How SentinelNet Works

A transparent look at the scoring model, sybil detection, trust contagion, and decay mechanisms that power autonomous agent reputation on Base.

Scoring Model

Every ERC-8004 agent is scored across 5 independent dimensions. Each dimension is weighted by its importance to overall trustworthiness, producing a composite score from 0 to 100.

Transaction History
30%

Volume, consistency, and recency of on-chain transactions. Agents with steady, legitimate transaction patterns score higher.

Contract Interactions
25%

Diversity and quality of smart contracts interacted with. Interacting with verified, high-trust contracts boosts this score.

Network Relationships
20%

Quality of peers an agent transacts with. Agents connected to other trusted agents earn higher network scores; connections to flagged agents lower it.

Compliance Signals
15%

Adherence to ERC-8004 registration standards, metadata completeness, and operational transparency.

Anomaly Score
10%

Inverse anomaly detection. Statistical outliers in timing, value, or behavior patterns reduce this dimension. Lower anomaly = higher score.

trust_score = (tx_history * 0.30) + (contract_quality * 0.25) + (network_score * 0.20) + (compliance * 0.15) + (anomaly_inv * 0.10)

Verdicts

The composite score maps to one of three verdicts that determine how the ecosystem treats an agent.

70 – 100
TRUST
Agent passes the TrustGate. Eligible for on-chain attestation, marketplace listing, and full ecosystem participation.
40 – 69
CAUTION
Agent is operational but flagged. May have limited history, borderline patterns, or indirect risk signals. Manual review recommended.
0 – 39
REJECT
Agent fails trust requirements. Blocked by TrustGate. Often associated with sybil networks, anomalous behavior, or compromised wallets.

🕵 Sybil Detection

SentinelNet uses two complementary methods to detect coordinated fake-agent networks. Confirmed sybils receive a −20 penalty applied directly to their trust score.

Wallet-Sharing Analysis

Agents that share a deployer or funding wallet are clustered. When 3 or more agents originate from the same wallet, the entire cluster is flagged as a sybil network.

Detection Rule

shared_wallet_agents ≥ 3 → flag all agents in cluster

Interaction Graph Cliques

Graph analysis identifies isolated cliques — groups of agents that interact almost exclusively with each other. If more than 80% of an agent's interactions are within its own cluster, it's flagged as a sybil ring.

Detection Rule

internal_interactions / total_interactions > 0.80 → isolated ring

Real Example

Wallet 0x67722c... deployed 260 agents that only transacted with each other. All 260 were flagged, penalized −20, and marked as part of the largest sybil network detected.

🌐 Trust Contagion

Trust and risk propagate through the agent interaction graph using a PageRank-inspired algorithm. If you interact with bad actors, your score drops. If you interact with trusted agents, you get a small boost.

Propagation Weights

Negative: 0.6x

Bad reputation spreads aggressively

Positive: 0.2x

Good reputation spreads conservatively

Algorithm Parameters

Damping factor: 0.3 — each hop reduces the propagated effect by 70%, preventing infinite cascades.
Penalty cap: −15 max — no agent loses more than 15 points from contagion alone.
Bonus cap: +10 max — positive contagion is capped to prevent trust inflation.

contagion_effect = sum(neighbor_delta * weight * damping^hops) clamped to [-15, +10]
How It Works

Agent A (score 85, TRUST) frequently transacts with Agent B (score 15, REJECT). Agent A receives a contagion penalty proportional to the interaction frequency and B's low score. After 3 hops, the effect is negligible (0.3^3 = 0.027x).

Trust Decay

Trust scores decay exponentially over time if an agent stops transacting. This prevents stale high scores from persisting indefinitely.

decayed_score = base_score * e^(-lambda * days_inactive) lambda = 0.012

Decay Example

An agent with a base score of 90 that goes inactive:

90Day 0
80Day 10
67Day 30
55Day 50
41Day 75
30Day 100

Score crosses CAUTION threshold (~67) at day 30 and REJECT threshold (~41) at day 75. Active agents reset their decay timer on each transaction.

📊 What We Found

Real results from scanning the ERC-8004 agent ecosystem on Base.

84
Sybil Networks
2,119+
Sybil Agents
754
Contagion-Hit
26/100
Ecosystem Health
400+
Agents Scored
5
Trust Dimensions
Key Insight

An ecosystem health score of 26/100 is exactly why SentinelNet exists. The ERC-8004 registry is flooded with sybils — 56% of all agents are fake. Without SentinelNet, protocols would blindly trust 2,119+ fake agents. The low score isn't a failure — it's SentinelNet's most important finding.

SentinelNet — Autonomous Agent Reputation Watchdog