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amber-hunter
Universal AI memory backend for Huper琥珀 — local E2E encrypted memory capture and recall with optional cloud sync
A legitimate, well-documented local AI memory backend with strong E2E encryption. Minor documented fallbacks for headless Linux do not constitute hidden malicious behavior.
技能名称amber-hunter
分析耗时87.9s
引擎pi
✓
可以安装
Consider pinning dependency versions in requirements.txt. For headless Linux, warn users about the config.json plaintext fallback for master_password. Otherwise safe to use.

安全发现 5 项

严重性 安全发现 位置
中危
Unpinned Python dependencies
All packages in requirements.txt use >= version specifiers without upper bounds. This allows dependency confusion attacks and supply chain injection via package updates.
sentence-transformers>=2.2.0
numpy>=1.24.0
→ Pin exact versions: sentence-transformers==2.7.0, numpy==1.26.4, etc.
 requirements.txt:1
低危
Linux headless stores master_password in plaintext
On headless Linux (VPS), master_password falls back to config.json in plaintext. While documented, this means the encryption key is stored unencrypted on disk.
_linux_config_set(account, password)
→ Warn users explicitly at install time; consider requiring user acknowledgment
 core/keychain.py:164
低危
master_password also written to config.json as fallback on all platforms
set_master_password_handler writes master_password to config.json even when OS keychain succeeds on macOS/Windows. The Keychain is primary but config.json serves as an unnecessary backup copy.
cfg['master_password'] = password_in.password
→ Only write to config.json when OS keychain fails, not as a parallel backup
 amber_hunter.py:2063
提示
Reads API keys from OpenClaw config
core/llm.py auto-detects LLM API keys from ~/.openclaw/openclaw.json. This reads third-party credentials to auto-configure providers.
providers = openclaw_config.get('models', {}).get('providers', {})
→ This is documented and intentional — the skill needs LLM keys to power its AI features
 core/llm.py:524
提示
Session file access for proactive capture
core/session.py and proactive scripts read OpenClaw/Claude session .jsonl files to build conversation context. This is declared in SKILL.md as the core proactive capture feature.
read_session_messages() reads .jsonl session files
→ No action needed — this is the stated purpose of the skill
 core/session.py:60
资源类型声明权限推断权限状态证据
文件系统 READ READ ✓ 一致 SKILL.md allowed-tools maps Read→filesystem:READ; code reads ~/.amber-hunter/, ~…
命令执行 WRITE WRITE ✓ 一致 install.sh/freeze.sh are shell scripts; LLM providers use subprocess.run with cu…
网络访问 READ READ ✓ 一致 SKILL.md declares huper.org cloud sync; core/llm.py makes API calls to minimaxi.…
数据库 READ WRITE ✓ 一致 SKILL.md: Memory write via /ingest is a core capability; code writes to SQLite a…
环境变量 NONE READ ✓ 一致 core/llm.py:361 reads MINIMAX_API_KEY env var; core/keychain.py:115 reads AMBER_…
8 项发现
🔗
中危 外部 URL 外部 URL
https://huper.org
CHANGELOG.md:275
🔗
中危 外部 URL 外部 URL
https://huper.org/dashboard
README.md:33
🔗
中危 外部 URL 外部 URL
https://huper.org/api
README.md:43
🔗
中危 外部 URL 外部 URL
https://huper.org/api/ingest
SKILL.md:68
🔗
中危 外部 URL 外部 URL
http://127.0.0.1:18998
amber_hunter.py:619
🔗
中危 外部 URL 外部 URL
https://api.minimaxi.com/anthropic/v1/messages
core/llm.py:130
🔗
中危 外部 URL 外部 URL
https://api.groq.com/openai/v1/chat/completions
core/llm.py:624
🔗
中危 外部 URL 外部 URL
https://api.minimaxi.com/anthropic
core/llm.py:692

