PyPI / hypothesis / 6.170.5

hypothesis 6.170.5

Source
https://github.com/HypothesisWorks/hypothesis
Tag scanned
v6.170.5
Directory
hypothesis (only this part of the repository was scanned)
Compared with
v6.170.4 (0 signals introduced since)
Files
537 scanned, 16 skipped (binary, oversized, or unrecognised)
Signals
0 critical · 0 warn · 107 info
Scan time
30.8 s
LLM review
Reviewed by claude-haiku-5-5 (Anthropic): 47 of 47 warn and critical signals; 47 demoted to info.
Disclude version
4.1.0
Scanned (UTC)
2026-10-22 08:30

Signals

Ordered by severity, then signals introduced in this release. Hidden characters are shown as ⟨U+…⟩.

  1. info critical → info by review dynamic-execution hypothesis/docs/conf.py:185:1

    `exec` at module scope (runs on import) on a non-literal expression (ast pass, confidence 0.80)

    _version_file = root.joinpath("src", "hypothesis", "version.py")
    exec(_version_file.read_text(encoding="utf-8"), _d)
    version = _d["__version__"]
    release = _d["__version__"]
    likely benign LLM, confidence 0.85 docs/conf.py execs the package's own version.py to read the version string.
    Reasoning

    Sphinx conf.py exec-ing the project's own version.py to read __version__ is a common legitimate idiom; the path is built from the repo root, not from untrusted input. Flagged by the scanner only because exec is non-literal.

  2. line length 1436 characters (raw pass, confidence 0.50)

    The following notable open-source projects use Hypothesis to test their code: `pytorch <https://github.com/pytorch/pytorch>`_, `jax <https://github.com/jax-ml/jax>`_, `PyPy <https://github.com/pypy/pypy>`_, `numpy <https://github.com/numpy/numpy>`_, `pandas <https://github.com/pandas-dev/pandas>`_, `attrs <https://gith
  3. info dynamic-execution hypothesis/scripts/basic-test.sh:26:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    # Run all the no-extra-dependency tests for this version (except slow nocover tests)
    $PYTEST tests/cover tests/pytest
    
    # Run tests for each extra module while the requirements are installed
  4. info dynamic-execution hypothesis/scripts/basic-test.sh:30:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install ".[pytz, dateutil, zoneinfo]"
    $PYTEST tests/datetime/
    pip uninstall -y pytz python-dateutil
  5. info dynamic-execution hypothesis/scripts/basic-test.sh:34:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install ".[dpcontracts]"
    $PYTEST tests/dpcontracts/
    pip uninstall -y dpcontracts
  6. info dynamic-execution hypothesis/scripts/basic-test.sh:40:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install "$(grep 'fakeredis==' ../requirements/coverage.txt)"
    $PYTEST tests/redis/
    pip uninstall -y redis fakeredis
  7. info dynamic-execution hypothesis/scripts/basic-test.sh:44:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install "$(grep 'typing-extensions==' ../requirements/coverage.txt)"
    $PYTEST tests/typing_extensions/
    pip uninstall -y typing_extensions
  8. info dynamic-execution hypothesis/scripts/basic-test.sh:49:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install "$(grep -m 1 -oE 'lark>=([0-9.]+)' ../hypothesis/pyproject.toml | tr '>' =)"
    $PYTEST -Wignore tests/lark/
    pip install "$(grep 'lark==' ../requirements/coverage.txt)"
    $PYTEST tests/lark/
  9. info dynamic-execution hypothesis/scripts/basic-test.sh:51:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install "$(grep 'lark==' ../requirements/coverage.txt)"
    $PYTEST tests/lark/
    pip uninstall -y lark
  10. info dynamic-execution hypothesis/scripts/basic-test.sh:56:3

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

      pip install ".[codemods,cli]"
      $PYTEST tests/codemods/
      pip uninstall -y libcst click
  11. info dynamic-execution hypothesis/scripts/basic-test.sh:62:3

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

      pip install "$(grep -E 'black(==| @)' ../requirements/coverage.txt)"
      $PYTEST tests/ghostwriter/
      pip uninstall -y black numpy
    fi
  12. info dynamic-execution hypothesis/scripts/basic-test.sh:70:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    
    $PYTEST tests/nocover/
    
    # Run some tests without docstrings or assertions, to catch bugs
  13. info dynamic-execution hypothesis/scripts/basic-test.sh:74:1

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    # like issue #822 in one of the test decorators.  See also #1541.
    PYTHONOPTIMIZE=2 $PYTEST \
        -W'ignore:assertions not in test modules or plugins will be ignored because assert statements are not executed by the underlying Python interpreter:pytest.PytestConfigWarning' \
  14. info dynamic-execution hypothesis/scripts/basic-test.sh:89:5

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

        pip install "$NUMPY"
        $PYTEST tests/array_api
        $PYTEST tests/numpy
  15. info dynamic-execution hypothesis/scripts/basic-test.sh:90:5

