Is github.com/seabra98/Polymarket-Kalshi-Arbitrage-Bot safe?

cautionmedium confidence
66/100

context safety score

A score of 66/100 indicates minor risk signals were detected. The entity may be legitimate but has characteristics that warrant attention.

identity
100
behavior
100
content
37
graph
67

5 threat patterns detected

high

prompt injection

Hidden HTML element contains AI-targeting instructions

high

social engineering

The README contains an 'About Developer' section impersonating a named developer ('Alexei') claiming expertise in EVM, Solana, and prediction market bots, and directing users to contact via Telegram (https://t.me/@bitship1_1). This is a classic fake developer persona used to build false trust and solicit direct contact, consistent with crypto bot scam patterns targeting traders on Polymarket and Kalshi. (location: page.html:1324-1326, page-text.txt:931-932)

critical

credential harvesting

The repository instructs users to place sensitive private key credentials (KALSHI_API_KEY, KALSHI_PRIVATE_KEY_PATH, KALSHI_PRIVATE_KEY_PEM, POLYMARKET_PRIVATE_KEY) into a local .env file for a bot authored by an unknown party with a Telegram contact handle. This pattern—free trading bot + credential setup instructions + social media contact—is a well-known credential harvesting vector targeting crypto trading platform API keys and private keys. (location: page.html:1338-1343, page-text.txt:944-988)

medium

social engineering

The 'Prove of Work' section links to a separate GitHub repository (Stuboyo77/polymarket-kalshi-arbitrage-trading-bot) to provide fake legitimacy. Cross-referencing unrelated accounts to fabricate credibility is a common trust-building technique in crypto scam repositories. (location: page.html:1328, page-text.txt:933-934)

low

hidden content

The repository title, meta description, og:title, og:description, and Twitter card all repeat the phrase 'Polymarket Kalshi Arbitrage Trading Bot' exactly 7 times. This keyword-stuffing pattern is used to inflate search engine visibility and attract victims searching for arbitrage bots, and may also be used to manipulate AI agent summarization of the page content. (location: page.html:165, page.html:213, page.html:221-222)

API

curl https://api.brin.sh/page/github.com%2Fseabra98%2FPolymarket-Kalshi-Arbitrage-Bot

FAQ: how to interpret this assessment

Common questions teams ask before deciding whether to use this web page in agent workflows.

Is github.com/seabra98/Polymarket-Kalshi-Arbitrage-Bot safe for AI agents to use?

github.com/seabra98/Polymarket-Kalshi-Arbitrage-Bot currently scores 66/100 with a caution verdict and medium confidence. The goal is to protect agents from high-risk context before they act on it. Treat this as a decision signal: higher scores suggest lower observed risk, while lower scores mean you should add review or block this web page.

How should I interpret the score and verdict?

Use the score as a policy threshold: 80–100 is safe, 50–79 is caution, 20–49 is suspicious, and 0–19 is dangerous. Teams often auto-allow safe, require human review for caution/suspicious, and block dangerous.

How does brin compute this web page score?

brin evaluates four dimensions: identity (source trust), behavior (runtime patterns), content (malicious instructions), and graph (relationship risk). Analysis runs in tiers: static signals, deterministic pattern checks, then AI semantic analysis when needed.

What do identity, behavior, content, and graph mean for this web page?

Identity checks source trust, behavior checks unusual runtime patterns, content checks for malicious instructions, and graph checks risky relationships to other entities. Looking at sub-scores helps you understand why an entity passed or failed.

Why does brin scan packages, repos, skills, MCP servers, pages, and commits?

brin performs risk assessments on external context before it reaches an AI agent. It scores that context for threats like prompt injection, hijacking, credential harvesting, and supply chain attacks, so teams can decide whether to block, review, or proceed safely.

Can I rely on a safe verdict as a full security guarantee?

No. A safe verdict means no significant risk signals were detected in this scan. It is not a formal guarantee; assessments are automated and point-in-time, so combine scores with your own controls and periodic re-checks.

When should I re-check before using an entity?

Re-check before high-impact actions such as installs, upgrades, connecting MCP servers, executing remote code, or granting secrets. Use the API in CI or runtime gates so decisions are based on the latest scan.

Learn more in threat detection docs, how scoring works, and the API overview.

Last Scanned

March 25, 2026

Verdict Scale

safe80–100
caution50–79
suspicious20–49
dangerous0–19

Trust Graph

Disclaimer

Assessments are automated and may contain errors. Findings are risk indicators, not confirmed threats. This is a point-in-time assessment; security posture can change.

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