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Sector analysis · Cybersecurity · France

GEO for cybersecurity in France: who AI recommends — and who it ignores

32 French cybersecurity brands measured on ChatGPT, Perplexity, Gemini and Claude. Thales leads at 95/100. 68% score below 50. The NIS2 citation effect is real — and measurable.

EV
Elena Vasquez
Jul 2, 2026 · 7 min read
CYBERSECURITY FRANCE — AI VISIBILITY · LVI JULY 2026
95/100
Thales — #1 cited brand
68%
of 32 brands score below 50/100
32
brands measured across 4 LLMs
On this page
01 · Market overview
02 · Full ranking (32 brands)
03 · Why NIS2 drives citations
04 · What works
05 · 90-day action plan

Market overview

When a CISO asks ChatGPT "best cybersecurity solution for a French SME under NIS2", the answer is a shortlist of 3 to 5 names. That shortlist is not random. It is measured. The LLM Visibility Index tracks which brands are cited across ChatGPT, Perplexity, Gemini and Claude on buyer-intent prompts in the French cybersecurity market. July 2026 data covers 32 brands.

Full ranking — 32 brands, cybersecurity France

# Brand LVI Score
01 Thales 95/100
02 Orange Cyberdefense 93/100
03 Capgemini 88/100
04 Ledger 86/100
05 Atos / Eviden 85/100
06 Airbus CyberSecurity 84/100
07 Sopra Steria 78/100
08 Stormshield 76/100
09 Wallix 75/100
10 Resilium 75/100
11 Idemia 74/100
12 Tehtris 72/100
13 HarfangLab 71/100
14 Sekoia.io 68/100
15 CrowdSec 64/100
16 YesWeHack 63/100
17 Safran 62/100
18 Filigran 61/100
19 Vade 60/100
20 Synacktiv 60/100
21 CybelAngel 59/100
22 Inetum 58/100
23 Gatewatcher 58/100
24 Quarkslab 57/100
25 Devoteam 56/100
26 Advens 55/100
27 Olvid 50/100
28 Egerie 45/100
29 Pradeo 44/100
30 Glimps 42/100
31 Sesame IT 40/100
32 Cyna-IT 30/100

Source: LLM Visibility Index — llm-visibility-index.com/category/cybersecurity-france/ — July 2026

Why NIS2 and DORA are reshaping citation patterns

NIS2 (October 2024) and DORA (January 2025) created a wave of high-intent AI queries: "which solution for NIS2 compliance", "best EDR for regulated French SME". Brands that produced structured answer-first content before these deadlines captured a citation lead that compounds over time.

Key finding: Stormshield (76) and Wallix (75) both saw citation gains on NIS2-specific prompts after publishing structured compliance guides in H2 2024. Their content was indexed by Perplexity within weeks of publication.

What works — and what does not

Top performers share three traits: (1) high domain authority from institutional co-citations — ANSSI reports, ENISA publications, CLUSIF documents — (2) structured answer-first content targeting exact regulatory vocabulary (NIS2, DORA, ANSSI, EDR, SIEM), (3) consistent coverage across all four AI engines.

What does not generate citations: product landing pages, press releases, generic "our solution is NIS2-compliant" copy. LLMs do not cite promotional content on informational queries.

90-day action plan for brands below 60/100

Month 1: Measure current citation score on 20 priority NIS2/DORA/RSSI prompts. Map which competitors appear in your place.

Month 2: Produce 3 answer-first assets targeting the highest-gap prompts — regulatory article analyses, operational checklists, anonymized case data. Distribute in tier-1 cyber media (MISC, L'Informaticien) and r/netsec.

Month 3: Re-run the prompt corpus, measure delta, adjust based on which assets generated the most citation uplift.

Sources
  • LLM Visibility Index — llm-visibility-index.com/category/cybersecurity-france/ — July 2026
  • ANSSI — panorama de la menace informatique 2025
  • ENISA threat landscape report 2026
Continue reading
Ranking
GEO agencies ranked by AI visibility: the LVI leaderboard
Research
How AI engines select their sources — and how to get in
Playbook
NIS2 and AI citations: the 60-day playbook