How This Briefing Works
This report opens with key findings, then maps the gaps between what Equativ discloses and what BLACKOUT observed at runtime. From there: what it means for your organization, what to do about it, and the detection data and evidence underneath.
Key Findings
Pre-Consent Activity
Equativ was observed loading and executing before user consent was obtained on 50% of sites where it was detected.
Claims vs. Observed Behavior
pending
“Unknown”
Requires claims extraction via CDT
What This Means For You
What To Do About It
Role-specific actions based on observed behavior
If You Use Equativ
- →Demand transparency on attribution methodology and implement independent conversion tracking via first-party analytics
- →Configure privacy-preserving audience targeting using contextual signals rather than behavioral profiles
- →Require contractual limits on bid stream data sharing and audience segment resale
- →Implement consent-first deployment where tracking only activates after explicit user opt-in
If You're Evaluating Equativ
- →Request third-party audit of consent bypass mechanisms and fingerprinting practices
- →Evaluate alternative programmatic platforms with documented privacy-first architectures (e.g., contextual targeting DSPs)
- →Consider direct publisher relationships to eliminate RTB competitive intelligence leakage
- →Assess incremental ROAS of programmatic versus direct buys after correcting for attribution inflation
Negotiation Leverage
- →Equativ VRS 80 = Broker (65) + Counselor (45) threat. RTB bid stream = competitive intelligence broadcast. Demand data minimization commitments.
- →Consent bypass (BTI-C09) + fingerprinting (BTI-C10) = ongoing GDPR violation risk. Request technical remediation or consider contract exit.
- →Attribution methodology opacity creates measurement corruption. Negotiate SLA on conversion tracking accuracy with third-party verification.
- →Behavioral biometrics (BTI-C06) for audience modeling = special category data processing. Require explicit legal basis documentation.
- →Ask: What user data is included in bid requests? How long are audience profiles retained? What is the opt-out mechanism? Expect evasive answers.
- →Programmatic efficiency gains must be weighed against competitive intelligence leakage and regulatory risk. Demand cost-benefit analysis with legal review.
Runtime Detections
BLACKOUT observed this vendor's JavaScript executing in a live browser and classified each hostile behavior using our BTI-C (Behavioral Threat Intelligence — Capability) taxonomy. These are not theoretical risks — each code below was triggered by something we watched this vendor's code actually do.
Evasion infrastructure, auditor bypass
Impact: Tag behavior varies based on detection of privacy tools or regulatory environments, presenting compliant facade while conducting full tracking in permissive contexts.
Keystroke/mouse tracking
Impact: Mouse tracking and interaction patterns feed audience models used for cross-site targeting, creating persistent user profiles that survive cookie deletion.
Ignoring CMP signals
Impact: Tracking pixels and fingerprinting continue after consent rejection, creating per-violation GDPR liability and undermining consent management platform investments.
Device identification
Impact: Browser and device fingerprinting creates stable identifiers used for ad frequency capping and attribution across domains, violating user privacy expectations and regulatory requirements.
IOC Manifest
Indicators of compromise across 3 categories. Use for detection rules, CSP policies, or Pi-hole blocklists.
No indicators in this category
Ecosystem & Supply Chain
Evidence Artifacts
Artifacts collected during analysis, available with evidence-tier access.
Complete network capture with all requests and responses
16 detection signatures across scripts, domains, cookies, and network endpoints