RRepoGEO

REPOGEO REPORT · LITE

vercel-labs/deepsec

Default branch main · commit e3c8f05a · scanned 6/17/2026, 11:52:13 PM

GitHub: 3,212 stars · 224 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface vercel-labs/deepsec, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README H1 and opening sentence to highlight key differentiators

    Why:

    CURRENT
    # deepsec
`deepsec` an agent-powered vulnerability scanner that you can run in your own infrastructure, optimized to perform on-demand review of all code in existing large-scale repos.
    COPY-PASTE FIX
    # deepsec: Agent-Powered, Self-Hosted Vulnerability Scanner for Large Codebases
Deepsec is an advanced, agent-powered vulnerability scanner designed to run in your own infrastructure, optimized for deep security analysis of large, existing codebases.
  • mediumreadme#2
    Add a 'How is Deepsec different?' section to the README

    Why:

    COPY-PASTE FIX
    ## How is Deepsec different?
Deepsec stands apart from traditional SAST tools like Semgrep or CodeQL by leveraging advanced AI agents for deep, contextual analysis. Unlike tools focused on pattern matching or rule-based detection, Deepsec is designed to surface hard-to-find, subtle vulnerabilities in large, existing codebases by simulating a human security expert's review process. It's optimized for self-hosted deployment, allowing you to run powerful, on-demand security reviews within your own infrastructure.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface vercel-labs/deepsec
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
github/codeql
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. github/codeql · recommended 2×
  2. returntocorp/semgrep · recommended 2×
  3. GitHub Copilot Enterprise · recommended 1×
  4. GitHub Advanced Security (GHAS) · recommended 1×
  5. Semgrep Code · recommended 1×
  • CATEGORY QUERY
    How to find subtle security vulnerabilities in large existing codebases using AI agents?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. GitHub Advanced Security (GHAS)
    3. CodeQL (github/codeql)
    4. Semgrep (returntocorp/semgrep)
    5. Semgrep Code
    6. DeepCode AI
    7. Snyk Code
    8. Veracode Static Analysis
    9. Checkmarx SAST
    10. OpenAI GPT-4
    11. Anthropic Claude
    12. CodeGuru Security

    AI recommended 12 alternatives but never named vercel-labs/deepsec. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are self-hosted AI-powered tools for deep security analysis of application code?
    you: not recommended
    AI recommended (in order):
    1. Semgrep OSS (returntocorp/semgrep)
    2. CodeQL (github/codeql)
    3. SonarQube (SonarSource/sonarqube)
    4. ShiftLeft CORE
    5. Fortify Static Code Analyzer (SCA)
    6. Checkmarx SAST (CxSAST)

    AI recommended 6 alternatives but never named vercel-labs/deepsec. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of vercel-labs/deepsec?
    pass
    AI named vercel-labs/deepsec explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts vercel-labs/deepsec in production, what risks or prerequisites should they evaluate first?
    pass
    AI named vercel-labs/deepsec explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo vercel-labs/deepsec solve, and who is the primary audience?
    pass
    AI named vercel-labs/deepsec explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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vercel-labs/deepsec — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite