{ "llm": { "conf": 0.015823761, "grade": "benign", "model": "Qwen/Qwen3.8-27B", "outcome": "benign", "interpretation": "legitimate ML serialization library" }, "ml": { "v": "7", "eng": "2.8.0-beta.0", "lvl": -1, "conf": 0, "mods": [ { "cls": 0, "raw": 0.023617556, "rte": "az", "prob": 0.023617556 } ], "prob": 0.023617556, "skip": [ { "rte": "az/whl", "why": "unavailable" }, { "rte": "az/whl", "why": "unavailable" } ], "files": [ { "id": 0, "lvl": -1, "conf": 0, "prob": 0.02361755631864071, "type": "whl" }, { "id": 2, "lvl": -1, "conf": 0, "prob": 0.000007212162017822266, "type": "python" }, { "id": 3, "lvl": -1, "conf": 0, "prob": 0.0000075598559305944946, "type": "python" }, { "id": 4, "lvl": -1, "conf": 0, "prob": 0.000008742014870222192, "type": "python" }, { "id": 5, "lvl": -1, "conf": 0, "prob": 0.000007957220077514648, "type": "python" }, { "id": 6, "lvl": -1, "conf": 0, "prob": 0.000008235375389631372, "type": "python" }, { "id": 7, "lvl": -1, "conf": 0, "prob": 0.0000080565614553052, "type": "python" }, { "id": 8, "lvl": -1, "conf": 0, "prob": 0.000008801619514997583, "type": "python" }, { "id": 9, "lvl": -1, "conf": 0, "prob": 0.000007838010787963867, "type": "python" }, { "id": 11, "lvl": -1, "conf": 0, "prob": 0.0000068247318267822266, "type": "python" }, { "id": 12, "lvl": -1, "conf": 0, "prob": 0.00000815590192360105, "type": "python" }, { "id": 13, "lvl": -1, "conf": 0, "prob": 0.00000864267349243164, "type": "python" }, { "id": 15, "lvl": -1, "conf": 0, "prob": 0.000009834766387939453, "type": "python" }, { "id": 18, "lvl": -1, "conf": 0, "prob": 0.000007063150405883789, "type": "registry" } ], "version": "v18.18", "analyzed_at": "2026-08-18T02:38:22Z" }, "path": "skeights-0.4.0-py3-none-any.whl", "raw": { "files": [ { "id": 0, "ctx": [ { "b": "p!H([6Awak2MK\u00268lqPm[GWQhc002T[000Yk0047QwOC^\u003cBAo9xuUKy(ByexcAcVqZo?@RX42aBoG{z4\u00265O\u0026UTblnf:.4JB\u0026Wc\u0026[6g]REs{/ROxprl0$tt\u0026ZlbPD6cPi[g$/0dO693@FF/eD9dVw}9Xs}XTQvOE\u003c", "n": [ { "c": 2, "d": "Python wheel archive basename", "i": "metadata/file/extension/identity::python-wheel-basename", "o": 0, "z": 31, "cf": 0.95 } ], "ln": 0 } ], "mol": "H₂(Db₂F)", "sha": "73eb0019869313035a41de0905dac335f23748b2d6a025b5683f89b642d37b83", "path": "skeights-0.4.0-py3-none-any.whl", "risk": 4, "size": 26896, "type": "whl", "facts": { "metrics": { "whl": { "native_extension_count": 0.0 }, "file": { "size": 26896.0, "entropy": 7.93, "size_bytes": 26896.0 }, "binary": { "overall_entropy": 7.93, "peak_region_bytes": 25600.0, "peak_region_entropy": 7.84 }, "archive": { "file_count": 20.0, "member_count": 20.0, "script_count": 15.0, "zip_bomb_ratio": 5.68, "directory_count": 0.0, "executable_count": 0.0, "extra_field_size": 0.0, "noise_file_count": 0.0, "total_compressed": 24524.0, "compression.ratio": 0.26, "hidden_file_count": 0.0, "total_uncompressed": 95164.0, "crc_collision_count": 0.0, "entry_comment_count": 0.0, "max_filename_length": 41.0, "rtlo_filename_count": 0.0, "format.regular_count": 20.0, "nested_archive_count": 0.0, "path_traversal_count": 0.0, "symlink_escape_count": 0.0, "security.setgid_count": 0.0, "security.setuid_count": 0.0, "security.sticky_count": 0.0, "double_extension_count": 0.0, "duplicate_member_count": 0.0, "security.symlink_count": 0.0, "unicode_filename_count": 0.0, "homoglyph_filename_count": 0.0, "security.encrypted_count": 0.0, "timing.mtime_unique_count": 1.0, "timing.mtime_unique_ratio": 0.05, "misplaced_executable_count": 0.0, "timing.mtime_dominant_count": 20.0, "timing.mtime_spread_seconds": 0.0, "timing.sentinel_mtime_count": 0.0, "security.world_writable_count": 0.0, "timing.mtime_dominant_fraction": 1.0, "compression.method_counts.deflate": 20.0 } } }, "ident": { "name": { "value": "skeights", "source": "whl.distribution", "verified": false }, "trust": "unsigned", "emails": [ "engineering@gigaton.co" ], "authors": [ { "name": "Gigaton", "role": "author", "email": "engineering@gigaton.co", "source": "whl.author" } ], "version": { "value": "0.4.0", "source": "whl.version", "verified": false } }, "traits": [ { "id": "metadata/package/manifest/ecosystem::pkginfo-version-field", "conf": 0.9, "crit": 1, "desc": "Declares Python package version", "from": [ { "file": 16 } ] }, { "id": "metadata/package/manifest/ecosystem::pkginfo-license-file", "conf": 0.9, "crit": 1, "desc": "Declares Python package license file", "from": [ { "file": 16 } ] }, { "id": "micro-behaviors/os/api-resolution/dynamic::py-importlib-import-module", "conf": 0.6, "crit": 3, "desc": "Dynamically imports a Python module", "from": [ { "file": 13 } ] }, { "id": "metadata/package/manifest/ecosystem::pkginfo-markdown-description", "conf": 0.9, "crit": 1, "desc": "Declares Markdown package description", "from": [ { "file": 16 } ] }, { "id": "metadata/package/manifest/ecosystem::pkginfo-core-metadata", "conf": 1.0, "crit": 1, "desc": "Declares Python Core Metadata version", "from": [ { "file": 16 } ] }, { "id": "metadata/package/manifest/ecosystem::pypi-runtime-metadata", "conf": 0.94, "crit": 2, "desc": "PyPI package declares Python and dependencies", "from": [ { "off": 898, "file": 16, "line": 21 } ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--arange", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (arange)", "from": [ { "file": 8 } ] }, { "id": "micro-behaviors/fs/file/write/direct::py-pathlib-write-call", "conf": 0.9, "crit": 3, "desc": "pathlib write_text/write_bytes call", "from": [ { "file": 6 } ] }, { "id": "micro-behaviors/data/manipulation::numeric-computation-library", "conf": 0.95, "crit": 3, "desc": "Module built on the numeric Python stack", "from": [ { "file": 2 } ], "spans": [ [ 5032, 8 ], [ 14143, 9 ] ] }, { "id": "metadata/package/manifest/ecosystem::pkginfo-requires-dist", "conf": 0.9, "crit": 1, "desc": "Declares Python runtime dependencies", "from": [ { "file": 16 } ] }, { "id": "metadata/package/manifest/ecosystem::pkginfo-name-field", "conf": 0.9, "crit": 1, "desc": "Declares Python package name", "from": [ { "file": 16 } ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations", "conf": 0.85, "crit": 3, "desc": "Dense NumPy array construction and reduction", "from": [ { "file": 2 } ], "spans": [ [ 5032, 8 ], [ 14143, 9 ] ] }, { "id": "metadata/package/manifest/ecosystem::pkginfo-license-expression", "conf": 0.9, "crit": 1, "desc": "Declares Python license expression", "from": [ { "file": 16 } ] }, { "id": "micro-behaviors/data/manipulation::numpy-import", "conf": 0.9, "crit": 3, "desc": "Imports the NumPy array library", "from": [ { "file": 2 } ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--array", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (array)", "from": [ { "file": 8 } ] }, { "id": "metadata/package/manifest/ecosystem::pypi-basic-metadata", "conf": 0.95, "crit": 2, "desc": "PyPI package declares name, version, summary", "from": [ { "off": 37, "file": 16, "line": 3 } ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--ndarray", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (ndarray)", "from": [ { "file": 2 } ] }, { "id": "metadata/package/manifest/ecosystem::pypi-license-metadata", "conf": 0.94, "crit": 2, "desc": "PyPI package declares license information", "from": [ { "off": 325, "file": 16, "line": 9 } ] }, { "id": "micro-behaviors/data/serialize/json::json-loads-call", "conf": 0.9, "crit": 3, "desc": "Parses JSON data with Python", "from": [ { "file": 6 } ] }, { "id": "metadata/package/manifest/ecosystem::pkginfo-summary-field", "conf": 0.9, "crit": 1, "desc": "Declares Python package summary", "from": [ { "file": 16 } ] }, { "id": "metadata/package/manifest/ecosystem::pkginfo-requires-python", "conf": 0.9, "crit": 1, "desc": "Declares supported Python versions", "from": [ { "file": 16 } ] } ] }, { "ctx": [ { "b": "a%Fi#z/Pziwnca7vru0)azbLjaAIamx\u003c\u003e*(DtdnfazbtfBy!#9B7n{1x(\u003e}ywNPQ%az2Rox(dp2z/P[K3jogjv@Dj6z/YGhayMy8x([Ddwft@ey?m3}zxJIiBzkP2Bz(gxx(n3hiTNCYk{e=#pFJG.vp\u003c6[wnbK}aA7\u003cmxNaMdA=tDcvqPN$wPz\u0026mvqYP#w[=vewN({8v{%gZAV/BBvru5/eG^t4w]7)$ay]g@BrCHlaz#ssAcSNmA=LPlB08(PwOC^\u003cBAn#Qw[=vewN(](A=LPlB14C6ra]#!aAg+6AV!