目录结构

29 文件 · 240.0 KB · 6548 行
Python 14f · 4387L Markdown 7f · 1057L JavaScript 3f · 606L Shell 3f · 325L TypeScript 1f · 161L Text 1f · 12L
├─ ▾ 📁 core
│ ├─ 🐍 __init__.py Python 5L · 312 B
│ ├─ 🐍 crypto.py Python 60L · 1.7 KB
│ ├─ 🐍 db.py Python 404L · 13.5 KB
│ ├─ 🐍 keychain.py Python 284L · 9.3 KB
│ ├─ 🐍 llm.py Python 735L · 23.7 KB
│ ├─ 🐍 models.py Python 46L · 1009 B
│ └─ 🐍 session.py Python 450L · 16.4 KB
├─ ▾ 📁 proactive
│ ├─ ▾ 📁 hooks
│ │ └─ ▾ 📁 openclaw
│ │ ├─ 📜 handler.js JavaScript 152L · 5.0 KB
│ │ ├─ 📜 handler.ts TypeScript 161L · 5.6 KB
│ │ └─ 📝 HOOK.md Markdown 39L · 1.2 KB
│ ├─ ▾ 📁 scripts
│ │ └─ 📜 proactive-check.js JavaScript 284L · 10.0 KB
│ ├─ 📜 proactive-check.js JavaScript 170L · 6.1 KB
│ └─ 📝 README.md Markdown 88L · 2.1 KB
├─ ▾ 📁 tests
│ ├─ ▾ 📁 test_api
│ │ ├─ 🐍 __init__.py Python 0 B
│ │ ├─ 🐍 test_recall.py Python 104L · 3.8 KB
│ │ └─ 🐍 test_status.py Python 34L · 1.0 KB
│ ├─ 🐍 __init__.py Python 0 B
│ ├─ 🐍 conftest.py Python 46L · 1.1 KB
│ └─ 🐍 test_crypto.py Python 50L · 1.7 KB
├─ 🐍 amber_hunter.py Python 2169L · 84.4 KB
├─ 📝 CHANGELOG.md Markdown 287L · 16.0 KB
├─ 📝 CLAUDE.md Markdown 28L · 1.0 KB
├─ 🔧 freeze.sh Shell 59L · 1.7 KB
├─ 🔧 install.sh Shell 188L · 7.5 KB
├─ 📝 README.md Markdown 261L · 8.8 KB
├─ 📝 RELEASE_CHECKLIST.md Markdown 46L · 1.5 KB
├─ 🔧 release.sh Shell 78L · 2.9 KB
├─ 📄 requirements.txt Text 12L · 202 B
└─ 📝 SKILL.md Markdown 308L · 12.3 KB

依赖分析 8 项

包名版本来源已知漏洞备注
fastapi 0.115.0 pip 否 Lower bound only, no upper cap
uvicorn 0.30.0 pip 否 Lower bound only
pydantic 2.9.0 pip 否 Lower bound only
cryptography 43.0.0 pip 否 Lower bound only
httpx 0.27.0 pip 否 Lower bound only
sentence-transformers >=2.2.0 pip 否 Version not pinned, ~90MB ML model download at install time
numpy >=1.24.0 pip 否 Version not pinned
pytest >=8.0.0 pip 否 Test only, not shipped

安全亮点

✓ E2E AES-256-GCM encryption with PBKDF2-HMAC-SHA256 key derivation (100k iterations)
✓ master_password stored in OS Keychain (macOS security, Linux secret-tool, Windows cmdkey)
✓ Local service restricted to localhost:18998 — no remote exposure
✓ Cloud sync payload is E2E encrypted before upload; huper.org never sees plaintext
✓ No base64/eval obfuscation or dynamic code execution patterns
✓ No reverse shell, C2 infrastructure, or data exfiltration to unexpected hosts
✓ All external network IOCs map to declared API endpoints (huper.org, LLM providers)
✓ Review queue requires user approval before memories become permanent
✓ SKILL.md is comprehensive and accurately describes capabilities
✓ Comprehensive CORS restrictions to declared origins only