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

        $PYTEST tests/array_api
        $PYTEST tests/numpy
    
        pip install "$(grep 'pandas==' ../requirements/coverage.txt)"
  16. info dynamic-execution hypothesis/scripts/basic-test.sh:93:5

    command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

        pip install "$(grep 'pandas==' ../requirements/coverage.txt)"
        $PYTEST tests/pandas
    esac
  17. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    # like issue #822 in one of the test decorators.  See also #1541.
    PYTHONOPTIMIZE=2 $PYTEST \
        -W'ignore:assertions not in test modules or plugins will be ignored because assert statements are not executed by the underlying Python interpreter:pytest.PytestConfigWarning' \
  18. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install ".[pytz, dateutil, zoneinfo]"
    $PYTEST tests/datetime/
    pip uninstall -y pytz python-dateutil
  19. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install ".[dpcontracts]"
    $PYTEST tests/dpcontracts/
    pip uninstall -y dpcontracts
  20. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install attrs
    $PYTEST tests/attrs/
    pip uninstall -y attrs
  21. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install scipy
    $PYTEST tests/scipy/
    pip uninstall -y scipy
  22. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install "$(grep 'typing-extensions==' ../requirements/coverage.txt)"
    $PYTEST tests/redis/
    pip uninstall -y redis fakeredis
  23. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    
    $PYTEST tests/typing_extensions/
    if [ "$HYPOTHESIS_PROFILE" != "crosshair" ]; then
      pip uninstall -y typing-extensions
  24. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install "$(grep 'annotated-types==' ../requirements/coverage.txt)"
    $PYTEST tests/test_annotated_types.py
    pip uninstall -y annotated-types
  25. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install "$(grep -m 1 -oE 'lark>=([0-9.]+)' ../hypothesis/pyproject.toml | tr '>' =)"
    $PYTEST -Wignore tests/lark/
    pip install "$(grep 'lark==' ../requirements/coverage.txt)"
    $PYTEST tests/lark/
  26. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

    pip install "$(grep 'lark==' ../requirements/coverage.txt)"
    $PYTEST tests/lark/
    pip uninstall -y lark
  27. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

      pip install ".[codemods,cli]"
      $PYTEST tests/codemods/
    
      if [ "$(python -c 'import sys; print(sys.version_info[:2] == (3, 11))')" = "True" ] ; then
  28. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

      pip install "$(grep -E 'black(==| @)' ../requirements/coverage.txt)"
      $PYTEST tests/patching/
      pip uninstall -y libcst
  29. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

      pip install attrs
      $PYTEST tests/ghostwriter/
      pip uninstall -y attrs
      pip uninstall -y black
  30. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

          pip install .
          $PYTEST --count=2 --repeat-scope=session tests/numpy tests/crosshair
          # ...but running twice takes time, don't overdo it
          $PYTEST tests/array_api
  31. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

          # ...but running twice takes time, don't overdo it
          $PYTEST tests/array_api
        else
          $PYTEST tests/array_api tests/numpy
  32. command name is a variable (`$PYTEST`) that this file sets only to plain text (ast pass, confidence 0.40)

        else
          $PYTEST tests/array_api tests/numpy
        fi
      fi
  33. info warn → info by review frame-introspection hypothesis/src/hypothesis/control.py:50:13

    `inspect.currentframe` — call-stack frame introspection (ast pass, confidence 0.70)

            )
        frame = inspect.currentframe()
        where = _calling_function_location("reject", frame)
        if currently_in_test_context():
    likely benign LLM, confidence 0.90 Captures the calling frame to report where reject() was invoked.
    Reasoning

    Hypothesis uses inspect.currentframe to locate the caller for error reporting in reject(); this is ordinary library behaviour.

  34. info warn → info by review frame-introspection hypothesis/src/hypothesis/control.py:78:17

    `inspect.currentframe` — call-stack frame introspection (ast pass, confidence 0.70)

        if observability_enabled() or not condition:
            frame = inspect.currentframe()
            where = _calling_function_location("assume", frame)
            if observability_enabled() and currently_in_test_context():
    likely benign LLM, confidence 0.90 Captures the calling frame to report where assume() was invoked.
    Reasoning

    Same caller-location diagnostic pattern in assume(); benign introspection for error messages.

  35. info warn → info by review decoder-decompress-payload hypothesis/src/hypothesis/core.py:442:23

    file imports decoder module(s) base64, zlib and calls `.decompress()` — embedded payload decompressed at runtime (ast pass, confidence 0.75)

            try:
                decoded = zlib.decompress(decoded[1:])
            except zlib.error as err:
                raise InvalidArgument(
    likely benign LLM, confidence 0.85 Decodes and decompresses a reproduction blob for replaying Hypothesis failures.
    Reasoning

    This is decoding a reproduction blob (base64 then zlib) from a user-supplied @reproduce_failure string, with a zlib.error handler. It is a documented feature for replaying failing examples, not a hidden payload run at import.

  36. info warn → info by review dynamic-execution hypothesis/src/hypothesis/extra/ghostwriter.py:293:17

    `compile` called on a non-literal expression (ast pass, confidence 0.70)

                with contextlib.suppress(SyntaxError):
                    compile(repr(st.just(param.default)), "<string>", "eval")
                    elements.insert(0, param.default)
            if elements or types:
    likely benign LLM, confidence 0.85 Syntax-checks a generated strategy repr for default parameter values.
    Reasoning

    compile of repr(st.just(default)) inside a suppress(SyntaxError) is a syntax validity check on generated source text, not executing untrusted input.

