New audit: unpinned-tools: VALIDATE, 62/100 | Ideas Lab

Add a GitHub Actions audit rule to detect when workflows use actions that fetch unpinned binary versions, creating supply chain attack vectors even when the action itself is hash-pinned.

The pain

Security teams using GitHub Actions face a blind spot: they can hash-pin an action to a specific commit, but that action may internally download the latest version of a tool (like Trivy or Cargo), which is mutable and can be replaced with malicious code. This defeats the purpose of pinning and creates a supply chain vulnerability that existing scanners do not detect.

The gap

No current security scanning tool (Trivy, SAST scanners, or GitHub's native checks) flags this pattern. The gap exists because it requires understanding both the action's inputs and the internal behavior of specific well-known actions. Zizmor already has the coordinate API and audit framework to add this, but the rule does not yet exist.

Build angle

Start with two high-confidence actions (trivy-action and install-action) where the unpinned pattern is clear and unambiguous. Build action-specific coordinate logic to detect missing version inputs or unversioned tool suffixes. Accept that some actions (setup-uv) will have higher false positive rates due to file-based version inputs that zizmor cannot parse. Ship the audit as a new rule in zizmor, document the limitations, and iterate based on user feedback.

Strengths

Problem is concrete and reproducible: hash-pinned actions with unpinned binary fetches are a real supply chain risk.
Fits naturally into zizmor's existing architecture and audit framework, requiring no new infrastructure.
Addresses a gap that no competitor currently fills, giving zizmor a differentiation point.
Can start narrow (two actions) and expand incrementally as more actions are analyzed.
Aligns with growing security industry focus on supply chain attacks and software provenance.

Risks

Market is small: only teams using GitHub Actions and caring about supply chain security will benefit, and many may not know this risk exists.
Feature is relatively simple to copy once published, so competitive moat is weak.
Requires ongoing maintenance as new actions emerge and existing actions change their behavior.
False positive rate may be high for actions that support file-based version inputs, reducing user trust.
Adoption depends entirely on zizmor's user base and mindshare; if zizmor does not grow, this feature reaches few people.
Some actions (like zizmor-action itself) require special-case logic to avoid false positives, increasing complexity.
Users may not be willing to pay for this as a standalone product; it only has value as part of a larger security scanning tool.

Fly Labs Method

Is the pain real, is there a gap, is it the right time, can one person build it.

62

Problem clarity: 78
Solution gap: 68
Willingness to pay: 52
Buildability: 50

The supply chain risk is real and well-defined, but willingness to pay for a niche audit rule is unclear and implementation requires ongoing maintenance of action-specific logic.

Value Equation

Dream outcome and how likely it feels, against the time and effort it costs.

55

The problem affects a specific audience (DevOps/security teams) but the solution is a feature addition to existing tooling rather than a standalone business, limiting pricing power and market size.

One-Person Business

Curiosity pull, identity fit, and a path from free value to paid for a solo creator.

48

This solves a genuine security gap for teams using GitHub Actions, but the market is narrow, the feature is relatively simple to copy, and adoption depends on existing tool penetration.

Viral Frameworks

Hook strength, shareability, and how cheaply it can be tested.

64

The audit fills a real gap in supply chain security detection, but success depends entirely on zizmor's adoption rate and the feature may become commoditized across competing security scanners.

Builder Lens

Evidence the problem exists, timing, defensibility, and a model that fits on a napkin.

59

A focused security feature that addresses a real vulnerability class, but lacks the scale potential, defensibility, or standalone business model that YC typically funds.

Five lenses, one composite. How scoring works

The angle

Start with two high-confidence actions (trivy-action and install-action) where the unpinned pattern is clear and unambiguous. Build action-specific coordinate logic to detect missing version inputs or unversioned tool suffixes. Accept that some actions (setup-uv) will have higher false positive rates due to file-based version inputs that zizmor cannot parse. Ship the audit as a new rule in zizmor, document the limitations, and iterate based on user feedback.

No market research recorded for this idea yet.

Semble – Code search for agents that uses 98% fewer tokens than grep

Hey HN! We (Stephan and Thomas) recently open-sourced Semble. We kept running into the same problem while using Claude Code on large codebases: when the agent can't find something directly, it falls back to grep, reading full files or launching subagents. This uses a lot of tokens, and often still misses the relevant code. There are existing tools for this, but they were either too slow to index on demand, needed API keys, or had poor retrieval quality.Semble is our solution for this. It combines static Model2Vec embeddings (using our latest static model: potion-code-16M) with BM25, fused via RRF and reranked with code-aware signals. Everything runs on CPU since there's no transformers involved. On our benchmark of ~1250 query/document pairs across 63 repos and 19 languages, it uses 98% fewer tokens than grep+read and reaches 99% of the retrieval quality of a 137M-parameter code-trained transformer, while being ~200x faster.Main features:- Token-efficient: 98% fewer tokens than grep+read- Fast: ~250ms to index a typical repo on our benchmark, ~1.5ms per query on CPU (very large repos may take longer)- Accurate: 0.854 NDCG@10, 99% of the best transformer setup we tested- MCP server: drop-in for Claude Code, Cursor, Codex, OpenCode- Zero config: no API keys, no GPU, no external servicesInstall in Claude Code with: claude mcp add semble -s user -- uvx --from "semble[mcp]" sembleOr check our README for other installation instructions, benchmarks, and methodology:Semble: https://github.com/MinishLab/sembleBenchmarks: https://github.com/MinishLab/semble/tree/main/benchmarksModel: https://huggingface.co/minishlab/potion-code-16MLet us know if you have any feedback or questions!

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Consus (YC F24) – LLM gateway for companies handling sensitive data

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