context safety score
A score of 72/100 indicates minor risk signals were detected. The entity may be legitimate but has characteristics that warrant attention.
prompt injection
Hidden HTML element contains AI-targeting instructions
social engineering
The repository title and description contain massively repeated keyword spam ('polymarket arbitrage bot polymarket arbitrage bot polymarket bot polymarket bot polymarket trading bot polymarket trading bot bot bot bot...') designed to manipulate search engine rankings and lure users searching for legitimate trading tools into installing this unvetted bot that handles real financial credentials and executes live orders. (location: page.html:165, page.html:213, page.html:1448 — <title> and <meta name='description'> and About sidebar)
credential harvesting
The repository README explicitly instructs users to configure KALSHI_API_KEY, KALSHI_PRIVATE_KEY_PATH or KALSHI_PRIVATE_KEY_PEM (RSA private key), and POLYMARKET_PRIVATE_KEY (Ethereum wallet private key) inside a .env file. An unknown actor ('0xFortuneRust') publishing an unverified trading bot that requests users to hand over API keys and crypto wallet private keys poses a serious credential harvesting risk — the bot code itself is unreviewed and could silently exfiltrate these secrets. (location: page-text.txt:950-996 — README Environment Variables / Quick Start section)
social engineering
The bot is framed as a legitimate arbitrage tool with professional README structure (Quick Start, NPM Scripts, Programmatic API, Risk Notice) to build false trust and lower the user's guard before they supply real API keys and private keys granting full control of their Kalshi and Polymarket accounts. The 'Risk Notice' section normalises running with live funds, nudging users toward enabling real-money execution. (location: page-text.txt:1035-1036 — Risk Notice section)
curl https://api.brin.sh/page/github.com%2F0xFortuneRust%2Fpolymarket-kalshi-arbitrage-trading-botCommon questions teams ask before deciding whether to use this web page in agent workflows.
github.com/0xFortuneRust/polymarket-kalshi-arbitrage-trading-bot currently scores 72/100 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.
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.
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.
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.
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.
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.
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.
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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