\u003e2zxJz1aAH$mwN({9zY\u003cafw[u6}zGx-pB08$Qn(FIXaA?EcaARpdaARKveO]0wwO.Ymw{503i:^2AwOC^\u003cBAo6QvrMi\u0026atj\u0026#w{503i:^2AwOC^\u003cBAo6Jz^^f:azb+lv@#B6zGvAqa%Fir3tar%z6ig)w{5irA+eP+azCXiz/P}xvqY$3Byxo9z/fR63tar%z6i}CAa%i5azCXiz/P}xl2H@P3tBu@z/P}xzGP/nC{3Kpaz#c9w].*baAIsmwNPQ%e[emgwGUY7AbP=savoHTwKQVZx(dp2z/Mg%A=k!qB8bP6vrclrAa%o5y?W=#azCXiz/P}xp?:(Wy?W=#3jpx=z/3RryH}i)xMOqFuUA\u003e=wnC*$azCXiz/P}xmrrM+zddK8A.6RRwb", "n": [ { "c": 3, "d": "Module built on the numeric Python stack", "i": "micro-behaviors/data/manipulation::numeric-computation-library", "o": 420, "z": 5, "cf": 0.95 }, { "c": 2, "d": "File uses a Python artifact extension", "i": "metadata/file/extension/identity::py", "o": 0, "z": 8, "cf": 1.0 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-1", "o": 277, "z": 3, "cf": 0.8 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-2", "o": 148, "z": 3, "cf": 0.8 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-5", "o": 17, "z": 3, "cf": 0.8 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-7", "o": 228, "z": 4, "cf": 0.8 }, { "c": 1, "d": "Python import-from statement", "i": "micro-behaviors/data/source/language::python-import-from-statement", "o": 353, "z": 34, "cf": 0.8 }, { "c": 1, "d": "Saves a configured shortcut", "i": "micro-behaviors/os/wsh/file::shortcut-save", "o": 306, "z": 5, "cf": 0.7 } ], "ln": 0, "col": 1, "line": 1 }, { "b": "A+e\u0026%CQ%$Hz/PY6BuKkOA=2lbdjCPDarR^HarR!EwPS6nzxK1xvru5/3lQDlazbLjazth3wnC*$azCZouUr}(uUA\u003e=wnC*$B0@E#3lQDlarR^HazCBgxKL^?y?mStxKL^?y?mVowPI%czddK8AW:3RarR^HarR^HarR^HA+funA=91kvqYQ(wPxzkz!%l3v@#70Byxo5", "n": [ { "c": 2, "d": "Contains an iteration loop", "i": "micro-behaviors/data/control-flow/analysis::iteration-loop-pattern", "o": 2043, "z": 16, "cf": 0.5 } ], "ln": 1995, "col": 67, "line": 64 }, { "b": "Ab]J4x)qVYB98BBjS\u003e{)ed9HxarUomA=2lbiV@G=AV/-Lph+2YauZ\u0026xz/fbq3mN8Hj%jxIv@${@BAe]PzG4jCwmoI0vr(ct3lQDlar\u00260NqE%uXA=U@rwO=SmwQ5rqvpKy4zGP/nC{3KoA::lmazbUjz6imfw[=vewN(]{B98bkvruBde*qF-3lQDlazCBgx(!0aB97\u0026dv}v61B98bkvruBdefE=6AaJ\u003c1zE\u003emT3lQDlarR^HayPqhvr(]Pay\u003e", "n": [ { "c": 3, "d": "Dense NumPy array construction and reduction", "i": "micro-behaviors/data/manipulation::numpy-array-operations", "o": 2961, "z": 10, "cf": 0.85 } ], "ln": 2897, "col": 5, "line": 94 }, { "b": "B-qqrA=+(6aAR)FwPGEF3lQDlarR^HasNT8arR^HA+frmy\u0026?YXwnbK}txs[befF?He]CidA=LPlt{8oMDWMkzarR!sz/M$eBAzKCx(k52q+G!Mk#HD+k#HPDsZKD]r8MS", "n": [ { "c": 1, "d": "Result field or assignment key", "i": "micro-behaviors/data/serialize/envelope::result-assignment-key", "o": 3891, "z": 7, "cf": 0.4 } ], "ln": 3859, "col": 31, "line": 116 }, { "b": "w*hOvA+e\u0026%CZT{EBAzLKb3=rOaz#cJvrk\u003c$A::kwxjVf[BAzKKwPI%czddK8AX5twBAzKLdgdguarUYoBAIRwaAz4mB.(db3jprPw/$D3wPI%iA+eP?B98bkvruBduTW%", "n": [ { "c": 1, "d": "Python getattr dynamic attribute lookup", "i": "micro-behaviors/os/api-resolution/dynamic::python-getattr-call", "o": 4052, "z": 7, "cf": 0.75 } ], "ln": 4020, "col": 20, "line": 122 }, { "b": "yH}=ljS[tXDVj1pw[=HrDTR2rA^YbsarR^HarR^Hx\u003ewG6wQbzjzxJwdA::lmiTM#LarR^HarR^HarU-pByxokAWUHuBzkP2Bz(gJayPwlAX5twA=LPlB6AA\u003eD0I\u003ca", "n": [ { "c": 1, "d": "Python in-membership check", "i": "micro-behaviors/data/control-flow/membership::in-membership-check", "o": 5022, "z": 17, "cf": 0.3 } ], "ln": 4990, "col": 9, "line": 151 } ], "depth": 1, "facts": { "imp": [ [ "", "TreeHandler" ], [ "", "TTRHandler" ], [ "", "MLPHandler" ], [ "", "GPHandler" ], [ "", "HGBHandler" ], [ "", "LGBMHandler" ], [ "", "XGBHandler" ], [ "", "isinstance" ], [ "", "estimator.named_steps.items" ], [ "", "state.update" ], [ "", "collect_fitted_state" ], [ "", "get_handlers" ], [ "", "handler.handles" ], [ "", "handler.collect_state" ], [ "", "isinstance" ], [ "", "estimator.named_steps.items" ], [ "", "restore_fitted_state" ], [ "", "get_handlers" ], [ "", "handler.handles" ], [ "", "handler.restore_state" ], [ "", "isinstance" ], [ "", "estimator.named_steps.items" ], [ "", "arrays.update" ], [ "", "arrays_from_estimator" ], [ "", "get_handlers" ], [ "", "handler.handles" ], [ "", "handler.extract_arrays" ], [ "", "any" ], [ "", "hasattr" ], [ "", "NotImplementedError" ], [ "", "type" ], [ "", "hasattr" ], [ "", "np.asarray" ], [ "", "getattr" ], [ "", "isinstance" ], [ "", "estimator.named_steps.items" ], [ "", "restore_estimator_arrays" ], [ "", "get_handlers" ], [ "", "handler.handles" ], [ "", "handler.restore_arrays" ], [ "", "setattr" ], [ "", "Any" ], [ "", "BaseEstimator" ], [ "", "EstimatorHandler" ], [ "", "GPHandler" ], [ "", "HGBHandler" ], [ "", "LGBMHandler" ], [ "", "MLPHandler" ], [ "", "Pipeline" ], [ "", "SKLEARN_ARRAY_ATTRS" ], [ "", "TTRHandler" ], [ "", "TreeHandler" ], [ "", "XGBHandler" ], [ "", "numpy" ], [ "", "skeights._gp" ], [ "", "skeights._handler" ], [ "", "skeights._hgb" ], [ "", "skeights._lgbm" ], [ "", "skeights._mlp" ], [ "", "skeights._trees" ], [ "", "skeights._ttr" ], [ "", "skeights._utils" ], [ "", "skeights._xgb" ], [ "", "sklearn.base" ], [ "", "sklearn.pipeline" ], [ "", "typing" ] ], "mbr": [ "arrays.update", "estimator.named_steps", "estimator.named_steps.items", "handler.collect_state", "handler.extract_arrays", "handler.handles", "handler.restore_arrays", "handler.restore_state", "np.asarray", "np.ndarray", "state.update", "type().__name__" ], "tgt": [ "GPHandler", "HGBHandler", "LGBMHandler", "MLPHandler", "NotImplementedError", "TTRHandler", "TreeHandler", "XGBHandler", "_arrays_from_estimator", "_collect_fitted_state", "_get_handlers", "_restore_estimator_arrays", "_restore_fitted_state", "any", "arrays.update", "estimator.named_steps.items", "getattr", "handler.collect_state", "handler.extract_arrays", "handler.handles", "handler.restore_arrays", "handler.restore_state", "hasattr", "isinstance", "np.asarray", "setattr", "state.update", "type" ], "funcs": [ [ "_get_handlers", 631 ], [ "_collect_fitted_state", 1423 ], [ "_restore_fitted_state", 2210 ], [ "_arrays_from_estimator", 2835 ], [ "_restore_estimator_arrays", 4098 ] ], "metrics": { "ast": { "op.bor": 2.0, "max_depth": 14.0, "bind_count": 9.0, "call_count": 41.0, "node_count": 1153.0, "member_count": 12.0, "op_density.bor": 0.0, "identifier_count": 70.0, "member_depth_max": 3.0, "string_literal_count": 22.0, "array_literal_max_length": 7.0 }, "file": { "size": 5090.0, "entropy": 4.61, "size_bytes": 5090.0 }, "text": { "space_count": 1048.0, "total_lines": 153.0, "char_entropy": 4.61, "unique_chars": 68.0, "string_density": 0.14, "ascii_art_lines": 2.0, "avg_line_length": 32.27, "max_line_length": 88.0, "empty_line_ratio": 0.19, "last_line_length": 49.0, "whitespace_ratio": 0.24, "most_common_ratio": 0.08, "identifier_density": 1.77, "line_length_stddev": 24.43, "normalized_string_count": 1.78, "repeated_char_sequences": 27.0, "suspicious_string_ratio": 0.05, "most_common_char_is_null": 0.0, "max_inline_whitespace_run": 1.0, "most_common_char_codepoint": 116.0, "normalized_unique_identifiers": 9.65 }, "binds": { "count": 9.0 }, "calls": { "count": 41.0 }, "binary": { "overall_entropy": 4.61, "peak_region_bytes": 4096.0, "peak_region_entropy": 4.83 }, "source": { "function_count": 5.0 }, "imports": { "count": 25.0, "stdlib_count": 1.0, "stdlib_ratio": 0.04, "unique_modules": 25.0, "aliased_imports": 2.0, "third_party_count": 24.0, "third_party_ratio": 0.96 }, "members": { "count": 12.0 }, "strings": { "total": 22.0, "avg_length": 44.64, "max_length": 349.0, "avg_entropy": 3.81, "empty_count": 4.0, "total_bytes": 982.0, "entropy_stddev": 0.38, "shell_command_strings": 1.0 }, "comments": { "chars": 304.0, "lines": 5.0, "total": 5.0, "to_code_ratio": 0.03 }, "functions": { "count": 5.0, "avg_params": 2.6, "max_params": 4.0, "length_stddev": 5.82, "avg_name_length": 20.4, "no_params_count": 1.0, "avg_length_lines": 23.6, "max_length_lines": 32.0, "min_length_lines": 