context safety score
A score of 43/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
encoded payload
suspicious base64-like blobs detected in page content
cloaking
Page loads content in transparent or zero-size iframe overlay
js obfuscation
JavaScript uses Function constructor for runtime code generation
brand impersonation
The site operates as 'SSSTik' and presents itself as a TikTok-affiliated downloader, using TikTok branding, terminology ('TT', 'TikTok'), and visual identity throughout. The footer explicitly states 'We are not affiliated with TikTok, Douyin or Bytedance,' confirming deliberate use of TikTok's brand to attract users while disclaiming any official relationship. The domain name 'ssstik.io' mimics 'TikTok' branding. (location: page.html: <title>, header logo, throughout body text, footer disclaimer)
social engineering
The site uses high-pressure social proof claims including a fabricated or unverifiable aggregate rating of 4.9 stars from 297,531 reviews embedded in JSON-LD structured data. The site also claims to be 'the most popular tiktok video downloader' without substantiation, and promotes an APK download link, encouraging users to sideload an Android application outside of official app stores. (location: page.html: <script type='application/ld+json'> AggregateRating block; menu APK link /apk)
malicious redirect
JavaScript dynamically rewrites the 'Install App' header button href based on device type (iOS/Android) using randomized A/B routing across multiple third-party app IDs (com.video.videodownloader_appdl, com.video.videodownloader_appdl_lite, com.universal.video.downloader). Users are silently redirected to different app store listings based on a random number, with no disclosure. The 'universal' app ID 'com.universal.video.downloader' is particularly generic and unverifiable as the site's own app. (location: page.html: inline <script> in header, android_apps_for_header and ios_apps_for_header objects)
obfuscated code
The partnerAlerts JavaScript object contains multiple Base64-encoded strings for platforms including 'likee', 'twitter', 'facebook', 'youtube', 'instagram', and 'threads'. These encoded strings contain HTML with affiliate/UTM-tracked redirect links to third-party downloader sites (ssstwitter.com, getmyfb.com, reelsvideo.io, savethr.com, likeedownloader.com) that are injected into the DOM as error messages. This obfuscation hides the affiliate redirect destinations from casual inspection. (location: page.html: var partnerAlerts = { ... } script block near </body>)
hidden content
A zero-dimension iframe loading Google Tag Manager (GTM-K3K8RD9) is embedded inside a <noscript> tag with style='display:none;visibility:hidden', ensuring tracking even when JavaScript is disabled. Additionally, the s_altvign variable is set to ['XXX'] in the site configuration script, suggesting an alternate vignette/ad configuration that may serve adult content ads under certain conditions. (location: page.html: <noscript><iframe src='https://www.googletagmanager.com/ns.html?id=GTM-K3K8RD9'...>; var s_altvign = ['XXX'])
social engineering
The site promotes an APK download page (/apk) via main navigation, encouraging Android users to download an app package directly — bypassing Google Play Store security review. This is a common vector for distributing malware-laced apps under the guise of a legitimate utility. (location: page.html: <a href='/apk' class='pure-menu-link' target='_self'>APK</a>)
curl https://api.brin.sh/domain/ssstik.ioCommon questions teams ask before deciding whether to use this domain in agent workflows.
ssstik.io 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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