining exploits on one application is solving an assurance problem. Buying the first and expecting the second is the most common disappointment on this query.

Both of us claim zero false positives. That claim is worth nothing on a website, ours included. The only version of it that survives contact with a security team is a finding you can reproduce by hand from the report. Ask both vendors for a proof of concept on your own scope and try to re-run it.

Residency is a paperwork difference, not a safety ranking. FireCompass being India-headquartered says nothing about its engineering. It says that a DORA Article 28 register entry and a NIS2 supply-chain review take longer to write, and that some regulated buyers have a procurement rule that ends the conversation regardless of merit. If that is not your rule, this row should not move your decision.

How both differ from Pentera

This comparison comes up often enough to be worth its own paragraph, because the three vendors are usually shortlisted together and are not really competing for the same job.

FireCompass starts outside and unknown: find the surface, then attack it. Pentera starts inside and known: validate what happens after an attacker already has a foothold, through credential leakage, Active Directory abuse and lateral movement. Fleuret AI starts outside and known: take a defined web and API scope and prove, with a re-runnable exploit, what an attacker can actually reach.

A buyer torn between the three is usually asking an unresolved question about their own risk register. Unmapped exposure, internal blast radius, or external exploitability. The answer decides the vendor, not the other way round.

Buying guide

Buy FireCompass when your asset inventory is a guess, shadow IT is a live problem, or your internal network carries material risk. Discovery-led continuous testing is genuinely the right tool for an estate nobody has fully mapped.

Buy Fleuret AI when the scope is known and the question is assurance: can this be exploited, can you prove it, and will the report satisfy a DORA or NIS2 auditor without a manual rewrite. Add the EU residency requirement and the shortlist gets short.

Buy both when you have sprawl and a critical web tier. Use discovery to keep the map current, and depth where an incident would actually hurt.

Buy neither yet if you have not run a single pentest on your main application. The first engagement usually reframes the whole question, and it is cheaper to learn that from one test than from an annual platform commitment.

Ask any vendor on this shortlist for one finding on your own scope, with the steps to reproduce it. The answer separates the categories faster than any comparison table, including this one.

Where Fleuret AI stands today

Fleuret AI is a French agentic pentest platform. Customer data and inference stay on EU infrastructure, on Scaleway in France with open-weight models and no US API call in the data path, and every engagement ships DORA Article 24 and NIS2 Annex I mappings by default. The scope we cover well is external: web applications, REST and GraphQL APIs, and external infrastructure.

What we do not cover in 2026: internal network, Active Directory, and the discovery of assets you do not know you own. For those, a discovery-led platform or an annual human red team is the better answer, and we would rather say so here than during a procurement call.

If your risk lives on a known external surface and your auditor wants evidence rather than a dashboard, request a demo.

Related reading

• XBOW alternative in Europe: the wider EU agentic-pentest shortlist.
• Pentera alternative: the internal-network side of this comparison, in detail.
• Agentic AI pentesting explained: how multi-agent exploitation actually works.
• Breach and attack simulation vs penetration testing: which side of the split closes a regulatory obligation.
• Sovereign EU AI pentest: the regime behind the data residency question.
• Pentest cost in Europe 2026: the pricing benchmark across categories.

Sources

• FireCompass Raises $20 Million for Offensive Security Platform, SecurityWeek, 5 September 2025: funding, headquarters, founding year, product scope, MITRE ATT&CK alignment, and the 24-hour CVE exposure claim.
• FireCompass Raises $7 Mn Funding, Inc42: the earlier Series A, its investors, and the founders. Cited to show the $7M and $20M rounds are separate events rather than conflicting reports.
• Continuous Automated Red Teaming, FireCompass: the vendor's own category framing, used only for how the company describes itself.
• Regulation (EU) 2022/2554 (DORA), EUR-Lex: Article 24 and Article 28 official text.
• Fleuret AI sub-processors: our own EU residency and GDPR Article 28 disclosure, linked so the claim is checkable.