16.0, "avg_param_name_length": 7.85, "density_per_100_lines": 3.27, "code_in_functions_ratio": 0.77 }, "identifiers": { "count": 70.0, "total": 271.0, "avg_length": 8.81, "max_length": 25.0, "min_length": 2.0, "avg_entropy": 2.53, "reuse_ratio": 0.26, "unique_count": 70.0, "length_stddev": 5.18, "high_entropy_count": 1.0, "high_entropy_ratio": 0.01, "all_lowercase_ratio": 0.8, "all_uppercase_ratio": 0.03, "double_underscore_count": 1.0, "underscore_prefix_count": 16.0 } } }, "id": 2, "mol": "H(Db)", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_core.py", "pid": 0, "risk": 1, "sha": "a1164545bbfce9dd25fc39eefbd99eeab8def59378aebfbd3d17be1d7129ec3c", "size": 5090, "traits": [ { "id": "micro-behaviors/data/manipulation::numpy-import", "conf": 0.9, "crit": 3, "desc": "Imports the NumPy array library", "spans": [ [ 420, 5 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--ndarray", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (ndarray)", "spans": [ [ 2961, 0 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations", "conf": 0.85, "crit": 3, "desc": "Dense NumPy array construction and reduction", "spans": [ [ 2961, 10 ] ] }, { "id": "micro-behaviors/data/manipulation::numeric-computation-library", "conf": 0.95, "crit": 3, "desc": "Module built on the numeric Python stack", "spans": [ [ 420, 5 ], [ 2961, 10 ] ] } ], "type": "python" }, { "ctx": [ { "b": "a%Fj3vrDTjx\u003c\u003e)4p\u0026ZF:wPI]nwPI%czddK8AV/BmA+O@#x)Kifx(v(ic}v9iefECVlN:Sia%Ev3w].*baywF/B-.+DwNw^!x(d*cA=-BjzF\u003cxmvruj4zGuc(w].*baAR)Fx(mMax(d*cA=-A\u0026zG#M@x(d*cA=-BwB.#8yayPslzG2}{A=k!qB8bP6vrclrvQTs?azCXiz/P}xlsB}DmrrM+zddK8ATDA0z/3RryIWM\u003cA=9HxvrDTjx\u003c\u003e)^Ab](bwPI]nx(d*cA=-AL3lQDlav/\u003c.B8#57zCUv(v}x.5lU{gLB7]l2wPxsearR^Hm}3KYB7]62", "n": [ { "c": 3, "d": "Module built on the numeric Python stack", "i": "micro-behaviors/data/manipulation::numeric-computation-library", "o": 127, "z": 5, "cf": 0.95 }, { "c": 2, "d": "File uses a Python artifact extension", "i": "metadata/file/extension/identity::py", "o": 0, "z": 6, "cf": 1.0 }, { "c": 1, "d": "Python import-from statement", "i": "micro-behaviors/data/source/language::python-import-from-statement", "o": 60, "z": 34, "cf": 0.8 } ], "ln": 0, "col": 1, "line": 1 }, { "b": "A=LPlB0}wrarR!rB98bkvruBdiV{:$B7E^YBzkP2Bz(gJaAhvjw[=GJaAITB3mN8Hj%jxIv@${@BAe]PzG4jCwmoI0vr(ct3lQDlar\u00260Nmr\u0026]{vpKy4vrcx%D2\u003e9uA=k!qviw6plM/\u0026DB7FY\u0026B98bkvruBduMZ+ax(mv1C{2QNqy#Z0yH[}Ea%FirarR^Hw].*baAIsfx\u003eIa3B1Q*xBzkMjazCXiz/P}xq+G!Mk#HD+k#HPDsZKD]r8MTqvrh", "n": [ { "c": 3, "d": "Dense NumPy array construction and reduction", "i": "micro-behaviors/data/manipulation::numpy-array-operations", "o": 492, "z": 10, "cf": 0.85 } ], "ln": 428, "col": 30, "line": 18 }, { "b": "r8=:]3jm)#arU9kA::lmiV}%Ev@${@BAe]PzG4jCwmoI0vr(c3jS]913lQDlazbLjayPwlAV/7layw5uoHRlBpg3p+qBaC)k#Z/Yq-UmdarR^HarR!vw/$+}B76fjAWUHuBzkP2Bz(gJayPwlAW:3RarR^HarR^HarR^Hvrcx%D2)h4b71oHwObU3Es2yABAh^Nt{8oMzG4jpB769fvr\u003cnlwPRv5BAe^vB98bkvruBdefFwyBAe/V3lQDlaAz4nB-Ivxvrcx%D2\u003cr13s)ZWayxe2B98tvwNw[PB7FY\u0026B98bkvrq", "n": [ { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-5", "o": 696, "z": 3, "cf": 0.8 }, { "c": 1, "d": "Python getattr dynamic attribute lookup", "i": "micro-behaviors/os/api-resolution/dynamic::python-getattr-call", "o": 818, "z": 7, "cf": 0.75 } ], "ln": 647, "col": 72, "line": 22 }, { "b": "yH}=ljS[tXDVj1pw[=HrDTR2rA^YbsarR^HarR^Hx\u003ewG6wQbzjzxJwdA::lmiTM#LarR^HarR^HarU-pByxokAWUHuBzkP2Bz(gJayPwlAX5twA=LPlB6AA\u003eD0I\u003ca3jpoVvrlGjm]h-+zu", "n": [ { "c": 1, "d": "Python in-membership check", "i": "micro-behaviors/data/control-flow/membership::in-membership-check", "o": 1201, "z": 17, "cf": 0.3 } ], "ln": 1169, "col": 9, "line": 40 }, { "b": "AaJqZarR^HarR^HarR^HarR^HdgdguarR^HarUliB7ExtarR^HarR^HarR^HvrlH3A=-BrB7]JkByx5%wHIbhBzkP2Bz(gJav/\u003c.B8#57zCUv(v}x.5lU{gLB7]l2wPxjbarR^HarR^HarR^Hx\u003ewG3vrk\u003e0BAe^vB98bkvruBdefDcOuT)[XB8$]luM{{W3lQDlarR^HarR^HarR^HaAITkBy!V*b71oHwObU3EqSz4y*?yawPIi5t{8o", "n": [ { "c": 2, "d": "Checks condition using Python assert", "i": "micro-behaviors/data/control-flow/assert::python-assert-statement", "o": 2146, "z": 55, "cf": 0.95 } ], "ln": 2098, "col": 61, "line": 62 }, { "b": "arR!vw/$J7BAeHrzxHtKuWl12A:-W1uU%v.zxZROb42R5BAg/7zEmEbwfJDBvqYP#C42htzE^D#au.\u003egfGGK-arR^HarR^HarR^HarR^HarR^HarR!FwPRv5BAe^vB98bkvruBdefFwyBAe]PC42htx(){6c[cOLarR^HarR^HarR^HarR^HarR^", "n": [ { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-2", "o": 6099, "z": 3, "cf": 0.8 } ], "ln": 6051, "col": 18, "line": 157 } ], "depth": 1, "facts": { "imp": [ [ "", "hasattr" ], [ "", "np.asarray" ], [ "", "getattr" ], [ "", "setattr" ], [ "", "isinstance" ], [ "", "hasattr" ], [ "", "isinstance" ], [ "", "hasattr" ], [ "", "serialize_kernel" ], [ "", "isinstance" ], [ "", "hasattr" ], [ "", "hasattr" ], [ "", "hasattr" ], [ "", "serialize_kernel" ], [ "", "hasattr" ], [ "", "isinstance" ], [ "", "deserialize_kernel" ], [ "", "isinstance" ], [ "", "hasattr" ], [ "", "deserialize_kernel" ], [ "", "isinstance" ], [ "", "hasattr" ], [ "", "key" ], [ "", "np.asarray" ], [ "", "getattr" ], [ "", "isinstance" ], [ "", "hasattr" ], [ "", "key" ], [ "", "np.asarray" ], [ "", "hasattr" ], [ "", "arrays.update" ], [ "", "extract_base_estimator_arrays" ], [ "", "isinstance" ], [ "", "setattr" ], [ "", "val.item" ], [ "", "setattr" ], [ "", "isinstance" ], [ "", "any" ], [ "", "k.startswith" ], [ "", "hasattr" ], [ "", "BinaryGaussianProcessClassifierLaplace" ], [ "", "restore_base_estimator_arrays" ], [ "", "Any" ], [ "", "BaseEstimator" ], [ "", "EstimatorHandler" ], [ "", "GaussianProcessClassifier" ], [ "", "GaussianProcessRegressor" ], [ "", "SKLEARN_ARRAY_ATTRS" ], [ "", "_BinaryGaussianProcessClassifierLaplace" ], [ "", "_deserialize_kernel" ], [ "", "_serialize_kernel" ], [ "", "numpy" ], [ "", "skeights._handler" ], [ "", "skeights._kernels" ], [ "", "skeights._utils" ], [ "", "sklearn.base" ], [ "", "sklearn.gaussian_process" ], [ "", "sklearn.gaussian_process._gpc" ], [ "", "typing" ] ], "mbr": [ "arrays.update", "be.kernel_", "be.log_marginal_likelihood_value_", "estimator.base_estimator_", "estimator.classes_", "estimator.copy_X_train", "estimator.kernel", "estimator.kernel_", "estimator.log_marginal_likelihood_value_", "estimator.max_iter_predict", "estimator.n_classes_", "estimator.n_restarts_optimizer", "estimator.optimizer", "estimator.random_state", "estimator.warm_start", "k.startswith", "np.asarray", "np.ndarray", "val.item", "val.ndim" ], "tgt": [ "_BinaryGaussianProcessClassifierLaplace", "_deserialize_kernel", "_extract_base_estimator_arrays", "_key", "_restore_base_estimator_arrays", "_serialize_kernel", "any", "arrays.update", "getattr", "hasattr", "isinstance", "k.startswith", "np.asarray", "setattr", "val.item" ], "funcs": [ [ "_extract_base_estimator_arrays", 399 ], [ "_restore_base_estimator_arrays", 864 ], [ "handles", 1310 ], [ "collect_state", 1482 ], [ "restore_state", 2950 ], [ "extract_arrays", 4414 ], [ "_key", 4553 ], [ "restore_arrays", 5485 ] ], "metrics": { "ast": { "op.bor": 2.0, "op.land": 1.0, "max_depth": 18.0, "bind_count": 26.0, "call_count": 42.0, "node_count": 1628.0, "member_count": 20.0, "op_density.bor": 0.0, "op_density.land": 0.0, "identifier_count": 78.0, "member_depth_max": 2.0, "string_literal_count": 45.0, "array_literal_max_length": 5.0, "string_return_function_count": 1.0, "string_return_function_ratio": 0.13 }, "file": { "size": 7404.0, "entropy": 4.27, "size_bytes": 7404.0 }, "text": { "digit_ratio": 0.0, "space_count": 2159.0, "total_lines": 184.0, "char_entropy": 4.27, "unique_chars": 59.0, "string_density": 0.24, "avg_line_length": 39.24, "max_line_length": 108.0, "empty_line_ratio": 0.1, "last_line_length": 88.0, "whitespace_ratio": 0.32, "most_common_ratio": 0.06, "identifier_density": 2.01, "line_length_stddev": 24.36, "normalized_string_count": 3.32, "repeated_char_sequences": 89.0, "most_common_char_is_null": 0.0, "max_inline_whitespace_run": 2.0, "most_common_char_codepoint": 