X Bot Detector

Tracking since Apr 1, 2026.

Changelog

• Jun 4, 2026
  description

  X Bot Detector analyzes tweets and accounts on X (formerly Twitter) to identify bot activity and AI-generated content using 22 heuristic signals, 9
    swarm detection checks, and 15 AI text detection signals. Everything runs locally in your browser — no data leaves your device, no API keys needed.    
    
    HOW IT WORKS
  
    The extension intercepts X's internal GraphQL API responses to extract rich user and tweet metadata — the same data X's own frontend uses. This gives  
    it access to account creation dates, follower counts, posting sources, listed memberships, and more, enabling far more accurate detection than DOM-only
     analysis.
  
    WHAT IT DETECTS
  
    Account signals (11): account age, reputation score (followers/following ratio), posting rate, list memberships, favourites ratio, default profile     
    detection, username patterns, display name analysis, bio spam patterns, media ratio, and follow-ceiling behavior.
  
    Content signals: hashtag density, spam keywords (crypto scams, engagement bait), emoji abuse, mention bombing, suspicious URLs, text entropy, and      
    template/low-variance text detection.
  
    Engagement signals: engagement ratio analysis for bought likes/views/retweets, generic reply farming, and vocabulary richness.
  
    Source analysis: identifies bot frameworks, automation tools, and suspicious posting clients from the tweet source app field.
  
    Temporal analysis: detects unnaturally regular posting patterns and rapid-fire tweeting.
  
    REPLY SWARM DETECTION (9 checks)
  
    Groups replies by conversation and checks for text similarity clustering, bot username patterns, generic reply floods, new account prevalence, default 
    avatars, low reputation repliers, automation tool usage, synchronized account creation dates, and shared suspicious URLs — catching coordinated        
    inauthentic behavior that single-tweet analysis would miss.
  
    AI TEXT DETECTION (15 signals)
  
    Independent from bot scoring, this module flags tweets likely written by large language models (ChatGPT, Claude, Gemini, etc.) using two complementary 
    approaches:
  
    Linguistic patterns: signature LLM phrases ("it's important to note", "delve into", "in the realm of"), corporate AI buzzwords, bulleted/numbered list 
    structure, avoidance of contractions, hedging language density, and a casualness discount for clearly human-sounding text.
  
    Statistical fingerprint: em dash density, semicolon usage, comma density, sentence burstiness (variation in sentence length), word complexity,
    sentence-end punctuation distribution, clause complexity, sentence uniformity, and passive voice frequency.
  
    Flagged tweets get a distinct violet "AI Text" badge alongside any bot badges, so you can tell apart bot accounts, human accounts posting AI-written   
    content, and legitimate organic posts.
  
    SCORING
  
    Each tweet gets a weighted score across all signals:
    - 70%+ = Likely Bot (red badge)
    - 40-69% = Suspicious (amber badge)
    - 20-39% = Mild Signals (blue badge)
    - Below 20% = Clean (no badge)
  
    Reply swarms get a pulsing purple badge. AI-generated text gets a violet badge. Badges show "API" (green) when scored with full intercepted data, or   
    "DOM" (grey) for fallback DOM-only analysis.
  
    WHAT'S NEW IN v3.2.0
  
    - AI text detection with 15 pattern + statistical signals, independent toggle
    - Reply swarm detection expanded to 9 checks (added creation-date clustering and shared-URL detection)
    - 3 new account-level signals (favourites ratio, media ratio, follow ceiling)
    - Redesigned popup with live status indicator and per-category accent colors
  
    100% private. Zero data collection. No external API calls. Everything stays in your browser.

  X Bot Detector checks tweets and accounts on X (formerly Twitter) for bot activity and AI-written content. It runs 36 heuristic signals, 9 swarm-detection checks and 
  15 AI text signals. Everything happens locally in your browser. No data leaves your
  device and there are no API keys to set up.
  
  HOW IT WORKS
  
  The extension reads X's own internal GraphQL API responses, the same data the X website uses to draw your feed. That gives it real account metadata: creation dates,
  follower counts, posting-source apps and list memberships. It's far more accurate than guessing from the page alone.
  
