context safety score
A score of 43/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
phishing
1 deceptive links where visible host does not match destination host
brand impersonation
The domain firefox.de.softmany.com uses Mozilla Firefox's brand name, logo, and product identity to present itself as an official or authorized Firefox download source. The site is operated by Softmany.com, a third-party software distribution platform with no affiliation to Mozilla. It uses Firefox's exact product name, version number (149.0), and branding throughout, creating a deceptive impression of legitimacy. (location: page.html: <title>, <h1>, structured data (lines 59-99), app-title-sc section (lines 434-438))
social engineering
The site presents itself as an official Mozilla Firefox download page, using urgency language ('Kostenloser Download', 'die neueste Version'), inflated trust signals (5.0 rating with only 1 vote, fabricated review authored by 'Softmany.com'), and Mozilla Organization attribution to manipulate users into downloading software from an unauthorized third-party distributor rather than from mozilla.org. The download button links to firefox.de.softmany.com/windows/download, not to official Mozilla servers. (location: page.html: lines 449-465 (rating form), lines 82-98 (structured data review), line 505-511 (download button))
credential harvesting
A hidden POST form (id='ratingForm') submits to https://firefox.de.softmany.com/rate-content with a CSRF token embedded as a hidden field. While nominally a rating form, the form includes hidden inputs (content_id, _token) and the fetch-based submission sends user interaction data back to the server. The CSRF token (PBdZGBR8EV2RrZh62gSuMqszlAF1TTFPVe1NkuEF) is exposed in both the HTML and the JavaScript fetch call headers, representing a data collection mechanism embedded in a page impersonating an official software source. (location: page.html: lines 449-452 (hidden form), lines 831-839 (fetch with X-CSRF-TOKEN header))
hidden content
Lazy-loaded screenshot images use a 1x1 transparent GIF as placeholder (data:image/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==) — this is the 12 suspicious base64 blobs flagged by Tier 2 scanning. These are standard lazy-loading placeholders (lazysizes library) and do not contain injected payloads. Confirmed false positive for injection, but noted as hidden/deferred content. (location: page.html: lines 519, 530, 541, 552, 563, 574, 585 (data-src lazy load img tags))
social engineering
The structured data (ld+json) lists Mozilla Organization as the author with a link to mozilla.org, while the review author is listed as 'Softmany.com'. This inconsistency is designed to make search engines and AI agents index the page as if Mozilla itself authored/endorsed it, while the actual content and downloads originate from Softmany.com. The aggregateRating shows 5.0 from only 1 vote — a manipulated trust signal. (location: page.html: lines 72-96 (ld+json author and review fields))
malicious redirect
The download button (line 505) links to https://firefox.de.softmany.com/windows/download — a third-party download endpoint, not mozilla.org. Users clicking 'Download für Windows' are redirected to a Softmany-controlled download pipeline that may serve bundled or modified software installers. The deceptive link count of 1 flagged in Tier 2 corresponds to this download link masquerading as an official Firefox download. (location: page.html: line 505 (href='https://firefox.de.softmany.com/windows/download'))
curl https://api.brin.sh/domain/firefox.de.softmany.comCommon questions teams ask before deciding whether to use this domain in agent workflows.
firefox.de.softmany.com currently scores 43/100 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.
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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