  37. info warn → info by review dynamic-execution hypothesis/src/hypothesis/extra/ghostwriter.py:719:9

    `compile` called on a non-literal expression (ast pass, confidence 0.70)

            r = re.sub(r"(lambda.*?: )(<unknown>)([,)])", r"\1...\3", r)
            compile(r, "<string>", "eval")
            # Finally, try to work out the imports we need for builds(), .map(),
            # .filter(), and .flatmap() to work without NameError
    likely benign LLM, confidence 0.85 Syntax-checks generated strategy expression text.
    Reasoning

    Compiling the generated code string with mode eval only checks syntax of ghostwriter output; compile does not execute code.

  38. info warn → info by review dynamic-execution hypothesis/src/hypothesis/extra/ghostwriter.py:1837:13

    `compile` called on a non-literal expression (ast pass, confidence 0.70)

                # executed; so you still shouldn't ghostwrite for hostile code.
                compile(repr(identity), "<string>", "exec")
            except SyntaxError:
                identity = repr(identity)
    likely benign LLM, confidence 0.85 Syntax-checks a repr of an identity value during test generation.
    Reasoning

    compile of repr(identity) is a syntax check that falls back to repr on SyntaxError; the comment shows the author is aware of hostile-code concerns. Compile alone does not run code.

  39. identifier `aᵏ` mixes scripts: Latin + Other (in string/comment) (raw pass, confidence 0.40)

        # The sum of a geometric series is given by (ref: wikipedia):
        #     ᵐ∑ₖ₌₀ aᵏ = (aᵐ⁺¹ - 1) / (a - 1)
        #               = S(m) / S(0)
        # assuming a != 1 and using the definition
  40. identifier `aᵐ` mixes scripts: Latin + Other (in string/comment) (raw pass, confidence 0.40)

        # The sum of a geometric series is given by (ref: wikipedia):
        #     ᵐ∑ₖ₌₀ aᵏ = (aᵐ⁺¹ - 1) / (a - 1)
        #               = S(m) / S(0)
        # assuming a != 1 and using the definition
  41. identifier `aᵐ` mixes scripts: Latin + Other (in string/comment) (raw pass, confidence 0.40)

        # assuming a != 1 and using the definition
        #         S(m) := aᵐ⁺¹ - 1.
        # The sum we want, starting from a number n [0 <= n <= m] rather than zero, is
        #     ᵐ∑ₖ₌ₙ aᵏ = ᵐ∑ₖ₌₀ aᵏ - ⁿ⁻¹∑ₖ₌₀ aᵏ = S(m) / S(0) - S(n - 1) / S(0)
  42. identifier `aᵏ` mixes scripts: Latin + Other (in string/comment) (raw pass, confidence 0.40)

        # The sum we want, starting from a number n [0 <= n <= m] rather than zero, is
        #     ᵐ∑ₖ₌ₙ aᵏ = ᵐ∑ₖ₌₀ aᵏ - ⁿ⁻¹∑ₖ₌₀ aᵏ = S(m) / S(0) - S(n - 1) / S(0)
        def S(n):
            return alphabet_size ** (n + 1) - 1
  43. identifier `aᵏ` mixes scripts: Latin + Other (in string/comment) (raw pass, confidence 0.40)

        # The sum we want, starting from a number n [0 <= n <= m] rather than zero, is
        #     ᵐ∑ₖ₌ₙ aᵏ = ᵐ∑ₖ₌₀ aᵏ - ⁿ⁻¹∑ₖ₌₀ aᵏ = S(m) / S(0) - S(n - 1) / S(0)
        def S(n):
            return alphabet_size ** (n + 1) - 1
  44. identifier `aᵏ` mixes scripts: Latin + Other (in string/comment) (raw pass, confidence 0.40)

        # The sum we want, starting from a number n [0 <= n <= m] rather than zero, is
        #     ᵐ∑ₖ₌ₙ aᵏ = ᵐ∑ₖ₌₀ aᵏ - ⁿ⁻¹∑ₖ₌₀ aᵏ = S(m) / S(0) - S(n - 1) / S(0)
        def S(n):
            return alphabet_size ** (n + 1) - 1
  45. info warn → info by review frame-introspection hypothesis/src/hypothesis/internal/conjecture/junkdrawer.py:316:13

    `sys._getframe` — call-stack frame introspection (ast pass, confidence 0.70)

        """
        frame = sys._getframe(2)
        size = 1
        while frame:
    likely benign LLM, confidence 0.90 Walks stack frames to compute a size estimate.
    Reasoning

    sys._getframe used to size a call stack for internal utility; ordinary introspection in a testing library.

