스킬 gaffa-find

📦

gaffa-find

Name: gaffa-find
Author: gaffaai

콘텐츠 리비전 r1 높은 위험 ⚙️ 외부 명령어🌐 네트워크 접근📁 파일 시스템 접근🔑 환경 변수

Find Website Information With Gaffa

Finding reliable website information often requires repeated page inspection and extraction attempts. This skill guides a bounded Gaffa workflow that validates results and returns evidence with a reusable script.

지원: Claude Codex Code(CC)

⚠️ 38 나쁨

Maintain this Skill? Claim it ⚠️ 38 나쁨

설치 전에 중지하고 확인을 요청하세요.

계획을 검토하고 파일을 변경하기 전에 사용자의 명시적 동의를 받으세요.

내 에이전트로 설치

이 요청을 에이전트에 복사하세요. 공식 Skill 페이지와 매니페스트가 포함되어 있습니다.

에이전트 요청

Review the Skillstore skill "gaffa-find" from https://skillstore.io/skills/gaffaai-gaffa-find.md and its manifest at https://skillstore.io/api/skills/gaffaai-gaffa-find/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.

에이전트는 계속해서 계획을 표시하고 보안 정책에서 요구하는 확인을 요청해야 합니다.

에이전트가 읽기 쉬운 리소스

AI 에이전트, 크롤러, 스크립트가 전체 페이지 대신 정리된 컨텍스트만 필요할 때 이 링크를 사용하세요.

Markdown 상세 GET /skills/gaffaai-gaffa-find.md 서명된 manifest GET /api/skills/gaffaai-gaffa-find/manifest 서명된 lockfile GET /api/skills/gaffaai-gaffa-find/lockfile

테스트해 보기

"gaffa-find" 사용 중입니다. Find the chief executive on a public company leadership page.

예상 결과:

Illustrative result: success.
Candidate: Morgan Lee, listed as Chief Executive Officer.
Evidence: the leadership page identifies the name and role in the main content region.
Deliverable: a reusable Gaffa extraction script with request recording disabled.

"gaffa-find" 사용 중입니다. Find a published salary range when the available pages do not provide clear evidence.

예상 결과:

Illustrative result: needs-human-review.
No verified salary range was found within the request budget.
The final response identifies the partial candidate, log location, and failed request identifier when available.
The answer does not invent a salary range.

보안 감사

높은 위험

v1 • 2026. 10. 14. 버전별 보고서 열기

Most alerts concern Markdown formatting or intended API operations; confirmed risks include conditional redaction, unsafe sed interpolation, exposed credential arguments, and predictable temporary files. The logging example persists content before redaction, and mandatory browser recording can retain sensitive pages externally. No evidence of prompt injection or intentional exfiltration was found.

스캔된 파일

283

분석된 줄 수

검토 항목

오탐 무시됨

확인된 보안 우려 사항 (2)

높음

templates/loop.md:102-113 SKILL.md:80-86

Logging Template Persists Data Before Redaction

The template writes log content before scrubbing it, reversing the explicit redaction-first rule. When adapted to real iteration data, interruptions or scrub failures can leave sensitive content on disk.

The shell example writes at line 102 before running sed at line 110, contradicting SKILL.md lines 85-86. Its placeholder requires adaptation, but the demonstrated write order is directly observable.

중간

SKILL.md:40-43 SKILL.md:157-159

Mandatory Recording Can Retain Sensitive Page Content

The skill requires recording every browser request and states retention lasts seven days to three months. Sensitive pages can be retained externally without a documented sensitivity check or explicit recording consent.

Recording and retention are explicit requirements, and neither file provides a sensitivity check or recording consent step. Exposure depends on the target content; no malicious intent is established.

기능 검토 항목 (7)

이 스킬에 대해 예상될 수 있는 실제 로컬 기능이므로 검토가 필요하지만, 확인된 악의적 동작으로는 집계되지 않습니다.

높음

SKILL.md:82

Generic API/secret keys

4. If the runtime value of `GAFFA_API_KEY` appears as a substring anywhere in a payload you are abou

The substring scrub is conditional on length and character composition in lines 83-84. Other nonempty keys can remain in unstructured payloads despite field-name redaction.

높음

templates/loop.md:10

Generic API/secret keys

-H "X-API-Key: ${GAFFA_API_KEY}" \

The shell expands GAFFA_API_KEY into the curl authentication argument, despite using the legitimate vendor endpoint. Local process inspection can expose credentials where argument access is permitted.

높음

templates/loop.md:25

Generic API/secret keys

-H "X-API-Key: ${GAFFA_API_KEY}" \

The expanded API key becomes part of the curl command-line header argument. It can be exposed to local process inspection, although the network destination is legitimate.

높음

templates/loop.md:53

Generic API/secret keys

-H "X-API-Key: ${GAFFA_API_KEY}" \

Environment expansion places the API key directly in the curl process arguments. Systems allowing other users or monitoring tools to inspect arguments can expose the credential.

높음

templates/loop.md:108

Generic API/secret keys

if [ "${#GAFFA_API_KEY}" -ge 16 ] && printf '%s' "$GAFFA_API_KEY" | grep -q '[0-9]' && printf '%s' "

The conditional skips substring redaction for short, digit-only, or letter-only keys. Those credentials can survive in unstructured logs before the unconditional rename.