101.0, "suspicious_identifier_ratio": 0.01, "normalized_unique_identifiers": 10.37 }, "binds": { "count": 26.0 }, "calls": { "count": 42.0 }, "binary": { "overall_entropy": 4.27, "peak_region_bytes": 2048.0, "peak_region_entropy": 4.76 }, "source": { "class_count": 1.0, "function_count": 8.0 }, "imports": { "count": 17.0, "stdlib_count": 1.0, "stdlib_ratio": 0.06, "unique_modules": 17.0, "aliased_imports": 2.0, "third_party_count": 16.0, "third_party_ratio": 0.94 }, "members": { "count": 20.0 }, "strings": { "total": 45.0, "avg_length": 19.13, "max_length": 64.0, "avg_entropy": 3.23, "total_bytes": 861.0, "entropy_stddev": 0.73 }, "comments": { "chars": 173.0, "lines": 7.0, "total": 7.0, "to_code_ratio": 0.04 }, "functions": { "count": 9.0, "avg_params": 3.13, "max_params": 5.0, "length_stddev": 14.2, "avg_name_length": 15.63, "avg_length_lines": 20.0, "max_length_lines": 46.0, "min_length_lines": 2.0, "nested_functions": 1.0, "avg_nesting_depth": 0.13, "max_nesting_depth": 1.0, "avg_param_name_length": 6.84, "density_per_100_lines": 4.35, "code_in_functions_ratio": 0.87 }, "identifiers": { "count": 78.0, "total": 370.0, "avg_length": 10.28, "max_length": 39.0, "min_length": 1.0, "avg_entropy": 2.55, "reuse_ratio": 0.21, "unique_count": 78.0, "length_stddev": 7.31, "sequential_names": 1.0, "single_char_count": 1.0, "single_char_ratio": 0.01, "high_entropy_count": 3.0, "high_entropy_ratio": 0.04, "all_lowercase_ratio": 0.87, "all_uppercase_ratio": 0.03, "underscore_prefix_count": 11.0 } } }, "id": 3, "mol": "H(Db)", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_gp.py", "pid": 0, "risk": 1, "sha": "01420314273984cbe04b7bf0741662a22912760d446c8b8d5543f7423a85d231", "size": 7404, "traits": [ { "id": "micro-behaviors/data/manipulation::numpy-import", "conf": 0.9, "crit": 3, "desc": "Imports the NumPy array library", "spans": [ [ 127, 5 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--ndarray", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (ndarray)", "spans": [ [ 492, 0 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations", "conf": 0.85, "crit": 3, "desc": "Dense NumPy array construction and reduction", "spans": [ [ 492, 10 ] ] }, { "id": "micro-behaviors/data/manipulation::numeric-computation-library", "conf": 0.95, "crit": 3, "desc": "Module built on the numeric Python stack", "spans": [ [ 127, 5 ], [ 492, 10 ] ] } ], "type": "python" }, { "id": 4, "mol": "H(Db)", "sha": "3b46afbb6c75de6cb6b3b31893c1d56ff9f08ca577afbd7b4e7fd1403ae48fe8", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_handler.py", "risk": 1, "size": 1957, "type": "python", "depth": 1 }, { "id": 5, "mol": "H(Db)", "sha": "83728f216771124b4e5b7a072e253712d24f89dd5040351eb69584edd89260c1", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_hgb.py", "risk": 1, "size": 9912, "type": "python", "depth": 1 }, { "ctx": [ { "b": "a%FjfvrMi8vqYP#y\u0026r-)azbtfBy!#9B8bP6vrcldwPI%czddK8A=SvBzY\u003cafw[u6}zGx-pB08$Qn(FIXe*qF-3jpx=z/3R7uUjC5B-I52uM:61AbP=sayPe9z//Afx(v)g3jpG:AbP=sazL$ozvg8{AbP=saA}mmzFs03A%=J1z/3Rovrug0x\u003c@i0ze:AlBrBy*Bz81[A=k!qBA}?tzF78aze:AlBrA\u003e!C)T))ze:AlBrCEzze:+yvriMeA0*q@AbP=saAH$6wPRH3B8M8ue]C/GAcR!8ze:AlBrCTuy?m3}zvf#@z/3RryIWM\u003cA=9Hsvrl05x(d*cA=-A\u003cvrl0GB98bkvruBd3jpx=z/3RryH}i)xMOqFuT[1{wGUY7AbP=sasENtarR!lvrcx%D2)r", "n": [ { "c": 3, "d": "Module built on the numeric Python stack", "i": "micro-behaviors/data/manipulation::numeric-computation-library", "o": 190, "z": 5, "cf": 0.95 }, { "c": 2, "d": "File uses a Python artifact extension", "i": "metadata/file/extension/identity::py", "o": 0, "z": 6, "cf": 1.0 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-2", "o": 8, "z": 3, "cf": 0.8 }, { "c": 1, "d": "Python import-from statement", "i": "micro-behaviors/data/source/language::python-import-from-statement", "o": 70, "z": 34, "cf": 0.8 } ], "ln": 0, "col": 1, "line": 1 }, { "b": "wO#P%C4CYnx(v(qAbf8EaAITBdiHiaaAITBaBCqbz/fbE3lQDlar\u00260Nm}D=+Bzbkdx(n0lvqG:\u003ewfu5bA=U@kzxJ\u003efayMyivpK7YxjSRpz/M%}z/fbsa%FirarR^Hx\u003ewGbyIa+MjS\u003e}\u0026yIWM\u003cA=96Z3lQDlarR^HaAz4nB-IvxB8bP6vrclruTE$/A=U@kzEl-TarR^HBAhT/3lQDlarR^HazCXiz/P}xx(d!", "n": [ { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-1", "o": 646, "z": 3, "cf": 0.8 }, { "c": 1, "d": "String literal equality or membership check", "i": "micro-behaviors/data/control-flow/analysis::string-literal-equality-check", "o": 705, "z": 12, "cf": 0.92 } ], "ln": 598, "col": 14, "line": 28 }, { "b": "arR^HaAz4nB-Ivxx(d*cA==bivLhIeBywY*Byu!BwPz\u003caz/c$xyIb76arR^HwQ4Y@Ac9i\u003eCW\u003er7BzkVhiTM#LarR^HarUYoBAIRwawM\u0026)wEn+KwmYu}uW2}0zEmM#A=U@kzEml{B8tucv}WoivrMi)uV{13B7]MgB2\u003eBOx\u003e8l?B98BNaAITBt}3)Fj%iQszE\u003e\u003coarR^Ha%Fjjvrcldx\u003ewF@zH0vCvrMi)ao", "n": [ { "c": 2, "d": "Error handling keywords", "i": "micro-behaviors/crypto/symmetric/fernet::error-handling-keywords", "o": 849, "z": 16, "cf": 1.0 }, { "c": 2, "d": "Python return None statement", "i": "micro-behaviors/data/control-flow/return::python-return-none", "o": 875, "z": 11, "cf": 0.94 } ], "ln": 801, "col": 4, "line": 35 }, { "b": "xjSiewPz\u003caz/cXdx\u003ey%*A=SvnA=k!qBzbkdv%8*jwO#Pjz/fbsa%FirarR^Hw]zYjAbf8qaAH$mwN]d\u003ewPw]czxK1eC4Ch\u003eC4CYnx(v)ge[]Aszf49OiTM#LarR^HarUxgaAhaeau.\u003egb6dKhx\u003eIa3B0rTLarR^HarR^HarR^Hv@Dmbx(n683lQC", "n": [ { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-5", "o": 1035, "z": 3, "cf": 0.8 } ], "ln": 987, "col": 31, "line": 41 }, { "b": "arR^Hv@Dmbx(n683lQDlarR^HaAH$mwN]d+z6g$:a$+5(yhW*7d05*uwN]d\u003ewPxzAAbolgc)yn/do!?*t}3a6arR^HarR!pB-IIlzGGl5z6g$:a$+5(yhW*7c$vyuA+fcguJ", "n": [ { "c": 1, "d": "Joins values with a dot separator", "i": "objectives/anti-static/obfuscation/encoding/ip-notation::join-call", "o": 1252, "z": 9, "cf": 0.5 } ], "ln": 1220, "col": 9, "line": 47 }, { "b": "vrcm1zFa2yCvtJfc\u003c?7tarR^HarR^HarR^HarUnuo(BMNy-)}gB0bKjC4ChbCwhejaBw6yxmg[HB76l6wm6H\u003eA^Y5O3lQDlarR^HarR^HarR^Haz8*bB-X:Kz/)ghA+cwfz^^f\u003czF78ox([2hDT?hsA+fcguV{13Ej=S^3lQDlarR^HarR^HarR^H", "n": [ { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-6", "o": 1441, "z": 4, "cf": 0.8 } ], "ln": 1393, "col": 14, "line": 51 }, { "b": "w]zZbvrsKMB98BBD(#g5zE\u003c}NawM\u0026)wH[fqat2=1BAILswM@XVv@${@BAe]Pl2H%NefFFqv@${@BAe]PzG4jCwmoI0vr(c:iTM#LarR\u003cLb2-5[x\u003c\u003e*(DsXjcazbtfBy!#9wPI%czddK8AV/ExayMylByxo5ay]g@BrC1fwftr3A::lmay]g@Bs)[carR^Hl2{QViTM#LarR^HarUlpBzkP2Bz(gXavdbZx([Ddwft@ey?m3}zxJIiBzkP2Bz?", "n": [ { "c": 3, "d": "Dense NumPy array construction and reduction", "i": "micro-behaviors/data/manipulation::numpy-array-operations", "o": 1729, "z": 10, "cf": 0.85 } ], "ln": 1665, "col": 5, "line": 61 }, { "b": "wPI%czddK8AW.trarR!vw/@ptD2Nssaz#atazCZoAa9=}zf4-BarR^HarR^HAa9=}zf5]9BA}?pb3=rOazkncuVQ10wNPQ%uVpc%y?Wx^Aa9\u003c4d0f-NwHIbhBzkP2Bz(g", "n": [ { "c": 1, "d": "EVM eth_call params field", "i": "objectives/command-and-control/channel/deaddrop/blockchain::evm-eth-call-params", "o": 2240, "z": 7, "cf": 0.9 } ], "ln": 2208, "col": 31, "line": 75 }, { "b": "B6x\u00268x\u003eIa3xjtZ4t{8oMy?WJ}Bz261e)?$ewPz\u003caz/e]?3lQDlaz2!cwPh-lnO@A+A=:-\u003cA=k$V3lQDlarR^HaAg+gA%:3jarU=DC@=oParR^HarR!vze:AlBrC*vvScgaBp5u$arR^HarR!vw/@pxxjt^$B95PGx(k5nD2NsywPI%czddK8AW-RFuU%Z(B.\u003eQ", "n": [ { "c": 2, "d": "ImportError exception", "i": "micro-behaviors/data/control-flow/error-handling::importerror-keyword", "o": 3605, "z": 11, "cf": 0.6 } ], "ln": 3557, "col": 20, "line": 118 }, { "b": "dgdguarU-lw[u6}zGx-pB1RuMze:+MB76l6uUj1*wHH#cA::lmefG1QAWUvpA::lmuVoB}xELwqarR^Hp*[DVd06GsBy!/#vrufie{ztIBy!*3wQ5qByiarhe[x9wAc0BGByxo5efFUAwmYU2jU!MhwmYvYB.(d.yiarhuU0.WvrDyddjCPh3s)ZWaz+$8wgd^carR!nA=LPlB6\u0026({Bz9YTB98BBD(#l]Bz9ijarR^HB97\u0026jwNxy+Bz9YTB98BBD(#l]Bn", "n": [ { "c": 3, "d": "pathlib write_text/write_bytes call", "i": "micro-behaviors/fs/file/write/direct::py-pathlib-write-call", "o": 4585, "z": 17, "cf": 0.9 }, { "c": 2, "d": "Serializes data with Python json.dumps()", "i": "micro-behaviors/data/serialize/json::json-dumps-call", "o": 4613, "z": 10, "cf": 0.9 } ], "ln": 4521, "col": 56, "line": 148 }, { "b": "aAz46z/fSrA=\u003e(lwN)tmA+eV\u0026C}BbRePt-wwnbK}az2Rox(dp2z/NDqarR^Ha%FirarR^HB97\u0026jwGTbUyiarhe]kDmwofd}vrufhB97\u0026jwNxy+Bz99QA+eV\u0026uVY\u003e7BsnN!3lQDlayPqhvr(]pjS[oHv@%buvp\u003c7)wO#NcA=S\u003cJB.