  WHAT IT DETECTS
  
  Account checks: account age, follower-to-following ratio, posting rate, list memberships, like activity, default profiles, username patterns, display-name spam, bio  
  spam, media ratio and follow-limit behavior.
  
  Content checks: hashtag stuffing, spam and scam keywords, emoji abuse, mention bombing, shortened or suspicious links, low text variety and templated copy.
  
  Engagement checks: ratios that point to bought likes, views or reposts, plus generic reply-farming and thin vocabulary.
  
  Source checks: known bot frameworks and automation tools spotted in the posting-client field.
  
  Timing checks: posting that's too regular to be human, plus rapid-fire bursts.
  
  REPLY SWARM DETECTION
  
  When a pile of replies lands on one post, the extension groups them and looks for coordination: near-identical wording, bot-style usernames, floods of generic        replies, clusters of brand-new accounts, default avatars, low-reputation repliers,
  automation tools, accounts all created in the same week and the same link posted  over and over. That's the kind of thing you'd never catch one tweet at a time.
  
  AI TEXT DETECTION
  
  This part is separate from the bot score. It flags tweets that read like a large language model wrote them (ChatGPT, Claude, Gemini and the like) using two angles.   
  
  Language patterns: telltale phrases like "it's important to note", "delve into" and "in the realm of", corporate AI buzzwords, bulleted or numbered structure, dodged 
  contractions and heavy hedging. Clearly casual, human writing pulls the score back down.
  
  Statistical fingerprint: em dash and semicolon habits, comma density, how much sentence length varies, word complexity, punctuation consistency, clause structure and
  passive voice.
  
  Flagged tweets get their own violet "AI Text" badge next to any bot badge. So you can tell a bot account from a real person posting AI-written text from a plain      
  organic post.
  
  SCORING
  
  Every tweet gets a weighted score:
    - 70% and up: Likely Bot (red badge)
    - 40 to 69%: Suspicious (amber badge)
    - 20 to 39%: Mild Signals (blue badge)
    - Under 20%: Clean (no badge)
  
  Reply swarms get a pulsing purple badge. AI text gets a violet one. A small tag reads "API" (green) when the score used full intercepted data or "DOM" (grey) when it 
  fell back to reading the page.
  
    WHAT'S NEW IN v3.3.0
  
  - Smarter scoring. One strong signal no longer gets watered down by weaker ones, so clear-cut bots stop slipping through.
  - Fewer false alarms. A "Likely Bot" verdict now needs real backup (a smoking-gun signal or evidence from more than one category), so an eager new account that       
    follows lots of people won't get tarred as a bot.
  - Fair handling of reposts. Spam or AI text in a retweet now counts against the original author instead of whoever reposted it.
  - Account age feeds into the reputation check. A brand-new account with few followers isn't treated like a seasoned mass-follow bot.
  - Verification stops being a free pass. A checkmark or an old account won't rescue something that trips several strong bot signals.
  - Reliability fixes. Saved timing and AI data now survive page reloads, and AI detection re-runs once the full tweet text loads.
  
  100% private. Zero data collection. No outside calls. It all stays in your browser.

• Apr 17, 2026
  description

  X Bot Detector analyzes tweets and accounts on X (formerly Twitter) to identify bot activity using 20 heuristic signals and 7 swarm detection checks. Everything runs
    locally in your browser — no data leaves your device, no API keys needed.
  
    HOW IT WORKS
  
    The extension intercepts X's internal GraphQL API responses to extract rich user and tweet metadata — the same data X's own frontend uses. This gives it access to       
    account creation dates, follower counts, posting sources, and more, enabling far more accurate detection than DOM-only analysis.
  
    WHAT IT DETECTS
  
    Account signals: account age, reputation score (followers/following ratio), posting rate, list memberships, default profile detection, username patterns, display name   
    analysis, and bio spam patterns.
  
    Content signals: hashtag density, spam keywords (crypto scams, engagement bait), emoji abuse, mention bombing, suspicious URLs, and template text detection.
  
    Engagement signals: bought likes/views/retweets detection and generic reply farming.
  
    Source analysis: identifies bot frameworks, automation tools, and suspicious posting clients.
  
    Temporal analysis: detects unnaturally regular posting patterns and rapid-fire tweeting.
  
