Solana meme coin scanner monitors cohort risk on Pump.fun bonding curves

Factual monitoring through a Solana meme coin scanner shows that coordinate wallet cohorts capture pump.fun bonding curve entry points before public market transition.

Bonding Curve Indexer Freshness and Board Metrics

Real-time launch analytics require high indexer freshness to map event pipelines. At 2026-06-23 07:31 UTC, the active indexer logged a freshness of 0.0 minutes old, confirming live operation status. The database tracking these activities, /root/Pumphouse/pump_events_live.db, processes transactions through WebSocket nodes. The system monitors connections as described in the Solana RPC WebSocket docs. Over a six-hour window, the fresh board registered 200 tokens. The scanner categorized these launches into risk segments: 15 green tokens, 159 amber tokens, and 26 red tokens. This categorization relies on programmatic signals written to /var/www/memes/api/signals.json. It identifies structural anomalies, developer changes, and early holder profiles prior to graduation. By mapping metadata through /var/www/memes/api/manifest.json, the scanner isolates launch metadata before tokens reach public liquidity pools.

Wallet Cohort Tracking and Cluster Risk Analysis

Detecting coordinate actor groups is crucial for identifying structural risks in token supply distribution. The wallet finder service logs transaction records in /var/www/memes/api/wallet_finder.json to identify cluster edges. The active database /root/Pumphouse/pumphouse_cohort.db tracks a cohort of 74 wallets. These wallets are monitored to determine if they operate in tandem during early launch phases. This identification process forms the foundation for Pump.fun cabal detection, which flags coordinated buy patterns across multiple launches. A trending scanner tracks 30 read-only wallets on a 15-minute window to identify shifting wallet concentrations. The data is written to /var/www/memes/api/trending.json.

Evaluating holder concentration is performed using a Solana holder scanner that processes historical balance snapshots. If multiple wallets are funded from a single source, the connection is written to the funder intelligence database at /root/Pumphouse/funder_intel.db. This database monitors wallet creation times and funding routes. The current verification system enforces strict claim rules: a minimum of a 2.5x lift across at least two fresh, non-overlapping live windows is required before any public or token claim can be validated. This protocol ensures that transient volatility does not trigger false positives in coordination alerts. The private state of these alerts is stored in /root/Pumphouse/pro_alerts_state.json.

Simulation Lanes and Paper Replay Outcomes

To evaluate bonding-curve tracking rules without executing live transactions, the system logs simulated trades in a memecoin paper demo ledger. This ledger records entry and exit signals under controlled conditions. The paper model operates with a base bankroll of GBP 50.0 and a standard stake of GBP 0.5 per trade. For specific high-velocity momentum lanes, including MEDIA_VELO, MEDIA_VELOR, VELO, and VELOR, the stake is set to GBP 2.5. The ledger, backed by /var/www/memes/api/copy_demo.json, records performance across several distinct strategy lanes:

• BUNDLE_V: GBP 481.53 (+431.53), 1263 of 1843 entered, 12.1% win rate (best 7639.7%, worst -93.1%).
• BUNDLE_Q50: GBP 339.45 (+289.45), 607 of 1195 entered, 10.9% win rate (best 9797.5%, worst -93.8%).
• BUNDLE: GBP 330.5 (+280.5), 602 of 1368 entered, 10.5% win rate (best 9797.5%, worst -93.8%).
• VELO: GBP 162.77 (+112.77), 321 of 321 entered, 50.2% win rate (best 223.9%, worst -91.4%).
• VELOR: GBP 90.31 (+40.31), 188 of 241 entered, 40.7% win rate (best 344.5%, worst -91.4%).
• CORE_V: GBP 78.15 (+28.15), 418 of 418 entered, 28.9% win rate (best 957.2%, worst -95.5%).
• MID: GBP 65.76 (+15.76), 336 of 393 entered, 34.6% win rate (best 721.7%, worst -96.2%).
• FRESH: GBP 62.06 (+12.06), 421 of 542 entered, 25.1% win rate (best 1625.9%, worst -99.3%).
• CORE: GBP 54.74 (+4.74), 393 of 437 entered, 28.9% win rate (best 796.2%, worst -98.2%).
• MEDIA_VELO: GBP 46.4 (-3.6), 16 of 16 entered, 31.2% win rate (best 123.3%, worst -91.4%).
• BW_SENTINEL_SOLO: GBP 45.33 (-4.67), 432 of 523 entered, 36.8% win rate (best 2670.0%, worst -92.3%).
• MEDIA_VELOR: GBP 41.76 (-8.24), 16 of 16 entered, 31.2% win rate (best 122.8%, worst -91.4%).
• FRESH_V: GBP 35.68 (-14.32), 657 of 907 entered, 28.6% win rate (best 1390.8%, worst -76.0%).
• ELITE: GBP 29.98 (-20.02), 408 of 435 entered, 9.2% win rate (best 575.4%, worst -94.4%).

These historical replay outcomes are logged continuously. The simulation framework helps isolate trade mechanics before considering future code deployments.

Analytical Limitations and Operational Status

Several parameters within the current research structure remain restricted or unverified. Edge access for real-time wallet graph claims is locked, which prevents public verification of specific cohort entities. The paper model operates on virtual parameters only, utilizing a delayed and redacted public feed. Consequently, transaction results logged in /var/www/memes/api/copy_demo.json do not reflect live market execution. Funding details, operator console endpoints, and live execution scripts, such as /root/Pumphouse/services/pumphouse_exec_mirror.py, are kept confidential and are not exposed. The research parameters outlined in the Pumphouse method serve as analytical boundaries. Further context on system updates is accessible via the Atlas notes and the Pumphouse dashboard. The metadata structure for these notes is mapped according to the Schema.org BlogPosting standard to ensure search index visibility. The parent system and branding belong to the FreedomCore architecture.