Mousecrack – Teaching an LSTM to move a mouse like a human is a skill AI agent for Train an AI model to mimic human mouse behavior for bypassing automation detection or testing system security. Pricing: Free. As of 2026-11-06, KanonAgent records 2 upvotes. First indexed by KanonAgent on 2026-08-07.
Uses an LSTM to model human-like mouse movements for use in anti-bot systems and human interaction research.
2 upvotes
Tracked by Kanon since Aug 7, 2026
Status basis: npm_downloads_7d momentum fell to 1 per 3d from 18 (<= 40% of the prior window)
📈 Timelinewhat changed, and when
- Cooling npm_downloads_7d momentum fell to 1 per 3d from 18 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 1 per 3d from 18 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 7 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Anomaly daily change 10.0 is 4.3 standard deviations from this entity's own prior mean (-0.3±2.4, baseline excludes this point) — unusual, not necessarily adoption
- Reactivated npm_downloads_7d did not move for 7d, then gained 7 in the last 3d
- Accelerating npm_downloads_7d gained 7 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Anomaly daily change 10.0 is 4.3 standard deviations from this entity's own prior mean (-0.3±2.4, baseline excludes this point) — unusual, not necessarily adoption
- Accelerating npm_downloads_7d gained 7 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Anomaly daily change 10.0 is 4.3 standard deviations from this entity's own prior mean (-0.3±2.4, baseline excludes this point) — unusual, not necessarily adoption
- Cooling npm_downloads_7d momentum fell to -1 per 3d from 11 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 0 per 3d from 13 (<= 40% of the prior window)
- Cooling npm_downloads_7d momentum fell to 3 per 3d from 12 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 11 in the last 3d vs 4 in the 3d before (ratio 2.8x, threshold 1.5x)
- Cooling npm_downloads_7d momentum fell to 3 per 3d from 12 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 13 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Cooling npm_downloads_7d momentum fell to -17 per 3d from 13 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 5 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Cooling npm_downloads_7d momentum fell to -8 per 3d from 13 (<= 40% of the prior window)
- Accelerating npm_downloads_7d gained 8 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Reactivated npm_downloads_7d did not move for 7d, then gained 8 in the last 3d
- Accelerating npm_downloads_7d gained 13 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Reactivated npm_downloads_7d did not move for 7d, then gained 13 in the last 3d
- Accelerating npm_downloads_7d gained 13 in the last 3d after a flat 3d baseline (no prior movement to compare a ratio against)
- Reactivated npm_downloads_7d did not move for 7d, then gained 13 in the last 3d
🔎 Known / Unknown
13 of 23 fields unknown
| Machine-callable | — | unknown | — |
| Open source | 1 | inferred | 1 quote(s) |
| Self-hostable | — | unknown | — |
| Bring your own key | — | unknown | — |
| Autonomy level | 2 | inferred | 1 quote(s) |
| Pricing model | — | unknown | — |
| Integrations | claude,codex | inferred | 1 quote(s) |
“Unknown” means we have not verified it — it is not a “no”. Hard filters never treat unknown as false.
🤖 Agent teardown · skill
Job to be doneTrain an AI model to mimic human mouse behavior for bypassing automation detection or testing system security.
AutonomyL2 · tool-calling(evidence: "await move(200, 400);…")
Who it is forB2B
Prerequisitesopen source
Integrationsclaude · codex
PricingFree
Why it matters
Applying LSTMs to simulate human mouse movements represents a cutting-edge approach to evading automated detection, with real-world potential in security and testing applications.
Evidence quotesverbatim, from the product’s own materials
“public GitHub repository (README fetched)”— structural
“await move(200, 400);”— readme
“For Claude Code: /plugin marketplace add puffinsoft/mousecrack”— readme
“npm i -g mousecrack”— readme
“Available as an SDK (for developers) and CLI (for agents).”— readme
Signal source: Show HN
Visit official site →
📛 Official badgefor your site / README
Building Mousecrack? Pick a style above — the embed code updates live. Deep color control via URL params: bg= / fg= / accent= (hex). It links back to this page.
On mobile tap Share for WeChat / RED (Xiaohongshu) / X; on desktop use Copy text and paste into the app.
FAQ
What is Mousecrack?
Uses an LSTM to model human-like mouse movements for use in anti-bot systems and human interaction research.
What does Mousecrack do?
Train an AI model to mimic human mouse behavior for bypassing automation detection or testing system security.
Why does Mousecrack matter?
Applying LSTMs to simulate human mouse movements represents a cutting-edge approach to evading automated detection, with real-world potential in security and testing applications.
How much does Mousecrack cost?
Free
Is Mousecrack free?
Yes — Mousecrack has a free tier. Pricing as stated on its own page: Free
Is Mousecrack open source?
Yes — Mousecrack is open source.
What does Mousecrack integrate with?
claude,codex
How popular is Mousecrack?
As tracked by KanonAgent: 2 upvotes (first indexed 2026-08-07).
What are the best Mousecrack alternatives?
Similar AI agents tracked by KanonAgent: Stealth Venture, archify, open-design, deer-flow, ruflo, career-ops.