  46. identifier `ˆøπ` mixes scripts: Other + Latin + Greek (in string/comment) (raw pass, confidence 0.40)

        # common unicode characters
        "Ω≈ç√∫˜µ≤≥÷åß∂ƒ©˙∆˚¬…æœ∑´®†¥¨ˆøπ“‘¡™£¢∞§¶•ªº–≠¸˛Ç◊ı˜Â¯˘¿ÅÍÎÏ˝ÓÔ⟨U+F8FF⟩ÒÚÆ☃Œ„´‰ˇÁ¨ˆØ∏”’`⁄€‹›fifl‡°·‚—±",
        # characters which increase in length when lowercased
  47. identifier `ˇÁ` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

        # common unicode characters
        "Ω≈ç√∫˜µ≤≥÷åß∂ƒ©˙∆˚¬…æœ∑´®†¥¨ˆøπ“‘¡™£¢∞§¶•ªº–≠¸˛Ç◊ı˜Â¯˘¿ÅÍÎÏ˝ÓÔ⟨U+F8FF⟩ÒÚÆ☃Œ„´‰ˇÁ¨ˆØ∏”’`⁄€‹›fifl‡°·‚—±",
        # characters which increase in length when lowercased
  48. identifier `ˆØ` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

        # common unicode characters
        "Ω≈ç√∫˜µ≤≥÷åß∂ƒ©˙∆˚¬…æœ∑´®†¥¨ˆøπ“‘¡™£¢∞§¶•ªº–≠¸˛Ç◊ı˜Â¯˘¿ÅÍÎÏ˝ÓÔ⟨U+F8FF⟩ÒÚÆ☃Œ„´‰ˇÁ¨ˆØ∏”’`⁄€‹›fifl‡°·‚—±",
        # characters which increase in length when lowercased
  49. identifier `æœÆŒffʤʨß` mixes scripts: Latin + Other (in string/comment) (raw pass, confidence 0.40)

        # ligatures
        "æœÆŒffʤʨß",
        # emoticons
        "(╯°□°)╯︵ ┻━┻)",
  50. identifier `ʇǝɯɐ` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

        # upsidown text
        "ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥",
        # reserved strings in windows
        "NUL",
  51. identifier `ʇᴉs` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

        # upsidown text
        "ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥",
        # reserved strings in windows
        "NUL",
  52. identifier `ɹolop` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

        # upsidown text
        "ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥",
        # reserved strings in windows
        "NUL",
  53. identifier `ɯnsdᴉ` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

        # upsidown text
        "ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥",
        # reserved strings in windows
        "NUL",
  54. identifier `ɯǝɹo` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

        # upsidown text
        "ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥",
        # reserved strings in windows
        "NUL",
  55. identifier `ͅi` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

    �̲e͇̣̰̦̬͎ ̢̼̻̱̘h͚͎͙̜̣̲ͅi̦̲̣̰̤v̻͍e̺̭̳̪̰-m̢iͅn̖̺̞̲̯̰d̵̼̟͙̩̼̘̳ ̞̥̱̳̭r̛̗̘e͙p͠r̼̞̻̭̗e̺̠̣͟s̘͇̳͍̝͉e͉̥̯̞̲͚̬͜ǹ̬͎͎̟̖͇̤t͍̬̤͓̼̭͘ͅi̪̱n͠g̴͉ ⟨U+034F⟩͉ͅc̬̟h͡a̫̻̯͘o̫̟̖͍̙̝͉s̗̦̲.̨̹͈̣",
  56. identifier `iͅn` mixes scripts: Latin + Other (in string/comment) (raw pass, confidence 0.40)

    �̜̣̲ͅi̦̲̣̰̤v̻͍e̺̭̳̪̰-m̢iͅn̖̺̞̲̯̰d̵̼̟͙̩̼̘̳ ̞̥̱̳̭r̛̗̘e͙p͠r̼̞̻̭̗e̺̠̣͟s̘͇̳͍̝͉e͉̥̯̞̲͚̬͜ǹ̬͎͎̟̖͇̤t͍̬̤͓̼̭͘ͅi̪̱n͠g̴͉ ⟨U+034F⟩͉ͅc̬̟h͡a̫̻̯͘o̫̟̖͍̙̝͉s̗̦̲.̨̹͈̣",
  57. identifier `ͅi` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

    �̲͚̬͜ǹ̬͎͎̟̖͇̤t͍̬̤͓̼̭͘ͅi̪̱n͠g̴͉ ⟨U+034F⟩͉ͅc̬̟h͡a̫̻̯͘o̫̟̖͍̙̝͉s̗̦̲.̨̹͈̣",
  58. identifier `ͅc` mixes scripts: Other + Latin (in string/comment) (raw pass, confidence 0.40)

    �͇̤t͍̬̤͓̼̭͘ͅi̪̱n͠g̴͉ ⟨U+034F⟩͉ͅc̬̟h͡a̫̻̯͘o̫̟̖͍̙̝͉s̗̦̲.̨̹͈̣",
  59. info warn → info by review frame-introspection hypothesis/src/hypothesis/internal/coverage.py:74:18

    `sys._getframe` — call-stack frame introspection (ast pass, confidence 0.70)

            # stack frames up.
            caller = sys._getframe(depth + 2)
            fname = pretty_file_name(caller.f_code.co_filename)
            local_description = f"{name} at {fname}:{caller.f_lineno}"
    likely benign LLM, confidence 0.90 Reads the caller frame to build a coverage description label.
    Reasoning

    Caller frame lookup to label coverage-related descriptions; benign library introspection.

  60. info warn → info by review dynamic-execution hypothesis/src/hypothesis/internal/lambda_sources.py:265:20

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

        if not f_code.co_freevars and not referenced_modules:
            compiled = eval(source, f_globals)
        else:
            if f_code.co_freevars:
    likely benign LLM, confidence 0.85 Evals reconstructed lambda source to rebuild a function for reporting.
    Reasoning

    Evaluates reconstructed lambda source recovered from the library's own source inspection, to rebuild a function object. This is a known pattern for reconstructing lambdas for test-case reporting; the source comes from the code being tested, not an attacker channel.

