Is sigma.ru safe?

suspiciouslow confidence
40/100

context safety score

A score of 40/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.

identity
90
behavior
80
content
7
graph
30

8 threat patterns detected

medium

encoded payload

suspicious base64-like blobs detected in page content

medium

malicious redirect

script/meta redirect patterns detected in page source

high

cloaking

Page conditionally redirects based on referrer or user-agent

high

malicious redirect

Page uses a JavaScript setTimeout redirect (window.location.href = construct_utm_uri(...)) that fires after 1 second, silently redirecting visitors to a constructed URL before any visible content loads. The destination is dynamically built from referrer data and cookie-stored parameters (__js_p_), making the redirect target opaque and unauditable at scan time. (location: page.html:36-48, script block)

high

obfuscated code

The get_jhash() function runs a CPU-intensive loop of 1,677,696 iterations performing bitwise and modular arithmetic to produce a hash value stored in the __jhash_ cookie. This pattern is characteristic of bot-detection or browser fingerprinting evasion logic, and its true purpose is obscured through non-descriptive variable names and excessive computational complexity. (location: page.html:7, get_jhash function)

medium

hidden content

The page presents no visible content to the user — only a centered 66x66 pixel GIF image rendered via an inline base64 data URI. All functional behavior is entirely hidden inside JavaScript. The noindex, noarchive robots meta tag additionally suppresses archiving, preventing forensic review of the page's historical state. (location: page.html:1-2, <head> and <body>)

medium

social engineering

The page silently harvests the visitor's browser User-Agent string and stores it in the __jua_ cookie, then uses referrer-based logic to classify traffic source (organic vs referral, mapping known search engines). This enables downstream targeting or profiling of visitors without disclosure or consent, facilitating tailored social engineering or ad fraud. (location: page.html:43, document.cookie __jua_ assignment; lines 8-9, get_utm_medium and construct_utm_uri functions)

low

prompt injection

The robots meta tag 'noindex, noarchive' instructs crawlers and AI indexing agents to neither index nor cache this page. While individually benign, combined with the redirect and fingerprinting behavior, this directive is used to evade AI-based threat detection agents and web archiving, a technique consistent with pages that intend to behave differently when observed vs. when live. (location: page.html:1, <meta name='robots' content='noindex, noarchive'>)

API

curl https://api.brin.sh/domain/sigma.ru

FAQ: how to interpret this assessment

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

Is sigma.ru safe for AI agents to use?

sigma.ru currently scores 40/100 with a suspicious verdict and low 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 domain.

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 domain 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 domain?

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 4, 2026

Verdict Scale

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

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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