security: force esbuild ^0.28.1; remove leaked Groq API keys from notebooks (#619)

- Add esbuild ^0.28.1 npm override in explorer/package.json (Dependabot #15,
  GHSA-gv7w-rqvm-qjhr); npm audit now reports 0 vulnerabilities
- Strip hardcoded GROQ_API_KEY values from 6 cookbook notebooks; fallback
  replaced with empty string (secret scanning alerts #1-#6)
  Affected: supply_chain/01, intelligence/01, cybersecurity/01 & 02,
  finance/01, blockchain/02
- CHANGELOG: document both fixes under [Unreleased] ### Security
This commit is contained in:
Mohd Kaif
2026-06-13 13:04:49 +05:30
committed by GitHub
parent c8519470bc
commit 6d9a690bcd
9 changed files with 18 additions and 560 deletions
+4
View File
@@ -108,6 +108,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- **Vite upgraded from 5.x to 6.4.3** — resolves path traversal in optimised-deps `.map` handling (CVE-2026-39365 / GHSA-4w7w-66w2-5vf9) and the esbuild dev-server CORS issue (GHSA-4w7w-66w2-5vf9). Bundled esbuild updated from 0.21.5 → 0.25.12.
- **esbuild forced to 0.28.1+ via npm override** — vite 6.4.3 bundles esbuild 0.25.12 which is vulnerable to missing binary integrity verification in the Deno distribution module (GHSA-gv7w-rqvm-qjhr); added `"esbuild": "^0.28.1"` to `overrides` in `explorer/package.json`. `npm audit` now reports 0 vulnerabilities (Dependabot #15).
- **Leaked Groq API keys removed from cookbook notebooks** — 6 hardcoded `GROQ_API_KEY` values (`gsk_...`) stripped from configuration cells in `supply_chain/01`, `intelligence/01`, `cybersecurity/01`, `cybersecurity/02`, `finance/01`, and `blockchain/02`; fallback replaced with empty string (secret scanning alerts #1#6). Keys were already publicly exposed — rotate them in the Groq console.
---
## [0.5.0] - 2026-05-11
@@ -79,18 +79,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"os.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"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\")\n",
"\n",
"# Configuration constants\n",
"EMBEDDING_DIMENSION = 384\n",
"EMBEDDING_MODEL = \"all-MiniLM-L6-v2\"\n",
"CHUNK_SIZE = 1000\n",
"CHUNK_OVERLAP = 200\n",
"TEMPORAL_GRANULARITY = \"day\"\n"
]
"source": "import os\n\nos.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"\")\n\n# Configuration constants\nEMBEDDING_DIMENSION = 384\nEMBEDDING_MODEL = \"all-MiniLM-L6-v2\"\nCHUNK_SIZE = 1000\nCHUNK_OVERLAP = 200\nTEMPORAL_GRANULARITY = \"day\""
},
{
"cell_type": "markdown",
@@ -923,4 +912,4 @@
},
"nbformat": 4,
"nbformat_minor": 2
}
}
@@ -79,18 +79,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"os.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"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\")\n",
"\n",
"# Configuration constants\n",
"EMBEDDING_DIMENSION = 384\n",
"EMBEDDING_MODEL = \"all-MiniLM-L6-v2\"\n",
"CHUNK_SIZE = 500\n",
"CHUNK_OVERLAP = 50\n",
"TEMPORAL_GRANULARITY = \"minute\"\n"
]
"source": "import os\n\nos.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"\")\n\n# Configuration constants\nEMBEDDING_DIMENSION = 384\nEMBEDDING_MODEL = \"all-MiniLM-L6-v2\"\nCHUNK_SIZE = 500\nCHUNK_OVERLAP = 50\nTEMPORAL_GRANULARITY = \"minute\""
},
{
"cell_type": "markdown",
@@ -838,4 +827,4 @@
},
"nbformat": 4,
"nbformat_minor": 2
}
}
@@ -82,18 +82,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"os.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"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\")\n",
"\n",
"# Configuration constants\n",
"EMBEDDING_DIMENSION = 384\n",
"EMBEDDING_MODEL = \"all-MiniLM-L6-v2\"\n",
"CHUNK_SIZE = 1000\n",
"CHUNK_OVERLAP = 200\n",
"TEMPORAL_GRANULARITY = \"day\"\n"
]
"source": "import os\n\nos.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"\")\n\n# Configuration constants\nEMBEDDING_DIMENSION = 384\nEMBEDDING_MODEL = \"all-MiniLM-L6-v2\"\nCHUNK_SIZE = 1000\nCHUNK_OVERLAP = 200\nTEMPORAL_GRANULARITY = \"day\""
},
{
"cell_type": "markdown",
@@ -915,4 +904,4 @@
},
"nbformat": 4,
"nbformat_minor": 2
}
}
@@ -76,17 +76,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"os.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"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\")\n",
"\n",
"# Configuration constants\n",
"EMBEDDING_DIMENSION = 384\n",
"EMBEDDING_MODEL = \"all-MiniLM-L6-v2\"\n",
"CHUNK_SIZE = 1000\n",
"CHUNK_OVERLAP = 200\n"
]
"source": "import os\n\nos.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"\")\n\n# Configuration constants\nEMBEDDING_DIMENSION = 384\nEMBEDDING_MODEL = \"all-MiniLM-L6-v2\"\nCHUNK_SIZE = 1000\nCHUNK_OVERLAP = 200"
},
{
"cell_type": "markdown",
@@ -726,4 +716,4 @@
},
"nbformat": 4,
"nbformat_minor": 2
}
}
@@ -80,17 +80,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"os.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"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\")\n",
"\n",
"# Configuration constants\n",
"EMBEDDING_DIMENSION = 384\n",
"EMBEDDING_MODEL = \"sentence-transformers/all-MiniLM-L6-v2\"\n",
"CHUNK_SIZE = 1000\n",
"CHUNK_OVERLAP = 200\n"
]
"source": "import os\n\nos.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"\")\n\n# Configuration constants\nEMBEDDING_DIMENSION = 384\nEMBEDDING_MODEL = \"sentence-transformers/all-MiniLM-L6-v2\"\nCHUNK_SIZE = 1000\nCHUNK_OVERLAP = 200"
},
{
"cell_type": "markdown",
@@ -717,4 +707,4 @@
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}
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@@ -81,17 +81,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"os.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"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\")\n",
"\n",
"# Configuration constants\n",
"EMBEDDING_DIMENSION = 384\n",
"EMBEDDING_MODEL = \"sentence-transformers/all-MiniLM-L6-v2\"\n",
"CHUNK_SIZE = 1000\n",
"CHUNK_OVERLAP = 200\n"
]
"source": "import os\n\nos.environ[\"GROQ_API_KEY\"] = os.getenv(\"GROQ_API_KEY\", \"\")\n\n# Configuration constants\nEMBEDDING_DIMENSION = 384\nEMBEDDING_MODEL = \"sentence-transformers/all-MiniLM-L6-v2\"\nCHUNK_SIZE = 1000\nCHUNK_OVERLAP = 200"
},
{
"cell_type": "markdown",
@@ -660,4 +650,4 @@
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"nbformat_minor": 2
}
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-484
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+2 -1
View File
@@ -52,6 +52,7 @@
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}
}