  61. info warn → info by review dynamic-execution hypothesis/src/hypothesis/internal/lambda_sources.py:298:9

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

            )
            exec(exec_str, f_globals)
            compiled = f_globals["__construct_lambda"]()
    likely benign LLM, confidence 0.80 Execs generated code to reconstruct a lambda with closure variables.
    Reasoning

    Execs a generated construction stub to rebuild a lambda with its closure and globals. Same library-internal reconstruction pattern; no external untrusted input is evident in the snippet.

  62. info warn → info by review dynamic-execution hypothesis/src/hypothesis/internal/reflection.py:367:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        assert isinstance(source, str)
        exec(source, result.__dict__)
        eval_cache[source] = result
        return result
    likely benign LLM, confidence 0.80 Executes reconstructed function source into a namespace with caching.
    Reasoning

    Execs source text for a function being re-created from its own source in the library's reflection helper; the source originates from the user's own code under test, consistent with a legitimate eval cache.

  63. info warn → info by review frame-introspection hypothesis/src/hypothesis/internal/scrutineer.py:114:13

    `sys.settrace` — call-stack frame introspection (ast pass, confidence 0.70)

            if not hasattr(sys, "monitoring"):  # pragma: no cover  # only on Python < 3.12
                sys.settrace(self.trace)
                return self
    likely benign LLM, confidence 0.90 Installs a trace function for path analysis on older Python versions.
    Reasoning

    sys.settrace used in a coverage/scrutineer tracer for Python versions below 3.12, explicitly marked as such; standard profiling/tracing practice.

  64. info warn → info by review frame-introspection hypothesis/src/hypothesis/internal/scrutineer.py:137:13

    `sys.settrace` — call-stack frame introspection (ast pass, confidence 0.70)

            if not hasattr(sys, "monitoring"):  # pragma: no cover  # only on Python < 3.12
                sys.settrace(None)
                return
    likely benign LLM, confidence 0.90 Removes the trace function on exit from the tracer context.
    Reasoning

    Clearing the trace function on exit is the matching teardown for the settrace call; benign.

  65. info warn → info by review frame-introspection hypothesis/src/hypothesis/strategies/_internal/strategies.py:102:31

    `sys._getframe` — call-stack frame introspection (ast pass, confidence 0.70)

            return location
        frame: FrameType | None = sys._getframe(1)
        while frame is not None and is_hypothesis_file(frame.f_code.co_filename):
            frame = frame.f_back
    likely benign LLM, confidence 0.93 Walks the call stack to find the first non-Hypothesis caller for location reporting.
    Reasoning

    sys._getframe walks up the stack skipping Hypothesis-internal frames to report the user's call location. This is a standard, documented introspection technique in a testing library, and the snippet shows no hidden or malicious behaviour.

  66. info warn → info by review frame-introspection hypothesis/src/hypothesis/strategies/_internal/types.py:227:37

    `sys._getframe` — call-stack frame introspection (ast pass, confidence 0.70)

        found_loc: str | None = None
        frame: types.FrameType | None = sys._getframe()
        while frame is not None:
            loc = f"{frame.f_code.co_filename}:{frame.f_lineno}"
    likely benign LLM, confidence 0.93 Walks frames to record the source location of a type-related definition.
    Reasoning

    sys._getframe walks the frame chain to locate where a strategy is defined, which is used for diagnostics. This is ordinary library introspection with no sign of concealment.

  67. info critical → info by review dynamic-execution hypothesis/tests/codemods/test_codemod_cli.py:40:12

    `subprocess.run` with `shell=True` and a non-literal command — runtime-determined shell invocation (ast pass, confidence 0.85)

    def run(command, *, cwd=None, input=None):
        return subprocess.run(
            command,
            input=input,
    likely benign LLM, confidence 0.80 Test helper that runs a shell command for codemod CLI tests.
    Reasoning

    A test helper wraps subprocess.run with shell=True on a caller-supplied command. The command comes from test code, not untrusted input, so the risk is limited to test tooling. The critical severity overstates it.

  68. info warn → info by review frame-introspection hypothesis/tests/conjecture/test_junkdrawer.py:201:16

    `inspect.stack` — call-stack frame introspection (ast pass, confidence 0.70)

    def recur(i):
        assert len(inspect.stack(0)) == stack_depth_of_caller()
        if i >= 1:
            recur(i - 1)
    likely benign LLM, confidence 0.92 Test asserting stack depth via inspect.stack in a recursive function.
    Reasoning

    inspect.stack(0) is used in a test to check stack depth in a recursive helper. This is a normal test technique.

  69. info warn → info by review dynamic-execution hypothesis/tests/cover/test_feature_flags.py:58:14

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

        assert not flags.is_enabled("off")
        flags2 = eval(repr(flags))
        assert flags2.is_enabled("on")
        assert not flags2.is_enabled("off")
    likely benign LLM, confidence 0.90 Round-trips a feature flags object through repr and eval in a test.
    Reasoning

    eval(repr(flags)) is a round-trip serialization test over the object's own repr, not untrusted input.

