webseclist-collect-year

name

webseclist-collect-year

description

Sweeps the internet for a given year's novel web/HTTP/API/browser security research and writes or extends that year's AI-collected candidate list at YEAR-ai.md, skipping every link already recorded in YEAR.md or YEAR-ai.md. Use when asked to collect, gather, sweep, compile, refresh, extend or "find all the techniques for" a year (2026, 2027, last year, this year so far); to build or update a YEAR-ai.md file; or to catch a year up before nominations open. Do NOT use it to score a single candidate's novelty (that is webseclist-judge-reference), to download or convert sources into archived-references/ (that is webseclist-archive-references), or to snapshot nomination and results pages (that is webseclist-archive-listings). It never edits the hand-curated year lists 2006.md..2025.md.

Collect a year's web hacking techniques

You are building <YEAR>-ai.md: a machine-assembled, unranked, explicitly provisional collection of candidate research published in one calendar year. It sits beside the hand-curated year lists and never replaces them.

Two failure modes make a run worthless, and both are easy to fall into:

1. Citing the wrong thing. A news article about research is not the research. A roundup, a vendor advisory with no analysis, or a CVE record is not a technique writeup. The deliverable is the original source.
2. Re-collecting what is already there. The curated list for the year, and any previous run of this skill, already hold links. Re-adding them inflates the file and hides the genuinely new finds. This is what the exclusion step exists to prevent — do not skip it because the year "looks empty".

Process

1. Resolve the year and build the exclusion set

Do this first, before any searching, so every downstream step can filter against it.

python .claude/skills/webseclist-collect-year/scripts/known_links.py <YEAR> --raw

This reads <YEAR>.md and <YEAR>-ai.md (and handles the shared 2016-17.md) and prints every URL already recorded, normalised so that trailing slashes, www., http-vs-https, tracking parameters and Wayback wrappers do not produce false "new" finds.

Read the existing <YEAR>-ai.md if there is one. Its Watchlist and Explicitly excluded sections are the previous run's notes to you: they say which artifacts had not been published yet and which candidates were already chased down and rejected, with reasons. Start from those rather than rediscovering them.

Fix the date window now and state it: 1 January to 31 December of the year, or to today if the year is still running.

2. Sweep, split across beats

Read references/source-map.md — it lists the beats, names the blogs that are currently productive, records which sources are confirmed dead (so you do not spend a sweep on them), and documents the API endpoints and workarounds for sources that block automated fetching.

Run the beats in parallel as subagents, one beat each, rather than sequentially. A year is far too much ground for one context, and the beats are independent. Give every subagent: the year and date window, the rules in step 3, and an instruction to return structured lines plus a list of sources it swept that produced nothing.

Subagents commonly exhaust their web-search budget mid-sweep. Tell them to fall back to fetching index pages, feeds, sitemaps and the JSON APIs in the source map, and to report explicitly which beats ended up under-covered — an honest gap recorded in the Watchlist is worth more than a silent one.

Any file saved to disk while probing — a page fetched with curl -o to inspect, a bot-wall response kept for a second look, a candidates.txt working list — goes in the session scratchpad or the OS temp directory, never inside the repository. A stray download at the repo root gets committed and published with the list. Pass this rule to every subagent.

3. Rules every candidate must pass

• Original source only. The researcher's own blog post, the whitepaper, the full slide deck, the talk video, or the disclosed report. Never a news site (BleepingComputer, The Hacker News, SecurityWeek, DarkReading), never Reddit, Hacker News or an X thread, never a newsletter. Those are fine to find things through — chase the link back and cite the original.

• A new technique, attack class, primitive, or a meaningful extension of one. Exclude vendor patch announcements, plain CVE disclosures with no analysis, routine bug bounty writeups, product marketing, and roundups.

• In the date window. Verify by fetching the page; do not trust a feed's <updated> timestamp, a sitemap lastmod, or a search result snippet, all of which are known to lie. The most common error is work disclosed the previous year and merely presented at a conference in the target year — that belongs to the year of disclosure.

• Not already recorded. Filter candidates through the exclusion set:

  cat candidates.txt | python .claude/skills/webseclist-collect-year/scripts/known_links.py <YEAR> --filter --verbose
  

• Grouped. One piece of work with a blog post, slides, a video and a tool is one entry with related links, not four entries.

Apply the judging criteria from webseclist-judge-reference as you triage — especially its central rule: impact is not research value. A CVSS 10.0 on a famous target can teach nothing new, and an obscure parser quirk can introduce a primitive that reshapes a class. Score the contribution, not the headline. You do not need a full scorecard for every candidate at this stage; use the criteria as a filter, and reach for the full skill when a call is genuinely close.

