ScraperAPI Skills

The trigger phrases include broad requests like 'get web data for my agent', 'scrape a website in my app', and 'add web scraping to my project', which can activate this skill in contexts that are not explicitly asking for ScraperAPI. Over-broad invocation increases the chance that user-supplied URLs, queries, and content are routed to a third-party service unexpectedly, creating privacy and data-handling risk.

This example sends a user-selected URL and the API key to ScraperAPI, and the skill metadata already states that user-supplied queries, URLs, and content are transmitted externally. In a skill that may be triggered broadly, this creates a real data egress risk because sensitive internal URLs, tokens in URLs, or proprietary content could be forwarded to a third party without sufficiently explicit consent or sanitization.

The REST examples instruct direct transmission of target URLs and authentication material to an external scraping service. Because the skill is designed to operationalize arbitrary web scraping requests, this can expose sensitive user inputs or cause unintended third-party processing when users provide confidential targets or data-bearing URLs.

This example shows externally sending rendered-page requests and structured search queries to ScraperAPI, which may include user intent, search terms, and browsing targets. In combination with the broad triggers and onboarding role, the skill can normalize third-party transmission of potentially sensitive prompts or investigative queries that users may not realize are leaving the local environment.

The structured Amazon and async job examples continue the pattern of sending user-controlled inputs and API credentials to external endpoints for processing. While expected for this product, it is still a true security concern because the skill facilitates broad data egress and could be used to transmit sensitive URLs, job payloads, or business data to a third party at scale.

This duplicate finding points to the same outbound POST to ScraperAPI carrying credentials and target request data. Even though the transmission is expected for a scraping integration, it is still a genuine security-relevant behavior because it exports user-controlled data and authentication material to an external service.

This duplicate finding points to the same outbound POST to ScraperAPI carrying credentials and target request data. Even though the transmission is expected for a scraping integration, it is still a genuine security-relevant behavior because it exports user-controlled data and authentication material to an external service.

YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).

The trigger scope is broad enough to activate on generic research or contact-finding requests, which increases the chance the skill runs in situations where users did not explicitly intend third-party scraping or personal-data enrichment. Because the skill then performs external searches and profile synthesis automatically, over-triggering can cause unnecessary collection and disclosure of personal information.

The skill explicitly instructs the model to gather and present personal contact details, including emails, phone numbers, locations, and social profiles, into a consolidated dossier. This creates a doxxing-style enrichment workflow that can facilitate targeted phishing, harassment, or unauthorized profiling even when data is scraped from public sources.

Using an email address as a seed to derive a person's identity, employer, and related company details materially increases privacy risk because a single identifier can be expanded into a fuller profile without the subject's consent. This supports deanonymization and targeted social-engineering workflows, especially when combined with search and scraping across multiple sources.

The synthesis step turns scattered public and scraped data into a structured contact card, which lowers the effort needed to operationalize personal information for phishing, impersonation, or surveillance. Aggregation meaningfully raises the sensitivity of the data beyond the risk of any single source because it produces a ready-made intelligence profile.

The skill authorizes broad external search and arbitrary URL fetching driven by discovered links, with no meaningful allowlist or destination restrictions. That enables exfiltration of user-supplied queries and URLs to third parties and increases the risk of collecting data from unexpected or sensitive sources during automated browsing.

The trigger text is broad enough to match common informational requests like general market questions, pricing questions, or trend questions, which can cause the agent to invoke this skill when the user did not explicitly intend external web research. Because the skill transmits user-supplied queries, URLs, and content to ScraperAPI, over-triggering increases unnecessary data exfiltration and can lead to privacy and compliance issues.

The trigger scope is unusually broad, covering generic activities like web scraping, research, shopping, SEO, market research, and product lookup. That can cause the skill to activate for many ordinary user requests and route user queries, URLs, and page content to a third-party scraping service, increasing the chance of unnecessary data exposure, unexpected tool use, and bypass of safer default web tools.

The Maps guidance explicitly recommends always supplying precise latitude/longitude for local queries but provides no caution about collecting, transmitting, or retaining sensitive geolocation data. In this skill context, user-supplied queries and coordinates are sent to a third-party service, which increases privacy risk and can expose exact user or target locations unnecessarily.

The guide explicitly promotes scraping that 'handles proxy rotation, CAPTCHAs, and anti-bot measures automatically' without any caution about authorization, terms-of-service, privacy, or legal constraints. In this skill context, that omission materially increases misuse risk because the tool is positioned for broad scraping tasks and transmits user-supplied URLs and queries to a third party, making it easier for users to bypass protections without informed consent or compliance checks.

The documentation recommends geo-targeting and premium proxy use but does not warn that requests may traverse third-party proxy infrastructure or different jurisdictions, which can create legal, compliance, and data-handling exposure. Given the skill metadata explicitly states that user-supplied queries, URLs, and content are transmitted to ScraperAPI, this omission is more dangerous because users may unknowingly send regulated or sensitive data through external networks.

The webhook workflow takes user-supplied company input and sends it directly to ScraperAPI/Google Search, which is a third-party service, without any built-in notice, consent check, or data-minimization guidance in the example itself. While the skill metadata notes that user-supplied queries are transmitted externally, someone copying this workflow may expose user input to an external processor without realizing the privacy and compliance implications.

The crawler configuration requires a crawlerCallbackUrl where ScraperAPI will POST crawl results, which means scraped page contents and metadata are transmitted to an externally reachable endpoint. The reference documents the mechanics but does not clearly warn about this data flow, increasing the risk that users unknowingly send sensitive, proprietary, or regulated data off-platform or to an exposed webhook.

The skill explicitly instructs use of external services and includes a direct API fetch from api.n8n.io, while the skill metadata also states that user-supplied queries, URLs, and content are transmitted to ScraperAPI. In this context, generated workflows may send user-controlled or sensitive data to third-party infrastructure without strong minimization, consent, or trust-boundary warnings at the point of use.

Code accesses environment variables that may contain secrets (API keys, tokens). This is a common pattern for credential theft.

Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.

Credentials or environment variables flow to a network sink. This is a high-confidence indicator of credential exfiltration.

The skill clearly requires environment variables, writes output files, and performs network requests, yet it does not declare explicit permissions for those capabilities. This creates a transparency and policy-enforcement gap: users or orchestrators may invoke the skill without understanding that sensitive queries and scraped content will be transmitted externally and persisted locally.