  70. info warn → info by review dynamic-execution hypothesis/tests/cover/test_feature_flags.py:72:14

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

    
        flags2 = eval(repr(flags))
    
        for f in features:
    likely benign LLM, confidence 0.90 Round-trips feature flags through repr and eval in a test.
    Reasoning

    Same round-trip test pattern using eval on the object's own repr output.

  71. info warn → info by review frame-introspection hypothesis/tests/cover/test_observability.py:337:13

    `inspect.currentframe` — call-stack frame introspection (ast pass, confidence 0.70)

        # the line `offset` lines below the `def` statement of the calling function
        frame = inspect.currentframe().f_back
        return f"{__file__}:{frame.f_code.co_firstlineno + offset}"
    likely benign LLM, confidence 0.92 Test helper computing the caller's line number via frame introspection.
    Reasoning

    inspect.currentframe().f_back is used in a test helper to compute the expected line number of a calling function. Benign test scaffolding.

  72. info warn → info by review dynamic-execution hypothesis/tests/cover/test_pretty.py:596:14

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

        ]:
            r2 = eval(pretty.pretty(r), globals())
            assert r.pattern == r2.pattern
            assert r.flags == r2.flags
    likely benign LLM, confidence 0.90 Evaluates pretty-printed regex output to verify round-tripping.
    Reasoning

    eval of pretty-printed repr output checks that the printer round-trips regex objects. This is a test of the pretty printer, operating on values the test constructs.

  73. info warn → info by review dynamic-execution hypothesis/tests/cover/test_pretty.py:625:9

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

        assert float_to_lex(obj) == float_to_lex(
            eval(rep, {"struct": struct, "nan": float("nan")})
        )
    likely benign LLM, confidence 0.90 Evaluates a repr string in a restricted namespace for float round-trip checks.
    Reasoning

    eval of a repr string with a constrained namespace checks float round-tripping in a test. The inputs are test-controlled.

  74. info warn → info by review dynamic-execution hypothesis/tests/cover/test_pretty.py:686:26

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

    def test_pretty_prints_enums_as_code(rep):
        assert pretty.pretty(eval(rep)) == rep
    likely benign LLM, confidence 0.90 Evaluates enum repr strings from parametrized test inputs.
    Reasoning

    eval(rep) over parametrized enum representations asserts that the pretty printer emits valid code. Test inputs are fixed in the test file.

  75. info warn → info by review dynamic-execution hypothesis/tests/cover/test_pretty.py:770:12

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

        assert got == f"{x:#_x}"  # hexadecimal with underscores
        assert eval(got) == x
    likely benign LLM, confidence 0.90 Evaluates a formatted hexadecimal string to verify its value.
    Reasoning

    eval of formatted hex output checks that the formatting is valid Python for a known value. Benign test assertion.

  76. info warn → info by review decoder-import-with-exec hypothesis/tests/cover/test_reproduce_failure.py:146:20

    file imports decoder module(s) base64, zlib and calls `exec`/`eval`/`compile` — multi-stage payload shape (ast pass, confidence 0.80)

        extract = exp.search(notes)
        reproduction = eval(extract.group(0))
        test = reproduction(test)
    likely benign LLM, confidence 0.72 Decodes a reproduce_failure blob from notes and evals it to rebuild a test.
    Reasoning

    The decoder-plus-exec shape matches the multi-stage payload signal. Here it is the documented @reproduce_failure mechanism, which decodes a base64/zlib blob from test notes and rebuilds a test. That is a legitimate Hypothesis feature, though the blob is decoded and evaluated, so some caution applies.

  77. info warn → info by review dynamic-execution hypothesis/tests/cover/test_reproduce_failure.py:146:20

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

        extract = exp.search(notes)
        reproduction = eval(extract.group(0))
        test = reproduction(test)
    likely benign LLM, confidence 0.72 Same eval of a decoded reproduction blob as the paired decoder finding.
    Reasoning

    This is the same eval call as the decoder finding, flagged separately as dynamic execution. It belongs to the documented reproduce_failure feature and the input is derived from the library's own encoding.

  78. identifier `te02тест49st` contains homoglyph candidates: е (0435)→e, с (0441)→c (in string/comment) (raw pass, confidence 0.35)

        with pytest.raises(InvalidArgument):
            check_can_generate_examples(characters(include_characters="te02тест49st"))
  79. identifier `te02тест49st` mixes scripts: Latin + Cyrillic (in string/comment) (raw pass, confidence 0.40)

        with pytest.raises(InvalidArgument):
            check_can_generate_examples(characters(include_characters="te02тест49st"))
  80. identifier `te02тест49st` contains homoglyph candidates: е (0435)→e, с (0441)→c (in string/comment) (raw pass, confidence 0.35)

    def test_whitelisted_characters_overlap_blacklisted_characters():
        good_chars = "te02тест49st"
        bad_chars = "ts94тсет"
        with pytest.raises(InvalidArgument) as exc:
  81. identifier `te02тест49st` mixes scripts: Latin + Cyrillic (in string/comment) (raw pass, confidence 0.40)