#8ye]kDmwm5}.y?k2oBAe^rA=LPlB6\u0026({Bz99LdgdguarU-lC4Ch\u003eC4CYnx(v)gauZ\u0026*Byxo5e[X:qc)w", "n": [ { "c": 3, "d": "Parses JSON data with Python", "i": "micro-behaviors/data/serialize/json::json-loads-call", "o": 5033, "z": 10, "cf": 0.9 }, { "c": 2, "d": "Read text via pathlib", "i": "micro-behaviors/fs/read/file::python-pathlib-read-text", "o": 5044, "z": 26, "cf": 0.8 } ], "ln": 4969, "col": 16, "line": 164 } ], "depth": 1, "facts": { "imp": [ [ "", "importlib.metadata.version" ], [ "", "saved_versions.items" ], [ "", "get_current_version" ], [ "", "\".\".join" ], [ "", "saved_ver.split" ], [ "", "\".\".join" ], [ "", "current_ver.split" ], [ "", "warnings.warn" ], [ "", "arrays_from_estimator" ], [ "", "get_model_params" ], [ "", "get_sklearn_public_path" ], [ "", "type" ], [ "", "collect_fitted_state" ], [ "", "rebuild_estimator_from_params" ], [ "", "state.get" ], [ "", "restore_estimator_arrays" ], [ "", "restore_fitted_state" ], [ "", "type" ], [ "", "type" ], [ "", "serialize" ], [ "", "version_info" ], [ "", "safetensors.numpy.save_file" ], [ "", "str" ], [ "", "Path(state_path).write_text" ], [ "", "Path" ], [ "", "json.dumps" ], [ "", "json.loads" ], [ "", "Path(state_path).read_text" ], [ "", "Path" ], [ "", "dict" ], [ "", "safetensors.numpy.load_file" ], [ "", "str" ], [ "", "state.get" ], [ "", "warn_version_mismatch" ], [ "", "deserialize" ], [ "", "Any" ], [ "", "BaseEstimator" ], [ "", "Path" ], [ "", "__version__" ], [ "", "_arrays_from_estimator" ], [ "", "_collect_fitted_state" ], [ "", "_rebuild_estimator_from_params" ], [ "", "_restore_estimator_arrays" ], [ "", "_restore_fitted_state" ], [ "", "get_model_params" ], [ "", "get_sklearn_public_path" ], [ "", "importlib.metadata" ], [ "", "json" ], [ "", "json_default" ], [ "", "lightgbm" ], [ "", "numpy" ], [ "", "pathlib" ], [ "", "safetensors.numpy" ], [ "", "skeights" ], [ "", "skeights._core" ], [ "", "skeights._params" ], [ "", "skeights._utils" ], [ "", "sklearn" ], [ "", "sklearn.base" ], [ "", "typing" ], [ "", "warnings" ], [ "", "xgboost" ] ], "mbr": [ "Path().read_text", "Path().write_text", "current_ver.split", "importlib.metadata", "importlib.metadata.version", "json.dumps", "json.loads", "lightgbm.__version__", "np.ndarray", "params.type", "safetensors.numpy", "safetensors.numpy.load_file", "safetensors.numpy.save_file", "saved_ver.split", "saved_versions.items", "sklearn.__version__", "state.get", "state.model_params", "state.skeights_version", "type().__module__", "versions.lightgbm", "versions.xgboost", "warnings.warn", "xgboost.__version__" ], "tgt": [ "Path", "Path().read_text", "Path().write_text", "_arrays_from_estimator", "_collect_fitted_state", "_get_current_version", "_rebuild_estimator_from_params", "_restore_estimator_arrays", "_restore_fitted_state", "_version_info", "_warn_version_mismatch", "current_ver.split", "deserialize", "dict", "get_model_params", "get_sklearn_public_path", "importlib.metadata.version", "json.dumps", "json.loads", "safetensors.numpy.load_file", "safetensors.numpy.save_file", "saved_ver.split", "saved_versions.items", "serialize", "state.get", "str", "type", "warnings.warn" ], "funcs": [ [ "_get_current_version", 585 ], [ "_warn_version_mismatch", 889 ], [ "serialize", 1616 ], [ "deserialize", 2482 ], [ "_version_info", 3173 ], [ "save", 3829 ], [ "load", 4666 ] ], "metrics": { "ast": { "op.bor": 7.0, "op.lor": 1.0, "max_depth": 13.0, "bind_count": 16.0, "call_count": 35.0, "node_count": 1109.0, "member_count": 24.0, "op_density.bor": 0.01, "op_density.lor": 0.0, "identifier_count": 75.0, "member_depth_max": 3.0, "string_literal_count": 31.0 }, "file": { "size": 5275.0, "entropy": 4.54, "size_bytes": 5275.0 }, "text": { "digit_ratio": 0.0, "space_count": 1089.0, "total_lines": 170.0, "char_entropy": 4.54, "unique_chars": 65.0, "string_density": 0.18, "avg_line_length": 30.03, "max_line_length": 83.0, "empty_line_ratio": 0.17, "last_line_length": 37.0, "whitespace_ratio": 0.24, "most_common_ratio": 0.08, "identifier_density": 1.37, "line_length_stddev": 23.4, "normalized_string_count": 2.38, "repeated_char_sequences": 14.0, "suspicious_string_ratio": 0.13, "most_common_char_is_null": 0.0, "max_inline_whitespace_run": 1.0, "most_common_char_codepoint": 116.0, "normalized_unique_identifiers": 10.12 }, "binds": { "count": 16.0 }, "calls": { "count": 35.0 }, "binary": { "overall_entropy": 4.54, "peak_region_bytes": 5275.0, "peak_region_entropy": 4.55 }, "source": { "function_count": 7.0 }, "imports": { "count": 27.0, "stdlib_count": 5.0, "stdlib_ratio": 0.19, "unique_modules": 27.0, "aliased_imports": 1.0, "dynamic_imports": 1.0, "third_party_count": 22.0, "third_party_ratio": 0.81 }, "members": { "count": 24.0 }, "strings": { "total": 31.0, "avg_length": 59.42, "max_length": 435.0, "avg_entropy": 2.9, "sql_strings": 1.0, "total_bytes": 1842.0, "entropy_stddev": 1.31, "shell_command_strings": 3.0 }, "functions": { "count": 7.0, "avg_params": 1.86, "max_params": 4.0, "length_stddev": 4.27, "avg_name_length": 11.86, "avg_length_lines": 18.71, "max_length_lines": 24.0, "min_length_lines": 10.0, "high_entropy_names": 1.0, "avg_param_name_length": 8.38, "density_per_100_lines": 4.12, "code_in_functions_ratio": 0.77 }, "identifiers": { "count": 75.0, "total": 233.0, "avg_length": 9.15, "max_length": 30.0, "min_length": 2.0, "avg_entropy": 2.6, "reuse_ratio": 0.32, "unique_count": 75.0, "length_stddev": 5.69, "high_entropy_count": 4.0, "high_entropy_ratio": 0.05, "all_lowercase_ratio": 0.93, "double_underscore_count": 2.0, "underscore_prefix_count": 13.0 } } }, "id": 6, "mol": "H₂(Db₂F)", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_io.py", "pid": 0, "risk": 3, "sha": "d12ec32387eeef1626112eb8ca3ecbf151fdb6d504971c5a323b002df1dd01c6", "size": 5275, "traits": [ { "id": "micro-behaviors/fs/file/write/direct::py-pathlib-write-call", "conf": 0.9, "crit": 3, "desc": "pathlib write_text/write_bytes call", "spans": [ [ 4585, 17 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-import", "conf": 0.9, "crit": 3, "desc": "Imports the NumPy array library", "spans": [ [ 190, 5 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--ndarray", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (ndarray)", "spans": [ [ 1729, 0 ] ] }, { "id": "micro-behaviors/data/serialize/json::json-loads-call", "conf": 0.9, "crit": 3, "desc": "Parses JSON data with Python", "spans": [ [ 5033, 10 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations", "conf": 0.85, "crit": 3, "desc": "Dense NumPy array construction and reduction", "spans": [ [ 1729, 10 ] ] }, { "id": "micro-behaviors/data/manipulation::numeric-computation-library", "conf": 0.95, "crit": 3, "desc": "Module built on the numeric Python stack", "spans": [ [ 190, 5 ], [ 1729, 10 ] ] } ], "type": "python" }, { "id": 7, "mol": "H(Db)", "sha": "16256bf93f8d36c4083082d30f591e92540dcc09ede77d70851c712c4563b69f", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_kernels.py", "risk": 1, "size": 1943, "type": "python", "depth": 1 }, { "id": 8, "mol": "H(Db)", "sha": "f09a81d79aac29618d6ed240aabc82427e6683795f9c954a97a47dc465d44da1", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_lgbm.py", "risk": 1, "size": 16019, "type": "python", "depth": 1 }, { "id": 9, "mol": "H(Db)", "sha": "699e3e76344dba7a85aa52b6802607ca0dd1c1b39b45d21196fb932f46964352", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_mlp.py", "risk": 1, "size": 2697, "type": "python", "depth": 1 }, { "id": 11, "mol": "H(Db)", "sha": "23dfafda38b5772143351e8fb7f3faee8d4132a0b035befdb04478447a0d90e5", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_trees.py", "risk": 1, "size": 14957, "type": "python", "depth": 1 }, { "id": 12, "mol": "H(Db)", "sha": "380d7d4f33641af0eaf7ec0c2bc3aee2024a6efdaf279e0901e784a7d5530313", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_ttr.py", "risk": 1, "size": 4626, "type": "python", "depth": 1 }, { "ctx": [ { "b": "a%FjfxKL{)wfu2px(4H9x\u003equdB-Rb8ayYQsvScv4aywR%A+c\u003exC{3KkwftD8BzkP2Bz(gxzeS%cy?mVu3jo:Cx(+zlz!a0bwGU\u0026jB95Kxz/^aoze:AlBrCgoz/3R7v@Dy0e]V7Uz/M$ezH0voB98bkvruBdaz(4cB.