wheel-crypto-scan

Reports crypto-relevant evidence found inside Python wheels, so the teams consuming a package index can see per-wheel FIPS risk before they ship it.

It gathers evidence. It does not decide compliance.

What it answers

The question it exists for: does this wheel use the system OpenSSL, or does it carry its own? A wheel that resolves libcrypto.so.3 from the host inherits the host's FIPS provider and crypto policy. A wheel that ships or statically links its own copy does not, and no amount of host configuration changes that.

There are three ways a wheel can carry its own OpenSSL, and all three are caught:

The third case is the one that matters most and the one a vendor-directory check alone misses. Run against three real builds of cryptography:

Fedora RPM build      DT_NEEDED libcrypto.so.3, libssl.so.3    64 symbols imported   -> system
PyPI 42.0.5           empty cryptography.libs/, no DT_NEEDED,  0 symbols exported    -> static
PyPI 3.4.8            no DT_NEEDED, no vendor directory,       0 symbols exported    -> static

For PyPI 42.0.5 the only evidence is the OpenSSL 3.2.1 banner in .rodata: the vendor directory is empty, nothing is declared, and the symbols are hidden by a version script.

What it explicitly does not do

• It never says "FIPS compliant." The verdict taxonomy has no passing class and cannot acquire one. A human makes that call.
• No LLM at runtime. Pure static analysis. The JSON is what gets fed to a model later, as a separate step.
• No dataflow or reachability analysis. It records the call site; it does not try to prove the call runs.
• No container images, no RPMs, no sdists. Wheels only.
• No network, except an explicitly requested --index-url download of the wheels.

Install and run

uv tool install .                       # or: uv run wheel-crypto-scan
wheel-crypto-scan scan /path/to/wheels -o index.jsonl --jobs 8
wheel-crypto-scan scan one.whl --format md
wheel-crypto-scan rules                 # the rule table, for review
wheel-crypto-scan schema                # the JSON Schema for the output

Useful flags: --jobs N, --cache-dir DIR / --no-cache, --resume, --evidence-level minimal|standard, --ruleset PATH, --from-file LIST, --index-url URL --download-dir DIR.

Triage the output with jq:

jq -r 'select(.verdict.conditions.openssl_linkage == "bundled") | .wheel.filename' index.jsonl
jq -r 'select(.verdict.class == "FIPS_BREAKING") | "\(.wheel.name) \(.verdict.reasons[0])"' index.jsonl
jq -r 'select(.verdict.class == "OPAQUE") | .wheel.filename' index.jsonl   # could not be read

Output

JSONL, one record per wheel. SCHEMA.md documents every field and the versioning rules; wheel-crypto-scan schema prints the machine-readable JSON Schema.

A wheel that could not be read is OPAQUE, never NO_CRYPTO_DETECTED. That distinction is enforced by a test asserting every recordable failure has a rule.

The ruleset

All policy lives in src/wheel_crypto_scan/data/ruleset.toml. Every package name, symbol, string, crate, library and verdict is data, each with a why explaining in plain language what it is and why it is flagged. A crypto engineer can review and edit it without reading any Python. wheel-crypto-scan rules renders it for review.

Bump ruleset_version after editing: it is part of the scan cache key, so bumping it is what makes previously scanned wheels get re-evaluated.

Determinism

Same wheel in, byte-identical JSONL out. Verified on a 100-wheel corpus to be identical across repeat runs, --jobs 1 vs --jobs 8, cold vs warm cache, and Python 3.11, 3.12, 3.13 and 3.14. Output is sorted, ASCII-only, float-free, and contains no host paths, timestamps or hostnames.

One caveat worth knowing: ast.parse follows the grammar of the interpreter running it, so a wheel using syntax newer than the scanner's interpreter will not parse. Pin the interpreter if you need output comparable across hosts. That difference is never silently favourable: unparsed files are counted in artifacts.py_files_unparsed, and a wheel whose every source file failed reports source_available: false and comes out OPAQUE, not clean.

Performance

Measured on 100 synthetic wheels averaging 3.3 MiB uncompressed, on 16 cores:

Wheels are read from the zip in memory and never extracted to disk. Members above the in-memory threshold stream through a seekable zip reader that retains a bounded window of what it has already decompressed, so a multi-gigabyte extension costs a bounded number of passes rather than a gigabyte of resident memory. Reading the real 5.5 MiB libcrypto.so.3 through that path takes 0.19 s with one decompression; without the window it took 17 s and 3,161.

Development

uvx --with tox-uv tox          # tests across py311-py314, plus ruff lint and format
uvx --with tox-uv tox -e lint

Test fixtures are synthesised, including the ELF objects: the suite needs no compiler, no network and no committed binaries, and runs byte-identically anywhere. Tests against real downloaded wheels are behind the real marker; tests that read host system libraries are behind hostbin.

Dependencies are pyelftools and packaging, and nothing else without asking.

Releasing

Publishing is triggered by a bare semver tag and nothing else. There is no version to bump: it is derived from the tag at build time by uv-dynamic-versioning, so the version in a record is always the version that produced it.

git tag -a 0.1.0 -m "0.1.0" && git push origin 0.1.0

No v prefix. The workflow re-runs the full matrix, builds, checks that the ruleset and schema are actually inside the distribution, and uploads through PyPI Trusted Publishing, so there is no token to store.

An untagged build reports its commit, for example 0.0.0.post14.dev0+1105fe9, which makes it obvious when a record came from something other than a release.

Licence

Apache 2.0. See LICENSE.