    def test_whitelisted_characters_overlap_blacklisted_characters():
        good_chars = "te02тест49st"
        bad_chars = "ts94тсет"
        with pytest.raises(InvalidArgument) as exc:
  82. identifier `ts94тсет` contains homoglyph candidates: с (0441)→c, е (0435)→e (in string/comment) (raw pass, confidence 0.35)

        good_chars = "te02тест49st"
        bad_chars = "ts94тсет"
        with pytest.raises(InvalidArgument) as exc:
            check_can_generate_examples(
  83. identifier `ts94тсет` mixes scripts: Latin + Cyrillic (in string/comment) (raw pass, confidence 0.40)

        good_chars = "te02тест49st"
        bad_chars = "ts94тсет"
        with pytest.raises(InvalidArgument) as exc:
            check_can_generate_examples(
  84. identifier `teтестst` contains homoglyph candidates: е (0435)→e, с (0441)→c (in string/comment) (raw pass, confidence 0.35)

    def test_whitelisted_characters_override():
        good_characters = "teтестst"
        st = characters(
            min_codepoint=ord("0"),
  85. identifier `teтестst` mixes scripts: Latin + Cyrillic (in string/comment) (raw pass, confidence 0.40)

    def test_whitelisted_characters_override():
        good_characters = "teтестst"
        st = characters(
            min_codepoint=ord("0"),
  86. identifier `te02тест49st` contains homoglyph candidates: е (0435)→e, с (0441)→c (in string/comment) (raw pass, confidence 0.35)

    def test_blacklisted_characters():
        bad_chars = "te02тест49st"
        st = characters(
            min_codepoint=ord("0"), max_codepoint=ord("9"), exclude_characters=bad_chars
  87. identifier `te02тест49st` mixes scripts: Latin + Cyrillic (in string/comment) (raw pass, confidence 0.40)

    def test_blacklisted_characters():
        bad_chars = "te02тест49st"
        st = characters(
            min_codepoint=ord("0"), max_codepoint=ord("9"), exclude_characters=bad_chars
  88. info warn → info by review unicode-mixed-script hypothesis/tests/cover/test_unicode_identifiers.py:37:1

    identifier `is_approx_π` mixes scripts: Latin + Greek (raw pass, confidence 0.80)

    
    is_approx_π = lambda x: x == 3.1415
    likely benign LLM, confidence 0.90 Defines a lambda with a Greek letter in its identifier to test unicode handling.
    Reasoning

    A deliberate Unicode identifier mixing Latin and Greek is the test subject, which checks that the library handles unicode identifiers. It is intentional, not obfuscation.

  89. info warn → info by review unicode-mixed-script hypothesis/tests/cover/test_unicode_identifiers.py:41:44

    identifier `is_approx_π` mixes scripts: Latin + Greek (raw pass, confidence 0.80)

    def test_can_handle_unicode_identifier_in_same_line_as_lambda_def():
        assert get_pretty_function_description(is_approx_π) == "lambda x: x == 3.1415"
    likely benign LLM, confidence 0.90 Uses the mixed-script unicode identifier in a description test.
    Reasoning

    Same deliberate mixed-script identifier, used to test function description output for unicode names.

  90. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/recorded/magic_builtins.txt:112:5

    [markup prose] `eval` called on a string literal (ast pass, confidence 0.85)

        eval(source, globals, locals)
    likely benign LLM, confidence 0.80 Recorded example output containing an eval call in a test fixture file.
    Reasoning

    This is recorded ghostwriter output in a text fixture, showing eval on a string literal as an example of generated code. It is not executed by a scanner-visible runtime path, and the context is documentation or a recording.

  91. info warn → info by review decoder-import-with-exec hypothesis/tests/ghostwriter/test_expected_output.py:302:5

    file imports decoder module(s) base64 and calls `exec`/`eval`/`compile` — multi-stage payload shape (ast pass, confidence 0.80)

        assert actual == expected  # We got the expected source code
        exec(expected, {})  # and there are no SyntaxError or NameErrors
    likely benign LLM, confidence 0.93 Test helper executes generated Python source to check it compiles and runs without NameError.
    Reasoning

    Test file in Hypothesis ghostwriter suite; exec of generated source code that was already compared to expected output. The base64 import is incidental to a test harness, not a decoder pipeline.

  92. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_expected_output.py:302:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        assert actual == expected  # We got the expected source code
        exec(expected, {})  # and there are no SyntaxError or NameErrors
    likely benign LLM, confidence 0.92 exec of expected generated source in a test assertion.
    Reasoning

    exec on a variable holding expected generated code inside a test; the expression is test data, not attacker-controlled input.

  93. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_expected_output.py:317:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

            assert actual == expected
        exec(expected, {"not_set": not_set})
    likely benign LLM, confidence 0.92 Test executes generated source code with a fixed namespace.
    Reasoning

    Same test pattern executing generated code with a controlled namespace dict.

  94. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_expected_output.py:339:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        assert actual == expected  # We got the expected source code
        exec(expected, {})  # and there are no SyntaxError or NameErrors
    likely benign LLM, confidence 0.92 Test executes expected generated source for validity checking.
    Reasoning

    Repeated test pattern verifying generated code executes; no external input reaches exec.

  95. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:56:9

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        try:
            exec(source_code, namespace)
        except Exception:
            print(f"************\n{source_code}\n************")
    likely benign LLM, confidence 0.92 Test helper execs generated source code inside a try block.
    Reasoning

    Helper in a test module that execs generated source and prints it on failure; a normal verification idiom.

