LearnSAFE
Bug bounty agent framework for Claude Code, Codex, Gemini, Cursor, Windsurf, Copilot, and OpenClaw — 48 agents, 26 commands, 19 CLI tools, 2 MCP servers, autonomous hunt loops, exploit chain builder.
Overview
Bug bounty agent framework for Claude Code, Codex, Gemini, Cursor, Windsurf, Copilot, and OpenClaw — 48 agents, 26 commands, 19 CLI tools, 2 MCP servers, autonomous hunt loops, exploit chain builder.
be1723764604OBSERVED · 2026-10-13What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: learn description: "Record a platform response and update learning. Usage: /learn <report_id> <status> [--bounty 500] [--vuln-type XSS]" disable-model-invocation: false --- Record platform response: $ARGUMENTS 1. Parse arguments and run: `uv run python3 $CLAUDE_PROJECT_DIR/tools/response_tracker.py log $ARGUMENTS` 2. Also update brain: `uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py log "Report response: $ARGUMENTS"` 3. Sync to global brain: `uv run python3 $CLAUDE_PROJECT_DIR/tools/global_brain.py sync-from-local` 4. Show updated insights: `uv run python3 $CLAUDE_PROJECT_DIR/tools/response_tracker.py insights` ## Top-Tier Learning Loop Convert every platform response into a future hunting rule. - If accepted: record the decisive proof artifact, impact framing, asset type, vuln variant, bounty tier, and why triage agreed. - If duplicate: record the duplicated primitive and which uniqueness signal was missing. - If N/A: record the exact sentence or policy clause that killed it. - If informative: record the missing chain or business impact required to make it payable. - If severity changed: record the evidence that moved it up or down. End with one concrete update: a brain pattern, a never-submit rule, a report wording change, or a target ranking adjustment.
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (1)
Gates applied: no_behavioural_pass, no_license.
be1723764604full audit observations/trust-audit/skill/h-mmer__learn.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-13 | be1723764604 | SAFE | B | 89 | first audit |
Questions
What does the Learn skill do?
Bug bounty agent framework for Claude Code, Codex, Gemini, Cursor, Windsurf, Copilot, and OpenClaw — 48 agents, 26 commands, 19 CLI tools, 2 MCP servers, autonomous hunt loops, exploit chain builder.
Is Learn safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Learn access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (be1723764604), read on 2026-10-13. The repository is watched, and a new audit runs when it changes — this is the first audit.