• Keep-cut: score 60 or above. A candidate stays in <YEAR>-ai.md only if a full webseclist-judge-reference scorecard puts it at ≥ 60/100 with a non-duplicate verdict; below 60 it is recorded in the evaluation folder but its link is removed from the displayed list. This cut is above the judge skill's general ≥ 50 supporting-reference bar and below its ≥ 70 core-technique label. Both provisional lists and the separately review-gated historical missed-item path use ≥ 60, while the historical path additionally requires publication-year verification and proof that the work was never nominated. Out-of-window work is excluded regardless of score.

4. Preserve every lead and judgement

Never erase a discovered candidate merely because it missed the display cut. Maintain ai-evaluation/<YEAR>/ as three complementary records:

• README.md indexes every credible lead and URL, including screened-out, out-of-window, removed and still-unavailable candidates;
• judgements.md holds every completed scorecard, whether kept or removed;
• history.jsonl is append-only and records each initial or changed judgement.

After changing judgements.md, append only changed scorecards to history:

python .claude/skills/webseclist-judge-reference/scripts/history.py \
  import-markdown --year <YEAR> --file ai-evaluation/<YEAR>/judgements.md \
  --event-type judgement
python .claude/skills/webseclist-judge-reference/scripts/history.py verify

Use --event-type rejudgement when the run deliberately revisits existing evidence. Never edit or sort history.jsonl by hand; an unchanged import is a no-op and a changed candidate links to its previous event with supersedes.

5. Verify the links

python .claude/skills/webseclist-collect-year/scripts/check_links.py <YEAR>-ai.md --only-problems

Read the output with judgement — the script's own docstring explains the codes. 403 and 429 are usually anti-bot defences rather than dead links; 404 is real and must be fixed or dropped. For a host that is down, a Wayback snapshot is an acceptable citation if you say so in the entry.

6. Write the file

Write <YEAR>-ai.md. On a re-run, merge — keep the existing entries, add the new ones to their sections, and update the Watchlist and exclusions rather than starting over.

The file opens with two notices, and neither is optional. The first says a machine assembled it; the second says it is provisional. Both exist so a reader arriving from a search engine cannot mistake this for the curated list.

# Web Hacking Techniques <YEAR> — AI-collected

> ## 🤖 Collected by an AI agent, not by the community
>
> **This file was assembled by an AI agent**, not by nominations, a community
> vote, or an expert panel. That is why it is named `<YEAR>-ai.md` and kept
> separate from the curated year lists (`2006.md` … ), which are maintained by
> hand. Nothing here has been reviewed by a human, so treat every line as a lead
> to check rather than a settled fact.
>
> The known failure modes of a collection built this way: a link may be
> misattributed, a date may be wrong, the "novel" claim may not survive a real
> prior-art search, and the coverage is uneven — it is biased toward sources that
> publish in English on the open web and reachable without a login.
>
> It was produced with the `webseclist-collect-year` skill, which can be re-run
> to extend it.
>
> ## ⚠️ Work in progress — this is not a Top 10
>
> <state whether the year's voting round has happened; give the exact date
> window covered; say it is unranked and incomplete.>
>
> **Judge it yourself.** Do not take inclusion here as endorsement. Use the
> `webseclist-judge-reference` skill to score any entry on its own evidence —
> original contribution, transferability, lasting value, technical soundness,
> practical usability, and clarity — and to check the prior art before treating






   []() []() []() — Author, org

… repeat per theme …

Group entries by theme, not by source or by date. Themes that have worked: HTTP and protocol; client-side and browser; frameworks, injection and server-side; authentication, identity and session; AI agents and MCP as web attack surface; CI/CD and supply chain with a web mechanism; academic papers. Adapt them to what the year actually produced — an empty section is noise.

Match the list style of the curated year files: - [Title](url) with three spaces after the dash. Wrap any URL containing parentheses in angle brackets, [Title](<url>), or the markdown link will break.

Handling finds from other years

A sweep for one year always surfaces work from the year before. Do not silently drop it and do not quietly add it to a curated list.

• Record it in the Explicitly excluded section with its actual publication date, so the next run does not re-chase it.
• If it looks genuinely significant and is missing from that year's list, run the full webseclist-judge-reference skill on it. Only if it scores ≥ 60 with a non-duplicate verdict is it a candidate for the curated <YEAR>.md, and then it is added as a single reviewed line under "Other nominations" with the score noted in the collecting file. Below 60, it stays excluded but the source and judgement remain in ai-evaluation/<YEAR>/ for audit history.

This is the only circumstance in which this workflow touches a curated year list. Never bulk-add to one.

What this skill does not do

It collects and writes <YEAR>-ai.md. It does not rank or vote, does not produce a top ten, does not fetch or convert sources into archived-references/ (that is webseclist-archive-references), does not snapshot nomination or results pages (that is webseclist-archive-listings), and does not rewrite the hand-curated lists 2006.md..2025.md beyond the single review-gated addition path above.