\u003eQ@Bz\u0026pgC5I89ay/bav%8P@AV/7kAbP=sB1N!za%Ev3w].*baywF/B-.+DwNw^!x(d*cA=-BjzF\u003cxmvruj4zGuc(x(d*cA=-Brze:AlBzLV23tBu@z/P}xCvtJfx(mN83tar%z6i}CAa%i5azCXiz/P}xl2H@P3tBu@z/P}xzGP/nC{3Kpaz#c9w].*baAIsmwNPQ%e[emgwGUY7AbP=savoHTwKQVZx(dp2z/Mf(3s)ZWazL$ozEl{=w)]*#Bsq6pyc0F6zH0VNeJ$pyzH1nIarR^Ha%Fj6q+{dhwO#0@wmY^7wmYvYB.(dxw]zYjzGP/nC{4iOAaK8ya]", "n": [ { "c": 3, "d": "Module built on the numeric Python stack", "i": "micro-behaviors/data/manipulation::numeric-computation-library", "o": 264, "z": 5, "cf": 0.95 }, { "c": 2, "d": "File uses a Python artifact extension", "i": "metadata/file/extension/identity::py", "o": 0, "z": 9, "cf": 1.0 }, { "c": 1, "d": "Python import-from statement", "i": "micro-behaviors/data/source/language::python-import-from-statement", "o": 164, "z": 34, "cf": 0.8 } ], "ln": 0, "col": 1, "line": 1 }, { "b": "az#cJw]8x]BzkS9dlm!UarR^HarR!EwPS6nzxJLcz^^-oz^)Dg3lQDlazCBgx(!0aB97\u0026dv}v6bvRNCpzG4jCwmoI0vr\u003cp.3lQDlarR^HaAz4nB-Ivxz^)DlBz\u003e#fB95/V3lQDlaAy[8B7DE[D2Ns-A=M8sc$TV0vRPE:BrCHlaAR)FwGVtwD2Nsyz^)Dge)?$6vqPN.uWT5hB0bvsBrBgOpFJ3NwPzG[y?Xi7vR/Q1dgcy?wmYu}xjVf(B8bP6vrcl)AckSax\u003e7H?vrufhv@ciEaAR)FwHO-Nj%j]*AYKKIarR^Ja%G]@BAIRwaARpdaAITkvR/P#AckSax\u003e5o1ze:AlBrCKhBz8!ez/M$ezxK1oy?m3}zxJIiBzkP2Bz(gxv@bN{B1N!barR^HB8bP6vrcldAbn@)wPF#7z/f69wPRGav@bN{B7Gznx(k5jA+PY9By=OoBZ/iawozZ1B08(xe[V^zarQ", "n": [ { "c": 3, "d": "Dense NumPy array construction and reduction", "i": "micro-behaviors/data/manipulation::numpy-array-operations", "o": 546, "z": 10, "cf": 0.85 }, { "c": 2, "d": "Source file has low overall entropy", "i": "metadata/file/metrics::low-overall-entropy-source", "o": 728, "z": 29, "cf": 0.9 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-5", "o": 765, "z": 3, "cf": 0.8 } ], "ln": 482, "col": 23, "line": 21 }, { "b": "c$3C7yIWM\u003cA=9HGA+figz!0v1B7]J8e(M\u003e2zE^f@wk=#Dy?mS{u[0YnarR^Hra]#!aA}mgyJyRvA3fmowGUV2wPzj1v}ZcsaA?spx\u003ezT8zF786vpJ%[v{%m=x\u003egT]wGVegviw@=xjVf[BAzLhu[qTcarR!nzE:(4vqG+3ayX+?yAN.qaARpdazb+jy-)Xqx)9{bwGU@2Bz8!hw/$#faAhEjy?Wx4A+c?lCYmOwBrCpsazbLmzE+vbarR^Ha%FirarR^HAa9^eB09Q*v@cisuTEU*wozZ1uTCBbAbolgc)yn/dgdguarUomAV/6sx(k5lvqYZ?c#rEjc#-QnBAn(Zattt?eIOXn3lQDlarR^HazCBgAa9^eB6Au3eG==Ne]#byA==wDx([2pb3#JyiTM#LarR^HarR^HarUfjzGGPgB.7[5arR^HarR!pvqYQ\u0026wmoN\u003eauZ?\u003ee*q].z!T8qAa9^eB6yXtt}3a6arR^HarR!GA^oXMarR^HarR^HarR^HzeS@cjS[DQAbP=sy?Wuhx(d*cA=+V9z!a0bwHI4%zE^D(vru6f3lQDlarR^HarR^HazCBgxjVf[BAzKKzeS@oay/kee)?$6vqPN.uO0r{z/fbnazC)tv@ciE3lQDlarR^HarR^HarR^HaAz4nB-Ivxw*hOivqYQ\u0026wmoN\u003eEj/\u003eRy\u0026.jouV6p?wNw!)a{]CnarR^HarUluv}xR3aw3A?z/P}*A=M8siTM#LarR^HarR^HarUfjzGGPgB.7[5arR!sB.\u003e(3Aa9\u003c4auZ\u0026Vb70*oB1Q*bzeS%cy?l%XEj/\u003eRy\u0026.jouV6p?wNw!)a{]CnarU(pA=bPexlbXHvrcll3lQDlarR^Haz8/)zY\u003c1wvR/:*aAz3BwQ5fjA=-Boz/]@dazbLjaBvQmB1Q*bzEEx[uTFjyaA.:tzF78hA+PY9By=Olvruf9a{]CnarR^HarUnucWPDFy\u00260D$vrughcOuJvxLzJgzddYjvSD3*yANt6aAIsmwNPQ%aAz4iA+w/#x(^\u003cbazC.nwPzV%y-)OkwozZ1B1OT/3lQDlarR^HaAITkv@2)(C4CFMgaS+ParR^Q3lQDlaAz4nB-Ivxw{4{auVoB}xBk7NwmYu}uUj1%uUTU2zEmu\u003eA:-/(BA}?pB0}wrarR!py\u0026.SWBA}?pts8+twKQVZx(dp2z/PbmaAg+fvqQ6Day]g@Bx-*dAX5t0zH2H{diHiaay]g@Bx-*dAX5t0zH2IG3lQDlar\u00260NlVl\u003c=wPz(ny?W%jaAg+fvqQ6d", "n": [ { "c": 4, "d": "Python dynamic import patterns", "i": "objectives/anti-static/obfuscation/reflection/class::python-import", "o": 1376, "z": 23, "cf": 0.85 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-2", "o": 1085, "z": 3, "cf": 0.8 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-7", "o": 1010, "z": 4, "cf": 0.8 }, { "c": 2, "d": "python code embedded in string", "i": "metadata/lang/embedded::python", "o": 1456, "z": 408, "cf": 1.0 }, { "c": 2, "d": "Contains an iteration loop", "i": "micro-behaviors/data/control-flow/analysis::iteration-loop-pattern", "o": 1207, "z": 10, "cf": 0.5 }, { "c": 1, "d": "Python for-range-over-len(X) loop", "i": "micro-behaviors/data/control-flow/analysis::python-for-range-len-loop", "o": 1217, "z": 5, "cf": 0.4 }, { "c": 1, "d": "Python getattr dynamic attribute lookup", "i": "micro-behaviors/os/api-resolution/dynamic::python-getattr-call", "o": 1426, "z": 7, "cf": 0.75 }, { "c": 1, "d": "Joins values with a dot separator", "i": "objectives/anti-static/obfuscation/encoding/ip-notation::join-call", "o": 1325, "z": 9, "cf": 0.5 }, { "c": 1, "d": "EVM eth_call params field", "i": "objectives/command-and-control/channel/deaddrop/blockchain::evm-eth-call-params", "o": 1907, "z": 7, "cf": 0.9 } ], "ln": 962, "col": 29, "line": 33 }, { "b": "3lQDlar\u00260NnO@A+A=-Bjay/j@B8@EkC{3*yB0b7qy?$k8z/*8jwft\u00261Bz9iFCwhejayPdgvqG:#CwH#mBrC7bwN/Hd3jm)#arTM\u003cx(^\u003cbayFOTvqH6$mriA!A:Sn$x\u003ewGfxK@r6z!a0bwGUYdaz#atazCZoBzbkdvqG:#Cv+qcAb]J4x)sige^-Zz", "n": [ { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-6", "o": 2781, "z": 4, "cf": 0.8 }, { "c": 1, "d": "Regex component marker", "i": "objectives/credential-access/shell/history::shell-history-unless-cond-1--rx-helper-6", "o": 2789, "z": 9, "cf": 1.0 } ], "ln": 2733, "col": 41, "line": 85 } ], "depth": 1, "facts": { "imp": [ [ "", "isinstance" ], [ "", "int" ], [ "", "isinstance" ], [ "", "float" ], [ "", "isinstance" ], [ "", "obj.tolist" ], [ "", "TypeError" ], [ "", "type" ], [ "", "cls.__module__.split" ], [ "", "range" ], [ "", "len" ], [ "", "parts[i - 1].startswith" ], [ "", "\".\".join" ], [ "", "importlib.import_module" ], [ "", "getattr" ], [ "", "warnings.warn" ], [ "", "cls().get_params" ], [ "", "cls" ], [ "", "tuple" ], [ "", "isinstance" ], [ "", "isinstance" ], [ "", "defaults.get" ], [ "", "params.items" ], [ "", "type_path.rpartition" ], [ "", "any" ], [ "", "type_path.startswith" ], [ "", "ValueError" ], [ "", "getattr" ], [ "", "importlib.import_module" ], [ "", "Any" ], [ "", "BaseEstimator" ], [ "", "importlib" ], [ "", "numpy" ], [ "", "sklearn.base" ], [ "", "typing" ], [ "", "warnings" ] ], "mbr": [ "cls().get_params", "cls.__module__", "cls.__module__.split", "cls.__name__", "defaults.get", "importlib.import_module", "np.floating", "np.integer", "np.ndarray", "obj.tolist", "params.items", "type().__name__", "type_path.rpartition", "type_path.startswith", "warnings.warn" ], "tgt": [ "TypeError", "ValueError", "any", "cls", "cls().get_params", "cls.__module__.split", "defaults.get", "float", "getattr", "importlib.import_module", "int", "isinstance", "len", "obj.tolist", "params.items", "range", "tuple", "type", "type_path.rpartition", "type_path.startswith", "warnings.warn" ], "funcs": [ [ "json_default", 317 ], [ "get_sklearn_public_path", 674 ], [ "_fix_json_param_types", 1850 ], [ "safe_import", 2693 ] ], "metrics": { "ast": { "op.sub": 2.0, "op.land": 1.0, "max_depth": 13.0, "bind_count": 7.0, "call_count": 29.0, "node_count": 769.0, "member_count": 15.0, "op_density.sub": 0.0, "op_density.land": 0.0, "identifier_count": 63.0, "member_depth_max": 3.0, "string_literal_count": 38.0, "array_literal_max_length": 20.0 }, "file": { "size": 3805.0, "entropy": 4.75, "size_bytes": 3805.0 }, "text": { "digit_ratio": 0.0, "space_count": 759.0, "total_lines": 121.0, "char_entropy": 4.75, "unique_chars": 73.0, "string_density": 0.31, "avg_line_length": 30.45, "max_line_length": 88.0, "empty_line_ratio": 0.16, "last_line_length": 1.0, "whitespace_ratio": 0.23, "most_common_ratio": 0.06, "identifier_density": 1.13, "line_length_stddev": 26.21, "normalized_string_count": 3.45, "repeated_char_sequences": 8.0, "suspicious_string_ratio": 0.21, "most_common_char_is_null": 0.0, "max_inline_whitespace_run": 2.0, "most_common_char_codepoint": 101.0, "suspicious_identifier_ratio": 0.05, "normalized_unique_identifiers": 9.11 }, "binds": { "count": 