높음

templates/loop.md:110

Generic API/secret keys

sed -i "s|${GAFFA_API_KEY}|<REDACTED>|g" "$TMPLOG"

The key enters a sed regex and process argument without literal escaping or protection from argument inspection. Scrubbing can fail or miss matches, yet line 113 still renames the log.

중간

templates/loop.md:99

Hidden file access

FINALLOG="./.gaffa-find-$(date +%Y%m%dT%H%M%S).log"

Lines 99-102 derive a predictable temporary filename and open it with ordinary redirection. A precreated symlink can redirect writes in an attacker-writable directory.

위험 요인

⚙️ 외부 명령어 (50)

🌐 네트워크 접근 (12)

SKILL.md:33 SKILL.md:45 SKILL.md:47 SKILL.md:93 SKILL.md:97 SKILL.md:149 templates/loop.md:9 templates/loop.md:13 templates/loop.md:24 templates/loop.md:29 templates/loop.md:52 templates/loop.md:57

📁 파일 시스템 접근 (8)

SKILL.md:85 SKILL.md:153 SKILL.md:85 SKILL.md:153 templates/loop.md:90 templates/loop.md:99 templates/loop.md:95 templates/loop.md:96

🔑 환경 변수 (11)

SKILL.md:28 SKILL.md:75 SKILL.md:77 SKILL.md:78 SKILL.md:80 SKILL.md:82 templates/loop.md:10 templates/loop.md:25 templates/loop.md:53 templates/loop.md:108 templates/loop.md:110

감사자: codex

이 보고서 공유 및 인용

버전이 지정된 평가 보고서, 중립 배지, 임베드 카드 및 인용을 공유하세요. Skillstore는 근거를 보고하지만 이 Skill의 안전 여부를 판단하지 않습니다.

버전별 보고서 열기

보고서 링크 복사

https://skillstore.io/skills/gaffaai-gaffa-find/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdown 배지

[![Skillstore security assessment](https://skillstore.io/badges/skills/gaffaai-gaffa-find/security.svg)](https://skillstore.io/skills/gaffaai-gaffa-find?utm_source=security_passport_badge)

HTML 배지

<a href="https://skillstore.io/skills/gaffaai-gaffa-find?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/gaffaai-gaffa-find/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

임베드 카드

<iframe src="https://skillstore.io/embed/skills/gaffaai-gaffa-find.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>

학술 인용 (APA · BibTeX · CFF)

APA 인용

gaffaai. (2026). gaffa-find security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/gaffaai-gaffa-find/audits/1

BibTeX 인용

@techreport{gaffaai-gaffaai-gaffa-find-2026,
  author = {gaffaai},
  title = {gaffa-find security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/gaffaai-gaffa-find/audits/1},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "gaffa-find security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
  - name: "gaffaai"
date-released: "2026-10-14"
url: "https://skillstore.io/skills/gaffaai-gaffa-find/audits/1"
identifiers:
  - type: other
    value: "skillstore:gaffaai-gaffa-find:audit:1"
    description: "Skillstore immutable audit report identifier"

Skillstore 점수

이 점수의 이유 증거 신뢰도: 중간

아키텍처

유지보수성

콘텐츠

커뮤니티

사양 준수

만들 수 있는 것

Build a Targeted Extraction Script

Turn a website URL and desired field into a validated extraction approach with evidence and a reusable script.

Verify a Public Website Fact

Locate a company fact on public pages and check that the extracted value matches the research question.

Validate Website Data Fields

Extract a structured field and apply an explicit validator before accepting it for a data workflow.

이 프롬프트를 사용해 보세요

Find One Public Fact

Use gaffa-find on [website URL] to find [specific fact]. Return the answer, source evidence, and a reusable script.

Extract and Validate a Field

Find [field] on [website URL]. Prefer deterministic extraction and validate the value against [regex or expected type].

Inspect Before Extracting

Use reconnaissance-only mode on [website URL] for [goal]. Return the site map or landing capture without entering the extraction loop.

Refine a Bounded Extraction

Find [information] on [website URL] using [language]. Apply [validator], use at most [iteration count] iterations, and stop for human review if uncertain. Return evidence and a reusable script.

모범 사례

Use authorized public targets, a precise goal, and an explicit validator when correctness matters.
Review request and credit estimates, including proxy bandwidth and recording charges, before running extraction.
Fix credential handling and log redaction, and review recording consent and retention before processing sensitive pages.

피하기

Accepting empty or ambiguous extraction output as a verified answer.
Using full-page LLM extraction when a narrow deterministic selector is sufficient.
Copying credential and logging examples unchanged or recording sensitive pages without reviewing retention.

자주 묻는 질문

What inputs are required?

Provide a target URL and a plain-language information goal. The workflow asks for missing inputs before starting.

Which assistants are supported?

The marketplace lists Claude, Codex, and Claude Code. Execution still requires suitable tools, network access, and Gaffa credentials.

Does it require a Gaffa account?

Yes. The workflow reads GAFFA_API_KEY from the environment and uses paid Gaffa API operations.

Does every extraction use an LLM?

No. It prefers deterministic extraction for stable structures and uses parse_json for interpretive or variable content.

How does the workflow limit spending?

It specifies defaults of three requests per iteration, fifteen requests per invocation, fifty credits, and five iterations. These are agent instructions, not executable enforcement.

What happens when the answer cannot be verified?

It returns needs-human-review or terminal-failure with available evidence and debugging details. It should not invent an answer.