    Coordination detection: finds copy-paste content across different users in your session.
  
    REPLY SWARM DETECTION
  
    Groups replies by conversation and checks for text similarity clustering, bot username patterns, generic reply floods, new account prevalence, default avatars, low      
    reputation repliers, and automation tool usage.
  
    SCORING
  
    Each tweet gets a weighted score across all signals:
    - 70%+ = Likely Bot (red badge)
    - 40-69% = Suspicious (orange badge)
    - 20-39% = Mild Signals (blue badge)
    - Below 20% = Clean (no badge)
  
    Badges show "API" (green) when scored with full intercepted data, or "DOM" (grey) for fallback DOM-only analysis.
  
    100% private. Zero data collection. No external API calls. Everything stays in your browser.

  X Bot Detector analyzes tweets and accounts on X (formerly Twitter) to identify bot activity and AI-generated content using 22 heuristic signals, 9
    swarm detection checks, and 15 AI text detection signals. Everything runs locally in your browser — no data leaves your device, no API keys needed.    
    
    HOW IT WORKS
  
    The extension intercepts X's internal GraphQL API responses to extract rich user and tweet metadata — the same data X's own frontend uses. This gives  
    it access to account creation dates, follower counts, posting sources, listed memberships, and more, enabling far more accurate detection than DOM-only
     analysis.
  
    WHAT IT DETECTS
  
    Account signals (11): account age, reputation score (followers/following ratio), posting rate, list memberships, favourites ratio, default profile     
    detection, username patterns, display name analysis, bio spam patterns, media ratio, and follow-ceiling behavior.
  
    Content signals: hashtag density, spam keywords (crypto scams, engagement bait), emoji abuse, mention bombing, suspicious URLs, text entropy, and      
    template/low-variance text detection.
  
    Engagement signals: engagement ratio analysis for bought likes/views/retweets, generic reply farming, and vocabulary richness.
  
    Source analysis: identifies bot frameworks, automation tools, and suspicious posting clients from the tweet source app field.
  
    Temporal analysis: detects unnaturally regular posting patterns and rapid-fire tweeting.
  
    REPLY SWARM DETECTION (9 checks)
  
    Groups replies by conversation and checks for text similarity clustering, bot username patterns, generic reply floods, new account prevalence, default 
    avatars, low reputation repliers, automation tool usage, synchronized account creation dates, and shared suspicious URLs — catching coordinated        
    inauthentic behavior that single-tweet analysis would miss.
  
    AI TEXT DETECTION (15 signals)
  
    Independent from bot scoring, this module flags tweets likely written by large language models (ChatGPT, Claude, Gemini, etc.) using two complementary 
    approaches:
  
    Linguistic patterns: signature LLM phrases ("it's important to note", "delve into", "in the realm of"), corporate AI buzzwords, bulleted/numbered list 
    structure, avoidance of contractions, hedging language density, and a casualness discount for clearly human-sounding text.
  
    Statistical fingerprint: em dash density, semicolon usage, comma density, sentence burstiness (variation in sentence length), word complexity,
    sentence-end punctuation distribution, clause complexity, sentence uniformity, and passive voice frequency.
  
    Flagged tweets get a distinct violet "AI Text" badge alongside any bot badges, so you can tell apart bot accounts, human accounts posting AI-written   
    content, and legitimate organic posts.
  
    SCORING
  
    Each tweet gets a weighted score across all signals:
    - 70%+ = Likely Bot (red badge)
    - 40-69% = Suspicious (amber badge)
    - 20-39% = Mild Signals (blue badge)
    - Below 20% = Clean (no badge)
  
    Reply swarms get a pulsing purple badge. AI-generated text gets a violet badge. Badges show "API" (green) when scored with full intercepted data, or   
    "DOM" (grey) for fallback DOM-only analysis.
  
    WHAT'S NEW IN v3.2.0
  
    - AI text detection with 15 pattern + statistical signals, independent toggle
    - Reply swarm detection expanded to 9 checks (added creation-date clustering and shared-URL detection)
    - 3 new account-level signals (favourites ratio, media ratio, follow ceiling)
    - Redesigned popup with live status indicator and per-category accent colors
  
    100% private. Zero data collection. No external API calls. Everything stays in your browser.

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