CredScore verdict
0x809e…8834ethereumScore
12
0 = max risk · 100 = clean
High riskEscalateConfidence:50%
Escalate for deeper review
CredScore sees a 9-month-old wallet with at least 501 transfers. Sanctions-sensitive exposure context and High-confidence sanctions attribution are severe enough to require escalation before any further interaction.
Wallet snapshot
Wallet age
9 months
Transfers observed
501
Last activity
5 months ago
Counterparties
110
Primary risk drivers
Sanctions-sensitive exposure context
Sanctioned counterparty interactions observed: 1 · Observed labels: USDT Token, circle, maker
Sanctions-sensitive attribution materially increases review urgency because legal and compliance context becomes critical.
High-confidence sanctions attribution
Sanctioned counterparty interactions observed: 1
Sanctions-sensitive attribution materially increases review urgency because legal and compliance context becomes critical.
History capped by fetch limit
Transfers observed: At least 501 · History cap: observed count may be a lower bound (cap 500)
Incomplete transfer coverage reduces confidence because observed totals may be lower bounds.
Sanctioned counterparty interactions
Observed entity context
Labels
USDT TokencirclemakertetherDAI Token
Protocols
USDT contracttethercircleShiba Inu (SHIB)maker
Offsetting factors
Recognizable exchange or protocol context
Observed label: USDT Token · Observed label: circle · Observed label: maker
Recognizable protocol attribution
Observed protocol: USDT contract · Observed protocol: tether · Observed protocol: circle
Analyst briefing
Executive Risk Verdict
This address presents elevated counterparty risk. Sanctions-sensitive exposure context and High-confidence sanctions attribution compose adverse signal severe enough to justify escalation under current coverage.
Decision Posture
Escalate for deeper review. A specific high-risk signal combination was detected (sanctions self). This pattern is materially more concerning than any individual flag in isolation and requires human context to resolve correctly.
Primary Risk Drivers
Sanctions-sensitive exposure context Sanctioned counterparty interactions observed: 1 Observed labels: USDT Token, circle, maker Sanctions-sensitive attribution materially increases review urgency because legal and compliance context becomes critical.
High-confidence sanctions attribution
Sanctioned counterparty interactions observed: 1
Sanctions-sensitive attribution materially increases review urgency because legal and compliance context becomes critical.
History capped by fetch limit
Transfers observed: At least 501
History cap: observed count may be a lower bound (cap 500)
Incomplete transfer coverage reduces confidence because observed totals may be lower bounds.
Offsetting Factors
Recognizable exchange or protocol context Observed label: USDT Token Observed label: circle Observed label: maker
Recognizable protocol attribution
Observed protocol: USDT contract
Observed protocol: tether
Observed protocol: circle
Structural Pattern Observations
Fan-out distribution (high confidence) The observed flow pattern is consistent with fan-out distribution behavior and also carries additional review pressure from thin visibility, limited history, or sensitive exposure. This is not a misconduct finding, but it is not a routine pattern under current coverage.
Behavior Distribution
Attributed interactions: 100% of observed activity, but only 5% resolved with high confidence, the remainder are unlabeled contract interactions, which is opacity rather than meaningful attribution coverage. High-confidence attributed interactions: 5% of observed activity.
Observed Entity / Protocol Context
USDT Token circle maker tether DAI Token
Observed Protocol Attribution
USDT contract tether circle Shiba Inu (SHIB) maker
Confidence Statement
Overall assessment confidence is moderate (50%), reflecting partial coverage with usable but still incomplete behavioral signal.
Sensitivity notes
Improved transaction coverage could materially change activity-based interpretation and increase confidence.
Improved data coverage for missing core metrics would likely improve confidence and may affect the trust score.
Off-chain context would be particularly valuable here, the detected structural patterns raise interpretive ambiguity that on-chain data alone cannot resolve.
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Shared Aug 24, 2026