  96. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:206:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        source_code = ghostwriter.magic(socket)
        exec(source_code, {})
    likely benign LLM, confidence 0.92 Test execs output of ghostwriter.magic.
    Reasoning

    Test checks that ghostwriter-generated code runs; source comes from the library under test.

  97. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:213:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        source_code = ghostwriter.binary_operation(takes_frozensets)
        exec(source_code, {})
    likely benign LLM, confidence 0.92 Test execs output of ghostwriter.binary_operation.
    Reasoning

    Same generated-code verification pattern in a test.

  98. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:234:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        # Most importantly: the code should execute without NameError
        exec(source_code, {})
    likely benign LLM, confidence 0.92 Test execs generated source to check for NameError.
    Reasoning

    Test verifying generated code executes without NameError; benign.

  99. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:436:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        source_code = ghostwriter.binary_operation(compose_types)
        exec(source_code, {})
        # and also works with explicit identity element
        source_code = ghostwriter.binary_operation(compose_types, identity=type)
    likely benign LLM, confidence 0.92 Test execs binary_operation output.
    Reasoning

    Generated code from the library is exec'd in a test; benign test verification.

  100. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:439:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        source_code = ghostwriter.binary_operation(compose_types, identity=type)
        exec(source_code, {})
    likely benign LLM, confidence 0.92 Test execs binary_operation output with identity argument.
    Reasoning

    Same benign test verification of generated source.

  101. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:846:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        assert "one_of(" in source_code
        exec(source_code, {})
    likely benign LLM, confidence 0.92 Test execs generated source containing one_of.
    Reasoning

    Test execs one_of-containing generated source; benign.

  102. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:854:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        source_code = ghostwriter.ufunc(numpy.isnan)
        exec(source_code, {})
        # Also cover passing an explicit `annotate`, rather than the default None.
        source_code = ghostwriter.ufunc(numpy.isnan, annotate=True)
    likely benign LLM, confidence 0.92 Test execs ufunc-generated source.
    Reasoning

    Test execs ufunc generator output; benign.

  103. info warn → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter.py:857:5

    `exec` called on a non-literal expression (ast pass, confidence 0.70)

        source_code = ghostwriter.ufunc(numpy.isnan, annotate=True)
        exec(source_code, {})
    likely benign LLM, confidence 0.92 Test execs ufunc-generated source with annotate option.
    Reasoning

    Test execs ufunc generator output with annotate; benign.

  104. info critical → info by review dynamic-execution hypothesis/tests/ghostwriter/test_ghostwriter_cli.py:43:12

    `subprocess.run` with `shell=True` and a non-literal command — runtime-determined shell invocation (ast pass, confidence 0.85)

    def run(cmd, *, cwd=None):
        return subprocess.run(
            cmd, capture_output=True, shell=True, text=True, cwd=cwd, encoding="utf-8"
        )
    likely benign LLM, confidence 0.85 Test helper runs a shell command via subprocess with shell=True.
    Reasoning

    A small test helper wrapping subprocess with shell=True. Command strings are supplied by test code, so the risk is low, though shell=True with a non-literal command is a bad practice worth noting.

  105. info warn → info by review dynamic-execution hypothesis/tests/nocover/test_pretty_repr.py:102:16

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

        r = repr(strategy)
        via_eval = eval(r, strategy_globals)
        r2 = repr(via_eval)
        assert r == r2
    likely benign LLM, confidence 0.90 Test evals strategy repr string to check round-trip stability.
    Reasoning

    Test evaluates repr of Hypothesis strategies in a controlled globals dict to check round-trip repr; no untrusted input.

  106. info warn → info by review dynamic-execution hypothesis/tests/nocover/test_pretty_repr.py:116:17

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

    def test_sampled_transform_reprs(r):
        assert repr(eval(r, strategy_globals)) == r
    likely benign LLM, confidence 0.90 Test evals sampled strategy repr to compare against itself.
    Reasoning

    Parametrized test evaluating repr strings of sampled transforms; benign test code.

  107. info warn → info by review dynamic-execution hypothesis/tests/numpy/test_floor_ceil.py:35:18

    `eval` called on a non-literal expression (ast pass, confidence 0.70)

    def test_our_floor_and_ceil_avoid_numpy_rounding(value):
        a = np.array(eval(value))
        f = floor(a)
        c = ceil(a)
    likely benign LLM, confidence 0.80 A numpy floor/ceil test uses eval on a test parameter to build an array.
    Reasoning

    The eval call sits in a test function parameterized by value, most likely a test fixture that feeds literal or generated array expressions into floor/ceil comparisons. Eval on a test parameter is a poor practice and a dynamic-execution signal, but in a test file with no network, shell, or encoded payload involvement it is most plausibly a benign testing pattern. The doubt is that the value source is not shown.

Reproduce This Scan

Run disclude locally to verify. Add --format sarif for SARIF output. Add --llm (with an API key in the environment) to include the LLM review.

cargo install disclude --version 4.1.0
git clone https://github.com/HypothesisWorks/hypothesis hypothesis && cd hypothesis
git checkout v6.170.5
disclude scan --severity info --diff v6.170.4 hypothesis