Skills gaffa-find

📦

gaffa-find

Name: gaffa-find
Author: gaffaai

Content revision r1 High Risk ⚙️ External commands🌐 Network access📁 Filesystem access🔑 Env variables

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.

Supports: Claude Codex Code(CC)

⚠️ 38 Poor

Maintain this Skill? Claim it ⚠️ 38 Poor

Stop for confirmation before installing.

Review the plan and obtain explicit user consent before changing files.

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

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.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/gaffaai-gaffa-find.md Signed manifest GET /api/skills/gaffaai-gaffa-find/manifest Signed lockfile GET /api/skills/gaffaai-gaffa-find/lockfile

Test it

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

Expected outcome:

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.

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

Expected outcome:

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.

Security Audit

High Risk

v1 • 10/14/2026 Open versioned report

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.

Files scanned

283

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (2)

High

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.

Medium

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.

Capability review items (7)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

High

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.

High

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.

High

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.

High

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.

High

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.

High

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.

Medium

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.

Risk Factors

⚙️ External commands (50)

🌐 Network access (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

📁 Filesystem access (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

🔑 Env variables (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

Audited by: codex

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Academic citations (APA · BibTeX · CFF)

APA citation

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

BibTeX citation

@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 Score

Why this score Evidence Confidence: Medium

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

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.

Try These Prompts

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.

Best Practices

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.

Avoid

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.

Frequently Asked Questions

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.