keygraphhq/shannon: technical due diligence, read from its repository

2 of 2 `FROM` lines in product Dockerfiles name an image without a version, or with `latest`. Each build pulls whatever the registry serves that day, so the image that ships can change without a commit, and last month's build cannot be reproduced. Pin a version, or a digest.

0 test files against 201 source files (0.0%). This does not measure whether the tests are good, only whether enough of them exist for the codebase to be changed safely by someone who did not write it — which is exactly the situation after an acquisition.

17 of 241 commits in the last 24 months changed over 2,000 lines of code, not counting reformatting, renames, vendored or generated code. A change that size is rarely reviewed line by line. Ask how they were reviewed, and what made them that large.

There is no disclosure policy, no automated dependency updates, no named code owners and no pre-commit configuration. None of these is load-bearing on its own. Their collective absence says that security posture here is whatever the current team happens to remember to do, which is not a posture that survives the team changing.

22 of 445 locked dependencies match 100 published advisories in OSV, 38 of them rated high or critical. A lockfile says which version is installed, not whether the flawed code is reachable from this product, so each needs a look. Most are fixed by an upgrade, and the advisory names the version.

The root licence changed 2 time(s). Code taken under earlier terms stays under them; check which terms any fork or customer relied on.

None of 314 readable files references an instrumentation, metrics or error-reporting library. If this system is in production, nobody learns that it broke from the system itself — they learn it from a customer. That is a reliability finding before it is an observability one.

Nothing references a structured logging library. Logs that are written to be read by a person are not searchable by a machine, which means incident response here is proportional to how well someone remembers the codebase rather than to what the tooling can find.

Nothing in the service carries a request or correlation id, and there is no tracing. When a customer reports a failure, the log lines that belong to their request cannot be picked out from everyone else's.