RRepoGEO

REPOGEO REPORT · LITE

AngoraFuzzer/Angora

Default branch master · commit 6b46c855 · scanned 6/5/2026, 10:52:04 PM

GitHub: 952 stars · 171 forks

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 AngoraFuzzer/Angora, 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

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

OVERALL DIRECTION
  • highreadme#1
    Refine README's opening to highlight C/C++ and unique methodology

    Why:

    CURRENT
    Angora is a mutation-based coverage guided fuzzer. The main goal of Angora is to increase branch coverage by solving path constraints without symbolic execution.
    COPY-PASTE FIX
    Angora is a mutation-based, **coverage-guided fuzzer for C/C++ applications** that employs **taint analysis and a principled search approach** to efficiently increase branch coverage by solving path constraints **without relying on symbolic execution**. It's designed for security researchers and developers to find bugs and vulnerabilities.
  • mediumtopics#2
    Expand topics to include specific fuzzing techniques and target language

    Why:

    CURRENT
    afl, data-flow-analysis, fuzzer, fuzzing, security, symbolic-execution, taint-analysis
    COPY-PASTE FIX
    afl, data-flow-analysis, fuzzer, fuzzing, security, symbolic-execution, taint-analysis, coverage-guided-fuzzing, principled-search, c-plus-plus, c-language, bug-finding, vulnerability-research
  • lowcomparison#3
    Add a brief comparison section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison with other Fuzzers

Unlike traditional coverage-guided fuzzers (e.g., AFL) that primarily rely on random mutations and edge coverage, Angora uses taint tracking and a principled search approach to guide mutations more effectively towards satisfying branch conditions and increasing coverage.

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 AngoraFuzzer/Angora
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AFL++
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. AFL++ · recommended 2×
  2. LibFuzzer · recommended 2×
  3. Honggfuzz · recommended 2×
  4. Radamsa · recommended 1×
  5. Domato · recommended 1×
  • CATEGORY QUERY
    How to improve code coverage during fuzzing without relying on symbolic execution?
    you: not recommended
    AI recommended (in order):
    1. AFL++
    2. LibFuzzer
    3. Honggfuzz
    4. Radamsa
    5. Domato
    6. Eclipser
    7. Antlr

    AI recommended 7 alternatives but never named AngoraFuzzer/Angora. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good mutation-based fuzzers for C/C++ applications that use taint analysis?
    you: not recommended
    AI recommended (in order):
    1. AFL++
    2. LibFuzzer
    3. Honggfuzz
    4. Driller
    5. Triton

    AI recommended 5 alternatives but never named AngoraFuzzer/Angora. 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 AngoraFuzzer/Angora?
    pass
    AI named AngoraFuzzer/Angora explicitly

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

  • If a team adopts AngoraFuzzer/Angora in production, what risks or prerequisites should they evaluate first?
    pass
    AI named AngoraFuzzer/Angora 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 AngoraFuzzer/Angora solve, and who is the primary audience?
    pass
    AI named AngoraFuzzer/Angora explicitly

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

Embed your GEO score

Drop this badge into the README of AngoraFuzzer/Angora. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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AngoraFuzzer/Angora — 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