Security scan results need source review before teams can trust findings or apply fixes. This skill guides Frame scans, evidence-based triage, patch review, and verification.
이 요청을 에이전트에 복사하세요. 공식 Skill 페이지와 매니페스트가 포함되어 있습니다.
에이전트 요청
Review the Skillstore skill "frame-security-scan" from https://skillstore.io/skills/lambdasec-frame-security-scan.md and its manifest at https://skillstore.io/api/skills/lambdasec-frame-security-scan/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.
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.
All 31 static findings are false positives involving Markdown formatting, authorized tooling, a local endpoint, a repository URL, and an empty credential example. The instructions require consent for hosted AI requests, installation, and source changes. No evidence found of credential theft, unauthorized exfiltration, or prompt injection.
lambdasec. (2026). frame-security-scan security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/lambdasec-frame-security-scan/audits/1
BibTeX 인용
@techreport{lambdasec-lambdasec-frame-security-scan-2026,
author = {lambdasec},
title = {frame-security-scan security audit report (audit version 1)},
institution = {Skillstore},
year = {2026},
number = {1},
url = {https://skillstore.io/skills/lambdasec-frame-security-scan/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: "frame-security-scan security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
- name: "lambdasec"
date-released: "2026-10-28"
url: "https://skillstore.io/skills/lambdasec-frame-security-scan/audits/1"
identifiers:
- type: other
value: "skillstore:lambdasec-frame-security-scan:audit:1"
description: "Skillstore immutable audit report identifier"
Skillstore 점수
이 점수의 이유증거 신뢰도: 중간
41
아키텍처
85
유지보수성
87
콘텐츠
65
커뮤니티
91
사양 준수
만들 수 있는 것
Review Application Vulnerabilities
Scan application code and inspect reported flows before deciding which findings require fixes.
Triage Security Findings
Separate symbolic and model findings, inspect validation and reachability, and document evidence for each verdict.
Check Changed Code
Use changed-file scans, baselines, and SARIF output to support repository security checks.
이 프롬프트를 사용해 보세요
Scan One File
Check whether Frame is installed, then scan [file] locally without AI. Summarize findings and limitations; do not install software without asking.
Triage Directory Findings
Scan [directory] without AI and save findings. Review each source-to-sink flow and explain confirmed findings, likely false positives, and unresolved questions.
Review and Verify Fixes
Triage [findings file], then propose fixes. Ask before endpoint use or source changes; show diffs, re-scan approved patches, and run project tests.
Assess Changed Code Against a Baseline
Scan files changed since [reference] using [baseline file]. Export SARIF, triage new findings, and explain verification limits without changing configuration.
모범 사례
Start with local scanning and obtain consent before sending code to hosted endpoints.
Inspect attacker control, source-to-sink flow, validation, and reachability before assigning a triage verdict.
Review diffs, commit or back up work before approved source changes, then re-scan and run project tests.
피하기
Treating low confidence or a clean scan as proof that code is safe.
Enabling hosted AI or applying source changes without explicit user agreement.
Suppressing findings or trusting model conclusions without reading the affected code.
자주 묻는 질문
Does this skill install Frame automatically?
No. It checks availability and shows the installation command, but requires agreement before running installation.
Which languages support symbolic scanning?
Python, JavaScript, TypeScript, Java, C, C++, and C# have symbolic frontends. Other languages require optional LLM detection.
Does source code leave my machine?
Hosted AI endpoints receive code snippets only after consent. The documented local endpoint supports keeping AI processing on your machine.
Can the skill change source files?
It can request proposed fix diffs. In-place source changes require agreement and a commit or backup; fix generation also requires an LLM endpoint.
Can I use Frame through MCP?
Yes. A connected Frame MCP server can replace CLI commands, with the same consent rules for AI, source changes, and exploit operations.
Does a clean scan guarantee security?
No. Frame can miss vulnerabilities and report false positives. Review findings, verify fixes, and run project tests.