7.0 }, "calls": { "count": 29.0 }, "binary": { "overall_entropy": 4.75, "peak_region_bytes": 3805.0, "peak_region_entropy": 4.75 }, "source": { "function_count": 4.0 }, "imports": { "count": 7.0, "stdlib_count": 3.0, "stdlib_ratio": 0.43, "unique_modules": 7.0, "aliased_imports": 1.0, "dynamic_imports": 1.0, "third_party_count": 4.0, "third_party_ratio": 0.57 }, "members": { "count": 15.0 }, "strings": { "total": 38.0, "avg_length": 42.55, "max_length": 438.0, "avg_entropy": 2.82, "sql_strings": 2.0, "total_bytes": 1617.0, "entropy_stddev": 1.33, "shell_command_strings": 2.0, "embedded_code_candidates": 4.0 }, "comments": { "chars": 302.0, "lines": 5.0, "total": 5.0, "to_code_ratio": 0.04 }, "functions": { "count": 4.0, "avg_params": 1.25, "max_params": 2.0, "length_stddev": 6.69, "avg_name_length": 16.75, "avg_length_lines": 16.5, "max_length_lines": 27.0, "min_length_lines": 9.0, "high_entropy_names": 3.0, "avg_param_name_length": 4.8, "density_per_100_lines": 3.31, "code_in_functions_ratio": 0.55 }, "identifiers": { "count": 63.0, "total": 137.0, "avg_length": 7.44, "max_length": 23.0, "min_length": 1.0, "avg_entropy": 2.33, "reuse_ratio": 0.46, "unique_count": 63.0, "length_stddev": 4.87, "sequential_names": 3.0, "single_char_count": 4.0, "single_char_ratio": 0.06, "high_entropy_count": 4.0, "high_entropy_ratio": 0.06, "all_lowercase_ratio": 0.89, "all_uppercase_ratio": 0.05, "double_underscore_count": 2.0, "underscore_prefix_count": 4.0 } } }, "id": 13, "mol": "H(Db)", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_utils.py", "pid": 0, "risk": 2, "sha": "b49ce96829a63bbc285fbf0363d7804124a6f3779d55d5c7dad335ac8c6730d0", "size": 3805, "traits": [ { "id": "micro-behaviors/data/manipulation::numpy-import", "conf": 0.9, "crit": 3, "desc": "Imports the NumPy array library", "spans": [ [ 264, 5 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--ndarray", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (ndarray)", "spans": [ [ 546, 0 ] ] }, { "id": "micro-behaviors/os/api-resolution/dynamic::py-importlib-import-module", "conf": 0.6, "crit": 3, "desc": "Dynamically imports a Python module", "spans": [ [ 1376, 23 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations", "conf": 0.85, "crit": 3, "desc": "Dense NumPy array construction and reduction", "spans": [ [ 546, 10 ] ] }, { "id": "micro-behaviors/data/manipulation::numeric-computation-library", "conf": 0.95, "crit": 3, "desc": "Module built on the numeric Python stack", "spans": [ [ 264, 5 ], [ 546, 10 ] ] } ], "type": "python" }, { "ctx": [ { "b": "a%Fjkm).cjB95KCwPzG[y?Xi7BzkVhe^.}:B-qqrA==vBBA.TCw]zZbvruMK3n0xdu#xy{x)a5tyiarhu%(2rB98tvwPF#oxK@q}z/oYswPw]gz!9A}ayPslsvUX@z/Z1FB0byBzxILIpFJ3yx\u003e8k(arUxoaARpdaAITkBy^6Eaxi2*B0bgraARpdaAH$6wGUO[y\u00260M?v@0X7eG!Cev@DgazeJ^5eP+MwB8M8uu%\u003e99wmYvYB.(dGiV}%Av@Dj6z/YGhaARpdaARTnwGUM4B7Gh$y?j-6zGG!7arUSiA:-^2wO-GbB.#8yayPqhvr(]pB98tvwN(]$zxK1ew[u6}zGx-pB1wCTx([2hz/fxpaAIydy?$knv{%gZATA{iv@Dl%x\u003eFM5zxILIpFJIHa%Fir3tar%z6ig)w{5irA+eP+azCXiz/P}xvqY$3Byxo9z/fR63tBu@z/P}xyiarh3tar%z6i}CAa%i5azCXiz/P}xl2H@P3tBu@z/P}xzGP/nC{3Kpaz#c9w].*baAIsmwNPQ%e[emgwGUY7AbP=savoHTwKQVZx(dp2z/Mf(w].*baAIsfx\u003eIa3B1Q*kvqYQ(wPw]cze:AlBrB1[BzkP2Bz(g\u003cvqYQ(wPwa+boOM\u0026eIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeD", "n": [ { "c": 3, "d": "Module built on the numeric Python stack", "i": "micro-behaviors/data/manipulation::numeric-computation-library", "o": 404, "z": 5, "cf": 0.95 }, { "c": 2, "d": "File uses a Python artifact extension", "i": "metadata/file/extension/identity::py", "o": 0, "z": 7, "cf": 1.0 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-1", "o": 75, "z": 3, "cf": 0.8 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-6", "o": 279, "z": 4, "cf": 0.8 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-7", "o": 137, "z": 4, "cf": 0.8 }, { "c": 1, "d": "Python import-from statement", "i": "micro-behaviors/data/source/language::python-import-from-statement", "o": 325, "z": 34, "cf": 0.8 } ], "ln": 0, "col": 1, "line": 1 }, { "b": "wHIbhBzkP2Bz(gJasHtZlq?xcA+frkz/NxKsvUXBy*?yax\u003ez6\u003cAW-BAarR^HwQ4Y@Ac9i]ze:AlBvyj\u003cz/N(CarR^HarR^HA+funA=90?vqH0@3jmbJwO95(x(^S\u003ey*?yax\u003ez6\u003cAWUHuBzkP2Bz(gXavoHTwKQVZx(dp2z/NoHeJ$p^z/oCM3lQDlaARTHiTM#LarR^HarQ", "n": [ { "c": 2, "d": "Error handling keywords", "i": "micro-behaviors/crypto/symmetric/fernet::error-handling-keywords", "o": 861, "z": 18, "cf": 1.0 } ], "ln": 813, "col": 25, "line": 30 }, { "b": "eIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeKYboPD\u0026wO+)1wmYv!zFsibz/fRsw]zYjv@DgazeJ^5az2!tA:-E1x(v\u003e@boOM\u0026eIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeLaeIeK", "n": [ { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-5", "o": 1207, "z": 3, "cf": 0.8 } ], "ln": 1159, "col": 51, "line": 44 }, { "b": "3jprPw/$C(CYW$mv@#6/z!%MkzEEMl3lQDlayYncB97#liV{.aC}opKat2=1BAILswM@XVv@${@BAe]PzG4jCwmoI0vr(cfay]g@Bx-*dAX5t0zH2I[iTM#LarR\u003cLb1l-#A:-E1ay/taB.#28AV!!hA::lmayPd#az\u003eXivpS!*vixf5z/3R9zxJ4Klt{^-BrC4hz/Z2iAXnKWa{]CnarUYkCox3\u003eyiarhe]kDmwofedz/oYswPxzAvrMi?A::euA::f0w]zZbvrsTRyiarha$kcPwN/T?wHF#R3lQDlaz+Q$A=bDeauZ\u0026/vrU{1y?m3}zE)\u0026jt).X%arUraz6g$:y?m3}zE)\u0026)b4\u003e}8wnbQ)ByeG}z/Z2iAW1=@arR^HzeS@@y-\u003e\u003e-xjp", "n": [ { "c": 3, "d": "Dense NumPy array construction and reduction", "i": "micro-behaviors/data/manipulation::numpy-array-operations", "o": 2239, "z": 10, "cf": 0.85 }, { "c": 3, "d": "Parses JSON data with Python", "i": "micro-behaviors/data/serialize/json::json-loads-call", "o": 2351, "z": 10, "cf": 0.9 }, { "c": 2, "d": "Contains common English function words", "i": "metadata/file/profile/language::lang-english--atom-2", "o": 2300, "z": 3, "cf": 0.8 } ], "ln": 2175, "col": 1, "line": 73 }, { "b": "z!9A^vpJ!day]g@Bx-*dAX5tHx(!x2zG4jCwmoI0vr(c:auZ\u0026]w)l#}iV}TjazbLjaz8:gzxJpYpEESUmOc3xl@OHvarR^Hz!rQ5wPR#ojS)@.t).X%arU=DwO2j/vrb^[B2\u003eBWx(!x2wnbK}txs[befG1QA:q@[jS)%m3jm)#arR)KlT+7Fxk.*8v{%f@B8U@fBrCa5BytI0arR!pvrq", "n": [ { "c": 2, "d": "Contains an iteration loop", "i": "micro-behaviors/data/control-flow/analysis::iteration-loop-pattern", "o": 2630, "z": 10, "cf": 0.5 }, { "c": 1, "d": "EVM eth_call params field", "i": "objectives/command-and-control/channel/deaddrop/blockchain::evm-eth-call-params", "o": 2681, "z": 7, "cf": 0.9 } ], "ln": 2582, "col": 6, "line": 86 }, { "b": "wQb*Hwor9owGUY8ayv(tl}7DLnKVrvq-UmdarR^HarR^HarR!Az!9A^vpJ!Kvrcx}yH}=%e[5ZrwO#3bzG4jpA=LPld0fGvwM@[\u003cz/e]$wQdMjay]OtAaIgyBA}?pdjCPharR^HarR^Hv{%F2auZ\u0026?A+e/mxjVfkb4C56wOk}4x\u003equfefFe5dgdguarR^HarUf5ByeD^v{pc!vru6[z/PM6B0s)xwQ5rdzE+e9vruMt3lQDlarR^Hay!\u00264", "n": [ { "c": 1, "d": "NumPy array operation (array)", "i": "micro-behaviors/data/manipulation::numpy-array-operations--array", "o": 3097, "z": 8, "cf": 0.85 } ], "ln": 3033, "col": 28, "line": 99 }, { "b": "BAzKPwmYv!zE)u:3jm)#arR^HarUxgazbLjzddJejV%]izEET3C4z\u003cU3lQDlarR^HarR^HaAITkBy!V*b71oHwObU3Ep3t[z/PY6Byex0t{8oMDKp(rarR^HarR^HarR^HarR\u003c", "n": [ { "c": 1, "d": "String literal equality or membership check", "i": "micro-behaviors/data/control-flow/analysis::string-literal-equality-check", "o": 6876, "z": 11, "cf": 0.92 } ], "ln": 6844, "col": 60, "line": 202 }, { "b": "z!9A}uUTU2zx-u[arR^HarR^HarR^HzeS@@y*QT%By/IojS[iVBy!)3A::kwyiarhe[x9wAc0BAz!9A}uUTU2zyEhHzEWP}wHF#R3lQDlarR^HarR^HayYncB97#lauZ\u0026(xjrFWz/oYswPxgF3lQDlarR^HarR^HayYncB97#le]kDmwm6g(wmYN9zeS@@y*N", "n": [ { "c": 2, "d": "Serializes data with Python json.dumps()", "i": "micro-behaviors/data/serialize/json::json-dumps-call", "o": 8039, "z": 10, "cf": 0.9 } ], "ln": 7991, "col": 50, "line": 237 } ], "depth": 1, "facts": { "imp": [ [ "", "isinstance" ], [ "", "isinstance" ], [ "", "json.loads" ], [ "", "booster.save_raw(raw_format=\"json\").decode" ], [ "", "booster.save_raw" ], [ "", "int" ], [ "", "offsets.append" ], [ "", "tree_params.append" ], [ "", "node_acc[arr_key].append" ], [ "", "np.array" ], [ "", "tree.get" ], [ "", "cat_acc[\"categories\"].extend" ], [ "", "cat_acc[\"categories_nodes\"].extend" ], [ "", "tree.get" ], [ "", "cat_acc[\"categories_segments\"].extend" ], [ "", "tree.get" ], [ "", "cat_acc[\"categories_sizes\"].extend" ], [ "", "tree.get" ], [ "", "len" ], [ "", "np.array" ], [ "", "np.concatenate" ], [ "", "np.array" ], [ "", "np.array" ], [ "", "learner.get" ], [ "", "learner.get" ], [ "", "learner.get" ], [ "", "len" ], [ "", "range" ], [ "", "int" ], [ "", "int" ], [ "", "arrays[arr_key][start:end].tolist" ], [ "", "trees.append" ], [ "", "meta.get" ], [ "", "is_xgb" ], [ "", "estimator.get_booster" ], [ "", "json.loads" ], [ "", "booster.save_raw(raw_format=\"json\").decode" ], [ "", "booster.save_raw" ], [ "", "extract_columnar" ], [ "", "is_classifier" ], [ "", "fitted_state.get(f\"{prefix}__format__\", {}).get" ], [ "", "fitted_state.get" ], [ "", "bytearray" ], [ "", "json.dumps(model_json).encode" ], [ "", "json.dumps" ], [ "", "xgb.Booster" ], [ "", "booster.load_model" ], [ "", "is_classifier" ], [ "", "estimator.get_booster" ], [ "", "extract_columnar" ], [ "", "columnar.items" ], [ "", "hasattr" ], [ "", "np.asarray" ], [ "", "fitted_state.get(f\"{prefix}__format__\", {}).get" ], [ "", "fitted_state.get" ], [ "", "arrays.items" ], [ "", "k.startswith" ], [ "", "len" ], [ "", "rebuild_model_json" ], [ "", "bytearray" ], [ "", "json.dumps(model_json).encode" ], [ "", "json.dumps" ], [ "", "xgb.Booster" ], [ "", "booster.load_model" ], [ "", "Any" ], [ "", "BaseEstimator" ], [ "", "EstimatorHandler" ], [ "", "XGBClassifier" ], [ "", "XGBRegressor" ], [ "", "json" ], [ "", "numpy" ], [ "", "skeights._handler" ], [ "", "sklearn.base" ], [ "", "typing" ], [ "", "xgboost" ], [ "", "xgboost" ] ], "mbr": [ "arrays.items", "arrays.offsets", "booster.load_model", "booster.save_raw", "booster.save_raw().decode", "cat_acc.categories", "cat_acc.categories.extend", "cat_acc.categories_nodes", "cat_acc.categories_nodes.extend", "cat_acc.categories_segments", "cat_acc.categories_segments.extend", "cat_acc.categories_sizes", "cat_acc.categories_sizes.extend", "columnar.items", "estimator._Booster", "estimator.feature_importances_", "estimator.get_booster", "estimator.n_classes_", "fitted_state.get", "fitted_state.get().get", "gbm.model", "gbm.name", "json.dumps", "json.dumps().encode", "json.loads", "k.startswith", "learner.get", "learner.gradient_booster", "learner.learner_model_param", "learner.objective", "meta.feature_names", "meta.feature_types", "meta.gbm_name", "meta.gbtree_model_param", "meta.get", "meta.iteration_indptr", "meta.learner_model_param", "meta.objective", "meta.tree_info", "meta.tree_params", "meta.version", "model.gbtree_model_param", "model.iteration_indptr", "model.tree_info", "model.trees", "np.array", "np.asarray", "np.concatenate", "np.float32", "np.int32", "np.ndarray", "np.uint8", "offsets.append", "raw.learner", "raw.version", "tree.get", "tree.tree_param", "tree.tree_param.num_nodes", "tree_params.append", "trees.append", "xgb.Booster" ], "tgt": [ "_extract_columnar", "_is_classifier", "_is_xgb", "_rebuild_model_json", "arrays.items", "booster.load_model", "booster.save_raw", "booster.save_raw().decode", "bytearray", "cat_acc.categories.extend", "cat_acc.categories_nodes.extend", "cat_acc.categories_segments.extend", "cat_acc.categories_sizes.extend", "columnar.items", "estimator.get_booster", "fitted_state.get", "fitted_state.get().get", "hasattr", "int", "isinstance", "json.dumps", "json.dumps().encode", "json.loads", "k.startswith", "learner.get", "len", "meta.get", "np.array", "np.asarray", "np.concatenate", "offsets.append", "range", "tree.get", "tree_params.append", "trees.append", "xgb.Booster" ], "funcs": [ [ "_is_xgb", 676 ], [ "_is_classifier", 904 ], [ "_extract_columnar", 2177 ], [ "_rebuild_model_json", 4743 ], [ "handles", 6535 ], [ "collect_state", 6627 ], [ "restore_state", 7644 ], [ "extract_arrays", 8367 ], [ "restore_arrays", 9032 ] ], "metrics": { "ast": { "op.add": 4.0, "op.bor": 2.0, "op.sub": 2.0, "max_depth": 17.0, "bind_count": 42.0, "call_count": 64.0, "node_count": 2761.0, "member_count": 61.0, "op_density.add": 0.0, "op_density.bor": 0.0, "op_density.sub": 0.0, "identifier_count": 108.0, "member_depth_max": 3.0, "string_literal_count": 130.0, "array_literal_max_length": 10.0, "string_concat_chain_max_length": 2.0 }, "file": { "size": 9986.0, "entropy": 4.58, "size_bytes": 9986.0 }, "text": { "digit_ratio": 0.01, "space_count": 2233.0, "total_lines": 290.0, "char_entropy": 4.58, "unique_chars": 70.0, "string_density": 0.45, "ascii_art_lines": 10.0, "avg_line_length": 33.43, "max_line_length": 99.0, "empty_line_ratio": 0.19, "last_line_length": 66.0, "whitespace_ratio": 0.25, "most_common_ratio": 0.08, "identifier_density": 1.69, "line_length_stddev": 24.73, "normalized_string_count": 7.63, "repeated_char_sequences": 66.0, "suspicious_string_ratio": 0.02, "most_common_char_is_null": 0.0, "max_inline_whitespace_run": 2.0, "most_common_char_codepoint": 45.0, "suspicious_identifier_ratio": 0.05, "normalized_unique_identifiers": 13.2 }, "binds": { "count": 42.0 }, "calls": { "count": 64.0 }, "binary": { "overall_entropy": 4.58, "peak_region_bytes": 7938.0, "peak_region_entropy": 4.74 }, "source": { "class_count": 1.0, "function_count": 9.0 }, "imports": { "count": 12.0, "stdlib_count": 2.0, "stdlib_ratio": 0.17, "unique_modules": 12.0, "aliased_imports": 2.0, "third_party_count": 10.0, "third_party_ratio": 0.83 }, "members": { "count": 61.0 }, "strings": { "total": 130.0, "avg_length": 15.03, "max_length": 321.0, "avg_entropy": 3.03, "sql_strings": 2.0, "total_bytes": 1954.0, "entropy_stddev": 0.52, "shell_command_strings": 1.0 }, "comments": { "chars": 1229.0, "lines": 25.0, "total": 25.0, "to_code_ratio": 0.09 }, "functions": { "count": 10.0, "avg_params": 2.67, "max_params": 5.0, "length_stddev": 18.19, "avg_name_length": 13.11, "avg_length_lines": 23.44, "max_length_lines": 62.0, "min_length_lines": 2.0, "high_entropy_names": 1.0, "avg_param_name_length": 6.92, "density_per_100_lines": 3.1, "code_in_functions_ratio": 0.73 }, "identifiers": { "count": 108.0, "total": 489.0, "avg_length": 7.29, "max_length": 20.0, "min_length": 1.0, "avg_entropy": 2.31, "reuse_ratio": 0.22, "unique_count": 108.0, "length_stddev": 3.9, "has_digit_ratio": 0.03, "sequential_names": 5.0, "single_char_count": 6.0, "single_char_ratio": 0.06, "high_entropy_count": 3.0, "high_entropy_ratio": 0.03, "all_lowercase_ratio": 0.87, "all_uppercase_ratio": 0.03, "numeric_suffix_count": 3.0, "underscore_prefix_count": 9.0 } } }, "id": 15, "mol": "H(Db₂)", "path": "skeights-0.4.0-py3-none-any.whl!!skeights/_xgb.py", "pid": 0, "risk": 2, "sha": "e4cc122efa3e84eb1e5801c0ef223cac617b366283f36397199a86d1872cbece", "size": 9986, "traits": [ { "id": "micro-behaviors/data/manipulation::numpy-import", "conf": 0.9, "crit": 3, "desc": "Imports the NumPy array library", "spans": [ [ 404, 5 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--array", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (array)", "spans": [ [ 3097, 0 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations--ndarray", "conf": 0.85, "crit": 1, "desc": "NumPy array operation (ndarray)", "spans": [ [ 2239, 0 ] ] }, { "id": "micro-behaviors/data/serialize/json::json-loads-call", "conf": 0.9, "crit": 3, "desc": "Parses JSON data with Python", "spans": [ [ 2351, 10 ] ] }, { "id": "micro-behaviors/data/manipulation::numpy-array-operations", "conf": 0.85, "crit": 3, "desc": "Dense NumPy array construction and reduction", "spans": [ [ 2239, 10 ], [ 3097, 8 ] ] }, { "id": "micro-behaviors/data/manipulation::numeric-computation-library", "conf": 0.95, "crit": 3, "desc": "Module built on the numeric Python stack", "spans": [ [ 404, 5 ], [ 2239, 10 ], [ 3097, 8 ] ] } ], "type": "python" }, { "id": 18, "mol": "Md", "sha": "39d32806166128f90e89f8bf7981711c07949a2e288b79b741efd7c3d6f2cd32", "path": "skeights@0.4.0.registry.json", "risk": 1, "size": 806, "type": "registry", "depth": 1 } ], "omitted_files": 8, "v": "8" } }