Case Study 03 / Disinformation

Borderlessdisinformation campaign.

Eleven days from initial narrative emergence to containment. A cross-platform, cross-language influence operation against a regional power — neutralized in 7 of 11 language markets within 96 hours.

SectorDiplomatic & Foreign Affairs
ThreatCross-border, cross-platform IO
Horizon11 days emergence → containment
Languages11 production quality

The first time we have been able to operate on the same tempo as the adversary, in the same languages, with the same level of attribution confidence.

— Foreign ministry strategic communications cell

8%

of projected SoV peak

7/11

markets neutralized in 96h

92%+

Synthetic-content detection

11

languages, cross-modal

The Situation

A regional power, 11 languages, 96 hours to response.

Population

~35M

Bilateral trigger

1 cross-border incident

Languages targeted

11

Platforms targeted

6

Pre-warning

3 days

A cross-platform disinformation campaign targeting a regional power's foreign policy posture, central bank independence, and the personal credibility of its foreign minister. Within 72 hours of a bilateral incident, narrative variants appeared in 11 languages, on 6 platforms, in 4 broadcast markets. The window between emergence and the next G7 summit — at which the foreign minister was scheduled to deliver a keynote — was 11 days.

The Challenge

Four axes on which the conventional playbook failed.

01 / 04

Multilingual reach exceeded in-house coverage.

The client had 4 analysts covering 6 languages; the campaign appeared in 11.

02 / 04

Coordination designed to evade CIB detection.

Clusters did not share infrastructure, did not coordinate posting times, used genuine local influencers as unwitting amplifiers.

03 / 04

AI-generated content at scale.

Synthetic images, audio, and video. The client's prior deepfake detection rate was below 40% — most synthetic content did not trigger existing filters.

04 / 04

Reactive approach had failed twice before.

The rebuttal arrived after the narrative shaped the diplomatic environment. The rebuttal itself became a meta-narrative the adversary exploited.

The Approach

Tiered response, 3 markets at 3 intensities.

Day 1–3

Step 01 / 05

Sovereign cloud + 11 languages

Sovereign cloud instance in client jurisdiction. 47+ platforms, 11 languages at production quality. Bot/CIB detection tuned to cross-platform, cross-language coordination patterns. Deepfake detection at 92%+ rate.

Day 1–3

Step 02 / 05

Narrative + cross-modal mapping

3 core narratives identified (foreign policy posture, central bank independence, personal credibility) and their variants in each of the 11 languages. 7 of 11 markets identified as being targeted with AI-generated synthetic content.

Day 4

Step 03 / 05

Multi-INT fusion + attribution

Multi-INT fusion engine: persona clusters, while appearing independent, shared a common infrastructure procurement pattern. Synthetic content generated on compute instances identified by CYBINT. Payment pattern traced by FININT to a known cutout network associated with a state-aligned actor.

Day 4

Step 04 / 05

Tiered counter-narrative response

Tier 1 (4 markets, no breakthrough): pre-emptive inoculation. Tier 2 (3 markets, traction): rapid rebuttal with public synthetic-content detection. Tier 3 (4 markets, breakthrough): long-tail counter-narrative over 30-day horizon.

Day 4–11

Step 05 / 05

Coordinated client execution

Client executed all three tiers under a unified communications strategy, with the foreign minister's office coordinating the messaging. Pre-positioned counter-assets deployed within hours of mainstream breakthrough.

Disinformation & IO

25-technique taxonomy, 18-technique propaganda library.

Media Intelligence

47+ platforms, 17+ languages, surface+deep+dark.

Multi-INT Fusion

OSINT + SOCMINT + CYBINT + FININT + GEOINT.

Reputation & Perception

8 dimensions, 90+ metrics.

AI & LLM Perception

Multimodal surface, 92%+ synthetic-content detection.

The Outcome

8%

of projected SoV peak

7/11

markets neutralized in 96h

±2 pp

Foreign-minister approval held

11

languages, cross-modal

Engagement timeline

Eleven days, eight milestones.

Day 1

Engagement initiated

Pre-warning from partner service: 'something is coming'. Client needs 96h.

01 / 08

Day 1

Sovereign deployment

11 languages live. Bot/CIB + deepfake detection tuned.

02 / 08

Day 2

3 core narratives mapped

Foreign policy, central bank, personal credibility. 7 of 11 markets = synthetic.

03 / 08

Day 4

Multi-INT fusion

Infrastructure procurement pattern links clusters. FININT cutout attribution.

04 / 08

Day 4

Tiered counter-narrative

T1: inoculation. T2: rapid rebuttal. T3: long-tail.

05 / 08

Day 4–11

Coordinated execution

All three tiers executed. Pre-positioned assets deployed in hours.

06 / 08

Day 11

G7 summit keynote

Foreign minister delivers as scheduled. Negotiating position unaffected.

07 / 08

Day +30

24-month strategic contract

Extended to campaign defense + narrative intelligence + AI perception.

08 / 08

Lessons learned

Three lessons from this engagement.

Lesson 01

Language coverage is a force multiplier, not a feature.

The campaign targeted 11 languages because the adversary knew the client could only cover 6. Equalizing the language asymmetry changed the outcome.

Lesson 02

AI-generated content is now a baseline capability of adversary operations.

The 7 of 11 markets that were targeted with synthetic content were not a special case; they were the campaign's actual mode of operation. Detection capability below 90% is now functionally equivalent to no detection.

Lesson 03

Multi-INT fusion is what makes attribution defensible.

The cyber signal, the FININT signal, and the OSINT signal were each individually suggestive. Together, they were conclusive. The client could not have made a public attribution on any one of them.

Confidential Briefing

Multi-language campaign defense, 96 hours.

The 7-of-11-market neutralization, the 92%+ synthetic-content detection, the three-tier counter-narrative — all in a confidential briefing tailored to your specific language and platform surface.

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